Resources: Information Technology Training

1. Terminology

OpenStax Introduction to Computer Science (free, openly licensed textbook) 
A resource for learning foundational vocabulary such as algorithms, programming, data, hardware, software, networks, and computing careers. Written for introductory college learners and places terminology in the context of real computing problems rather than presenting it as an isolated glossary. 
Reference: OpenStax. (2024). Introduction to computer science. Rice University. https://openstax.org/details/books/introduction-computer-science

 

OpenStax Foundations of Information Systems (free, openly licensed textbook)
Use the opening chapters to distinguish among data, information, information systems, information technology, people, procedures, and organizational processes. This is especially helpful for students taking business, IT, or information-systems courses.
Reference: OpenStax. (2025). Foundations of information systems. Rice University. https://openstax.org/details/books/foundations-information-systems

 

TechTerms Computer Dictionary (free online reference)A searchable dictionary for checking unfamiliar technical words encountered in textbooks, lectures, software menus, and assignments. Students should use it to confirm a term’s meaning, then record the term in a personal course glossary with an example.
Reference: Sharpened Productions. (n.d.). TechTerms computer dictionary. https://techterms.com/

2. Information Technology Concepts

OpenStax Foundations of Information Systems (free, openly licensed textbook)
Introduces the major components of information systems—hardware, software, data, people, and procedures—and explains how organizations collect, process, store, retrieve, and distribute information. It provides a solid conceptual base before students focus on a particular device or application.
Reference: OpenStax. (2025). Foundations of information systems. Rice University. https://openstax.org/details/books/foundations-information-systems

 

GCFGlobal Computer Basics (free online tutorials)
Beginner-oriented lessons explain computers, mobile devices, the internet, cloud services, hardware, software, files, online safety, and digital citizenship in plain language. It is particularly useful for students who need a low-pressure review before beginning more technical coursework.
Reference: Goodwill Community Foundation. (n.d.). Computer basics. GCFGlobal. https://edu.gcfglobal.org/en/computerbasics/

 

Cisco Networking Academy: Introduction to Cybersecurity (free course; account may be required)
An accessible introduction to digital security concepts, including common threats, personal privacy, device protection, and responsible online behavior. It adds an important security perspective to a basic IT course.
Reference: Cisco Networking Academy. (n.d.). Introduction to cybersecurity. https://www.netacad.com/courses/cybersecurity/introduction-cybersecurity

3. Operating Systems

LibreTexts: Types of Software (free, openly licensed learning material)
This reading distinguishes system software from application software and explains the operating system’s central roles: managing hardware resources, providing a user interface, and supporting application programs. It also helps students compare desktop and mobile operating systems.
Reference: LibreTexts. (2022, August 9). Types of software. https://workforce.libretexts.org/Courses/Evergreen_Valley_College/Information_Systems_for_Business_2e/03%3A_Software/3.02%3A_Types_of_Software[workforce.libretexts]

GCFGlobal: Understanding Operating Systems (free online tutorial)
An overview of Windows, macOS, Linux, and mobile operating systems. Use it to learn what an operating system does before practicing file management, settings, software installation, and updates on a personal device.
Reference: Goodwill Community Foundation. (n.d.). Understanding operating systems. GCFGlobal. https://edu.gcfglobal.org/en/computerbasics/understanding-operating-systems/1/

Ubuntu Desktop Documentation (free and open-source documentation)
Ubuntu’s official documentation provides practical examples of working with an open-source Linux operating system, including files, software, settings, and basic command-line tasks. It is useful for students who want hands-on exposure beyond Windows or macOS.
Reference: Canonical Ltd. (n.d.). Ubuntu desktop documentation. https://help.ubuntu.com/

4. Artificial Intelligence

IBM SkillsBuild: Artificial Intelligence Fundamentals (free online learning)
A beginner pathway that introduces AI history, machine learning, natural-language processing, computer vision, deep learning, neural networks, and practical applications. It is especially useful because it combines conceptual instruction with interactive activities and can lead to a digital credential.
Reference: IBM. (n.d.). Artificial intelligence fundamentals. IBM SkillsBuild. https://skillsbuild.org/

OpenStax Foundations of Information Systems, Chapter 10 (free, openly licensed textbook)
This reading connects AI to information systems and emerging technology. It introduces AI, machine learning, neural networks, cloud computing, and mobile computing while emphasizing data quality, potential bias, privacy, and the importance of responsible use.
Reference: OpenStax. (2025). The evolving frontiers of information systems. In Foundations of information systems. Rice University. https://openstax.org/books/foundations-information-systems/pages/10-2-the-evolving-frontiers-of-information-systems

Elements of AI (free online course)
A widely used introductory course that helps non-specialists understand what AI can and cannot do, how machine learning works at a high level, and why ethical and societal questions matter. It is appropriate for students in any major.
Reference: University of Helsinki, & MinnaLearn. (n.d.). Elements of AI. https://www.elementsofai.com/

5. Productivity Software for Problem Solving

OpenStax Workplace Software and Skills (free, openly licensed textbook)
This is an excellent core text for first-year students because it covers computer literacy, workplace software, Microsoft 365, Google Workspace, word processing, spreadsheets, and presentations. Its guided practice and authentic scenarios help students use software to analyze problems, make decisions, collaborate, and communicate results.

Reference: OpenStax. (2023). Workplace software and skills. Rice University. https://openstax.org/details/books/workplace-software-skills

 

LibreOffice (free and open-source software)
A no-cost, open-source productivity suite: Writer for documents, Calc for spreadsheets, Impress for presentations, and Base for databases. It is a useful alternative for students who do not have institutional access to Microsoft 365 or who want transferable software skills.
Reference: The Document Foundation. (n.d.). LibreOffice: Free and private office suite. https://www.libreoffice.org/

 

Google Workspace Learning Center (free online training)
Provides tutorials for Docs, Sheets, Slides, Drive, Forms, and other cloud-based collaboration tools. It is particularly useful for group projects that require real-time editing, commenting, sharing permissions, and version history.
Reference: Google. (n.d.). Google Workspace Learning Center. https://workspace.google.com/training/[workspace.google]

6. Computer Technology Trends

OpenStax Foundations of Information Systems, Chapter 10 (free, openly licensed textbook)
Begin here for a foundational overview of emerging technologies, including AI, machine learning, cloud computing, mobile computing, cybersecurity, data analytics, social media, and the Internet of Things. The chapter is useful because it also asks students to consider innovation’s organizational and social implications.
Reference: OpenStax. (2025). The evolving frontiers of information systems. In Foundations of information systems. Rice University. https://openstax.org/books/foundations-information-systems/pages/10-2-the-evolving-frontiers-of-information-systems

 

Pew Research Center: Internet and Technology (free research reports)
Pew Research Center publishes accessible, nonpartisan research on technology adoption, social media, AI, privacy, online behavior, and the digital divide. Students can use its reports to add current evidence and data to technology-trends discussions.
Reference: Pew Research Center. (n.d.). Internet and technology. https://www.pewresearch.org/internet/

 

MIT Technology Review (some free content; subscription content also available)
A reputable technology-journalism source for following developments in AI, computing, climate technology, biotechnology, cybersecurity, and digital policy. Students should compare its reporting with primary sources and scholarly research when writing assignments.
Reference: MIT Technology Review. (n.d.). MIT Technology Review. https://www.technologyreview.com/

7. Professional Documents

OpenStax Workplace Software and Skills (free, openly licensed textbook)
Use this text for guided practice in word processing, professional communication, document design, collaboration, and workplace-ready formatting. It is especially valuable because it covers comparable tasks in both Microsoft 365 and Google Workspace.
Reference: OpenStax. (2023). Workplace software and skills. Rice University. https://openstax.org/details/books/workplace-software-skills

 

Google Workspace Learning Center: Google Docs (free online training)
Google’s official training materials explain how to create, revise, format, share, comment on, and collaborate in documents. This is a practical option for students preparing collaborative reports, résumés, memos, and peer-review assignments.
Reference: Google. (n.d.). Google Workspace Learning Center. https://workspace.google.com/training/

 

Microsoft Support: Office Training Center (free online training; software access may require a license)
Microsoft’s training center includes official learning resources for Word and other Microsoft 365 applications. Students can use it to practice document formatting, templates, collaboration, accessibility features, and professional layout.
Reference: Microsoft. (n.d.). Train your users on Office and Microsoft 365. Microsoft Support. https://support.microsoft.com/en-us/office/o365-itpro/train-your-users-on-office-and-microsoft-365[support.microsoft]

 

Purdue Online Writing Lab: Professional, Technical Writing (free online writing guide)
This guide supports the writing decisions behind professional documents, including audience awareness, tone, clarity, résumé writing, workplace correspondence, and document design. Pair it with word-processing practice for stronger academic and career communication.
Reference: Purdue Online Writing Lab. (n.d.). Professional, technical writing. Purdue University. https://owl.purdue.edu/owl/subject_specific_writing/professional_technical_writing/index.html

8. Spreadsheets

LibreOffice Calc Guide (free and open-source documentation)
LibreOffice’s community-written documentation teaches spreadsheet fundamentals using Calc, including formulas, functions, data organization, charts, and analysis. It is a strong choice for students who want to learn concepts that transfer to Excel and Google Sheets.
Reference: The Document Foundation. (n.d.). LibreOffice Calc guide. LibreOffice Bookshelf. https://books.libreoffice.org/en/CG/latest/

OpenStax Workplace Software and Skills (free, openly licensed textbook)
The textbook provides structured activities for using spreadsheets in academic and workplace contexts. Students can practice formulas, tables, data visualization, organization, and problem solving while comparing features across Microsoft Excel and Google Sheets.
Reference: OpenStax. (2023). Workplace software and skills. Rice University. https://openstax.org/details/books/workplace-software-skills

Google Workspace Learning Center: Google Sheets (free online training) 

Google’s official Sheets tutorials are useful for learning cloud-based spreadsheets, collaboration, formulas, sorting, filtering, charts, and sharing data with a team.  

Reference: Google. (n.d.). Google Workspace Learning Center. https://workspace.google.com/training/[workspace.google]

Microsoft Support: Excel Help and Learning (free online training; software access may require a license)
Official Excel tutorials provide practical instruction in formulas, functions, tables, charts, PivotTables, and data analysis. This is a good reference when a course specifically requires Microsoft Excel.
Reference: Microsoft. (n.d.). Excel help and learning. https://support.microsoft.com/en-us/excel

9. Presentations

LibreOffice Impress Guide (free and open-source documentation)
The official LibreOffice documentation introduces presentation creation with Impress, including slide layouts, visual elements, charts, media, transitions, and presentation delivery. It is useful for learning principles that transfer to PowerPoint and Google Slides.
Reference: The Document Foundation. (n.d.). LibreOffice Impress guide. LibreOffice Bookshelf. https://books.libreoffice.org/en/IG/latest/

OpenStax Workplace Software and Skills (free, openly licensed textbook)
This resource provides practice in using presentation software for real workplace and academic communication. Students can develop skills in slide design, visual hierarchy, concise writing, collaboration, and preparing content for an audience.
Reference: OpenStax. (2023). Workplace software and skills. Rice University. https://openstax.org/details/books/workplace-software-skills

Google Workspace Learning Center: Google Slides (free online training)
Google’s official Slides learning materials help students create, edit, share, comment on, and present slide decks in a collaborative environment. This is particularly helpful for team presentations and asynchronous peer feedback.
Reference: Google. (n.d.). Google Workspace Learning Center. https://workspace.google.com/training/

Microsoft Support: PowerPoint Help and Learning (free online training; software access may require a license)
Microsoft’s official PowerPoint resources cover slide creation, templates, media, speaker notes, accessibility, animations, and presenting. Use it when course assignments require PowerPoint-specific features.
Reference: Microsoft. (n.d.). PowerPoint help and learning. https://support.microsoft.com/en-us/powerpoint

10. Databases

LibreOffice Base Guide (free and open-source documentation)
The official Base documentation provides an accessible introduction to desktop databases. Students can learn to create tables, forms, queries, and reports while developing a practical understanding of how structured information is stored and retrieved.
Reference: The Document Foundation. (n.d.). LibreOffice Base guide. LibreOffice Bookshelf. https://books.libreoffice.org/en/BG/latest/

OpenStax Foundations of Information Systems (free, openly licensed textbook)
This text helps students understand databases in the broader context of information systems, data management, organizational decision-making, and ethical issues such as privacy and data quality. It is most useful as conceptual preparation before database-design software practice.
Reference: OpenStax. (2025). Foundations of information systems. Rice University. https://openstax.org/details/books/foundations-information-systems

SQLBolt (free interactive SQL lessons)
SQLBolt provides browser-based interactive lessons in SQL, the language commonly used to retrieve and manipulate data in relational databases. It is appropriate for beginners who need hands-on practice with queries such as SELECT, WHERE, JOIN, and GROUP BY.
Reference: SQLBolt. (n.d.). Learn SQL with simple, interactive exercises. https://sqlbolt.com/

Microsoft Support: Access Help and Learning (free online training; software access may require a license)
Microsoft’s official Access resources are useful for students assigned to create relational databases, tables, forms, queries, and reports in Microsoft Access.
Reference: Microsoft. (n.d.). Access help and learning. https://support.microsoft.com/en-us/access

11. Web Pages

MDN Web Docs: Learn Web Development (free and open web documentation)
MDN is one of the best starting points for learning web-page production. Its beginner materials explain how HTML structures content, CSS controls presentation and layout, and JavaScript adds behavior; students can build projects while learning accessible, standards-based practices.
Reference: Mozilla. (n.d.). Learn web development. MDN Web Docs. https://developer.mozilla.org/en-US/docs/Learn_web_development[developer.mozilla

 

freeCodeCamp Responsive Web Design (free interactive curriculum)
This hands-on curriculum teaches HTML and CSS through small projects and larger portfolio-style exercises. It is particularly effective for students who learn best by writing code and seeing immediate results in a browser.
Reference: freeCodeCamp. (n.d.). Responsive web design certification. https://www.freecodecamp.org/learn/2022/responsive-web-design/

 

W3C Web Accessibility Initiative: Introduction to Web Accessibility (free standards-based guidance)
Students should use this resource while building web pages to understand why accessible design matters and how choices involving headings, alternative text, color contrast, keyboard navigation, and semantic HTML affect users.
Reference: World Wide Web Consortium. (n.d.). Introduction to web accessibility. Web Accessibility Initiative. https://www.w3.org/WAI/fundamentals/accessibility-intro/

 

GitHub Pages Documentation (free web-publishing documentation)
GitHub Pages allows students to publish a basic static website directly from a GitHub repository. It is a useful next step after learning HTML and CSS because it teaches file organization, version control basics, and web publishing.
Reference: GitHub. (n.d.). What is GitHub Pages? GitHub Docs. https://docs.github.com/en/pages/getting-started-with-github-pages/what-is-github-pages

Leadership - Digital Forensics Lab: Delegating Assignments to Staff

Delegation means assigning work with authority, controls, safeguards, and oversight. ISO/IEC 17025 is designed to support laboratories in producing valid results, and accreditation assesses both competence and the operation of the quality system.[1]

Ten delegation tips:

1. Define the assignment and intended outcome
   State, in writing, exactly what is being delegated, why, and what a completed deliverable looks like.
   Example:“Validate the updated mobile-device extraction workflow and prepare a validation report for technical review by 30 September.”
2. Assign only within demonstrated competence
   Confirm the examiner is trained, authorized, and currently competent for the relevant activity—not merely available. Keep records that show the basis for the authorization. Competence and consistent operation are core expectations.[2]
3. Match the authority to the responsibility
   Say what the subordinate may decide independently, what requires supervisor approval, and what they must not do.
   Example:An examiner may perform a routine acquisition using an approved method, but may not introduce a new tool or materially modify a method without the required review and authorization.
4. Specify the approved method and documents
   Identify the current controlled procedure, work instruction, form, template, and software/tool version. Require the employee to use the current revision rather than an obsolete version. ISO/IEC 17025’s process and management-system requirements support technically valid work and controlled operations.[1]
5. Protect evidence integrity from the outset
   Explicitly set expectations for chain of custody, secure storage, access control, forensic imaging, hash verification, and contemporaneous notes.
   Example:“Before analysis, verify the evidence seal, log custody transfer, create and verify the forensic image, then work only from the verified copy.”
6. Set measurable acceptance criteria
   Avoid “do a good job.” Define the criteria that make the work acceptable: required checks, peer review, report sections, data to retain, and objective quality indicators.
   Example:“The report must include tool/version, acquisition method, hash values, limitations, results, and an independent technical review.”
7. Provide resources and remove constraints early
   Confirm the examiner has secure workspace access, validated tools, adequate storage, reference material, time, and access to a qualified reviewer. Delegation fails when responsibility is given without the resources needed to perform it.
8. Require escalation of exceptions and risks
   Tell the employee to pause and escalate circumstances outside the approved method or scope—such as encrypted media, an unsupported device, damaged storage, a failed hash comparison, or suspected contamination. This preserves impartiality and prevents an unapproved workaround from becoming routine practice.
9. Use planned check-ins, not constant takeover
   Establish proportionate milestones: initial plan, acquisition completion, preliminary findings, technical review, and final report. Ask questions that test understanding—“Which SOP applies, what controls will you record, and what would trigger escalation?”—rather than redoing the task yourself.
10. Close the loop and improve the system
    Review the output against the assignment’s acceptance criteria; document technical review, deviations, nonconforming work, corrective actions, and lessons learned where applicable. Give specific feedback and update training or procedures if the assignment exposed a recurring weakness. ISO/IEC 17025 emphasizes continuous improvement and keeping pace with relevant scientific and technological advances.[1]

Delegation example:

Assignment: “You are requested to conduct the forensic acquisition and preliminary examination of the seized Android phone, case DF-2026-041, using SOP DF-MOB-04 Rev. 7.”

Supervisor’s briefing should include:

• Scope:Acquisition and preliminary artifact identification only; no cloud-account requests or destructive procedures.
• Authority:Use validated, approved tools listed in the SOP; escalate if the device is unsupported, encrypted, damaged, or requires a method deviation.
• Evidence controls:Record custody transfer, photograph condition, document the device state, calculate and record verification hashes, and retain all relevant work files.
• Deliverables:Examination notes, acquisition log, hash-verification record, preliminary report, and complete case file for independent technical review.
• Milestones:Notify the supervisor after intake verification, after acquisition, and immediately upon any exception.
• Acceptance:Work is complete only after documentation is complete, the reviewer’s comments are resolved, and the supervisor authorizes release of the report.

References

1. https://en.wikipedia.org/wiki/ISO/IEC_17025   
2. https://anab.ansi.org/accreditation/iso-iec-17025-forensic-testing-laboratory/  
3. https://intranet.cityofmesquite.com/DocumentCenter/View/2354/The-10-Best-Tools-and-Tips-for-Delegating-Tasks-Efficiently-article-PDF 
4. https://www.sarahmhoban.com/blog/how-to-delegate-effectively 
5. https://www.nist.gov/document/report-digital-evidence-task-group-quality-study 
6. https://onlinelibrary.wiley.com/doi/10.1111/1556-4029.15254 
7. https://a2la.org/iso-iec-17025-vs-iso-iec-17020/ 
8. https://www.labmanager.com/comprehensive-guide-to-iso-iec-17025-accreditation-prep-for-forensic-labs-34639 
9. https://www.scribd.com/document/976480637/Management-Requirements-Notes-Iso-iec-17025-2017-Dfss-Fsl-1 
10. https://www.youtube.com/watch?v=N2K2a2BI_w8 
11. https://sytech-consultants.com/ensuring-trust-in-digital-evidence-17025-accreditation-for-law-enforcement/ 
12. https://www.forensicfocus.com/articles/safeguarding-digital-evidence-best-practices-and-the-critical-role-of-iso-iec-17025/ 
13. https://asana.com/resources/how-to-delegate 
14. https://online.hbs.edu/blog/post/how-to-delegate-effectively 
15. https://depts.washington.edu/edgh/namibia-lio/unit-10.html 
16. https://www.shrm.org/topics-tools/news/organizational-employee-development/managers-must-delegate-effectively-to-develop-employees 
17. https://gravitypayments.com/blog/delegation-tips-for-new-managers/ 
18. https://www.nonprofitlearninglab.org/post/how-to-delegate-tasks-responsibilities-as-a-supervisor 
19. https://www.youtube.com/watch?v=FulkBRIOErw 

IoT: Wearable Sleep Monitoring Device

Introduction

Recent research discusses a wearable IoT patch that monitors brain water dynamics during sleep (Ban et. al. 2026). This report describes the functions of the device and the significance for law enforcement.

What the device is

This article describes a soft, wireless forehead patch that tracks changes in brain water during sleep. It is an IoT-style wearable because it gathers data from the body, sends that data wirelessly, and supports analysis outside the device.

What the device is trying to do

The patch is designed to help researchers study how the brain manages fluid movement during sleep. The article links this to the brain’s cleaning process, which may be more active during certain sleep stages.

How it works

The device sits on the forehead and shines small amounts of light into the tissue using several light colors, including near-infrared light. A built-in light sensor measures the light that comes back, and the system uses those measurements to estimate changes related to water in the head, as well as blood-related signals.

The patch includes a small battery, electronics for signal processing, and Bluetooth low energy for wireless data transfer. The data can then be sent to another device, such as a computer, for storage and further analysis.

Why the design matters

Unlike large sleep systems, this device is soft, lightweight, and made to stay on the skin during sleep at home. The authors designed it to reduce discomfort and reduce signal problems caused by movement.

What the researchers found

In overnight home testing, the device recorded changing brain-water-related signals across wakefulness, non-REM sleep, and REM sleep. The researchers found patterns suggesting that these signals rise and fall with sleep stages and may reflect sleep-related fluid shifts in the brain.

The system also picked up rhythms related to breathing, heart activity, and slow sleep-related oscillations. This means the wearable may be useful not only for tracking possible brain fluid changes but also for giving a broader picture of sleep physiology.

What this means in everyday terms

In simple terms, this is a smart sleep patch for the forehead that aims to watch how fluid-related signals in the brain change through the night. The long-term goal is to create a more comfortable way to study brain health and sleep at home instead of relying only on bulky lab equipment.

Limits to keep in mind

The article does not claim that the patch directly measures cerebrospinal fluid flow or the brain’s cleaning process by itself. Instead, it measures optical signals that may be related to brain water changes, and the authors note that signals from the scalp and skull can also contribute.

The human study was also small, with only a few healthy adult participants. That means the device looks promising, but more testing is needed before it can be treated as a routine medical tool.

Why it could matter in investigations

If a victim or suspect was wearing a device like this around the time of a crime, the recorded data might help show whether the person was asleep, awake, resting, or moving during a certain period. That kind of timing information could matter to first responders, police officers, investigators, and prosecutors when they are trying to understand a timeline.

The device might also provide clues about whether the wearer had unusual physiological changes before or after an event, although that would require careful expert review. In practice, the information should be treated as supportive rather than final proof, because the article describes a research-stage device and not a fully validated forensic tool.

First responders could see value in such wearables if they help identify whether a person may have been asleep, unconscious, or under physical stress before discovery. Investigators and prosecutors could potentially use the data to compare reported events with recorded timing patterns, but only with proper legal process, technical validation, and caution about privacy, accuracy, and interpretation.

Glossary 

• Beer-Lambert law: A mathematical method used to estimate how substances affect light as it passes through material.
• Bluetooth low energy (BLE): A low-power wireless communication method used by small devices. 
• Cerebrospinal fluid (CSF): The clear fluid that surrounds and protects the brain and spinal cord.   
• EEG (electroencephalogram): A test that records electrical activity of the brain.   
• EOG (electrooculogram): A test that measures eye movements.
• Glymphatic system: The proposed waste-clearing system in the brain that helps move fluids and remove byproducts.  
• Hypnogram: A chart showing sleep stages over time.  
• Interstitial fluid (ISF): Fluid that sits between cells in body tissue.  
• Machine learning: A type of computer analysis that finds patterns in data and uses them for predictions or classification.  
• Motion artifact: Distortion in measurements caused by body movement.  
• Near-infrared spectroscopy (NIRS): A method that shines light into tissue and measures the returning light to estimate changes inside the body.  
• NREM sleep: Sleep stages that are not REM, including deeper restorative sleep.  
  Noninvasive: Doing a measurement without surgery or placing tools inside the body.  
• Optical density: A way of describing how much light is absorbed or blocked by tissue.  
• Photodetector: A sensor that detects light.  
• REM sleep: A sleep stage linked to vivid dreaming and rapid eye movements.  
• Signal-to-noise ratio (SNR): A measure of how clear a useful signal is compared with background interference.  
• Thermal safety: Whether a device stays within safe temperature limits during use. 

 

Ethics Lost: When Investigators Become Criminals

The investigation of the Silk Road drug trafficking operation was meant to bring down the online black marketplace. Concurrently, it also exposed something more troubling: two of the agents entrusted with dismantling the criminal enterprise secretly abandoned their sworn code of ethics and committed serious crimes of their own. A Drug Enforcement Administration (DEA) special agent and a U.S. Secret Service special agent used their access to undercover operations, digital evidence, and cryptocurrency accounts to enrich themselves, obstruct justice, and betray the public trust.

Their misconduct, eventually uncovered and prosecuted, highlights not only personal corruption but also systemic vulnerabilities in how digital evidence and virtual currency are handled. Even as the government pursued the operators of Silk Road, it had to turn inward and prosecute its own investigators for extortion, money laundering, and related offenses. The story of these two agents is a cautionary tale about the risks that arise when powerful investigative tools meet weak internal controls. 

Background: Silk Road and the Baltimore Task Force

Silk Road operated as an online marketplace where users could buy and sell illegal drugs and other contraband, typically using bitcoin or other digital currencies to conceal their identities and the flow of funds. The site’s creator, Ross Ulbricht, operated under the alias “Dread Pirate Roberts” and became the central target of a broad federal investigation into the platform’s activities and infrastructure. Federal authorities viewed Silk Road as a pivotal test case for enforcing drug and financial laws in the emerging world of dark‑web markets and cryptocurrencies.

To meet that challenge, the government formed the Baltimore Silk Road Task Force, a multi‑agency team that included the DEA, Secret Service, FBI, IRS‑Criminal Investigation, and other components. The task force relied heavily on undercover personas, digital forensics, and the management of bitcoin wallets used in controlled transactions with Silk Road. Agents had to navigate both traditional investigative techniques and the technical demands of tracing, seizing, and safeguarding virtual currency. In that environment, two agents, Carl M. Force and Shaun W. Bridges, saw opportunities for personal gain.

The DEA Agent: Carl M. Force

Assignment and Undercover Role

Carl M. Force was a veteran DEA special agent with roughly 15 years of service when he joined the Baltimore Silk Road Task Force around 2012. In that role, he operated a sanctioned online persona known as “Nob,” a supposed criminal intermediary who communicated directly with Ross Ulbricht. Through “Nob,” Force was authorized to engage with Ulbricht, gather intelligence, and orchestrate controlled transactions on Silk Road. His position gave him direct access to Ulbricht’s trust and to significant amounts of digital currency passing through the investigation.

As “Nob,” Force’s communications with Ulbricht were part of the official investigative strategy. However, the same access that enabled law‑enforcement actions also gave Force the ability to manipulate information, solicit payments, and divert funds if he chose to disregard the rules. That is ultimately what he did, blurring the line between undercover work and personal profiteering.

Extortion Schemes and Covert Personas

Using his “Nob” persona, Force offered Ulbricht purported inside information about the government’s investigation and other services that would be valuable to someone operating an illicit marketplace. He represented that he had access to sensitive law‑enforcement data and that he could provide Ulbricht with updates and warnings about the case. In exchange, Force obtained bitcoin payments that, under the law and the terms of the investigation, constituted government property and evidentiary funds.

Force did not stop at the sanctioned persona. He created a second, unauthorized online identity known as “French Maid,” which he did not disclose to his superiors. Under this covert persona, he again approached Ulbricht and offered investigative information in return for payment, this time positioning “French Maid” as an independent source within law enforcement. Through “French Maid,” Force secretly solicited and received additional bitcoin—amounting to hundreds of thousands of dollars’ worth—outside any approved investigative plan. 

These schemes effectively turned the undercover operation into a vehicle for extortion. Ulbricht believed he was paying law‑enforcement insiders for protection and intelligence; in reality, he was paying a corrupt agent who was concealing the transactions from prosecutors and fellow investigators.

Misuse of Position at a Digital Currency Exchange

Force’s misconduct was not confined to the Silk Road undercover environment. Without DEA authorization, he took on an outside role as the chief compliance officer for CoinMKT, an online digital currency exchange. In that capacity, he leveraged his status as a DEA agent to pressure the company and its customers, while also positioning himself to control accounts with substantial holdings.

At one point, Force directed CoinMKT to freeze accounts containing approximately 337,000 dollars in cash and digital currency on the asserted basis of law‑enforcement authority. He then transferred roughly 300,000 dollars’ worth of the digital currency from those accounts into an account he personally controlled. By doing so, he turned a purported enforcement action into a direct act of theft. His dual roles—public agent and private compliance officer—created a glaring conflict of interest and a pathway to misappropriation.

Obstruction of Justice and Sentencing

When questions arose about his conduct, Force compounded his wrongdoing by obstructing justice. He admitted that he lied to federal prosecutors and other agents investigating his activities, attempting to conceal the bitcoin he had received from Ulbricht and the funds he diverted from CoinMKT. His false statements and omissions hindered efforts to understand what had happened to significant amounts of digital evidence and government property.

Ultimately, Force pleaded guilty to charges including extortion under color of official right, money laundering, and obstruction of justice. He was sentenced to a term of imprisonment—reported as 78 months—along with an order to pay substantial restitution and to serve a period of supervised release after completing his prison term. His case demonstrated that an agent’s lengthy tenure and prior service record offered no protection from prosecution when the evidence showed deliberate abuse of authority.

The Secret Service Agent: Shaun W. Bridges

Role in the Silk Road Task Force

Shaun W. Bridges served as a special agent with the U.S. Secret Service and was also assigned to the Baltimore Silk Road Task Force. His responsibilities included handling aspects of the digital evidence and virtual currency involved in the investigation. That role gave him access to bitcoin wallets, transaction records, and accounts associated with Silk Road and its users, including funds seized or controlled as part of the government’s operations.

In a complex investigation where virtual currency played a central role, Bridges’s technical responsibilities placed him in a position of significant trust. He had both the knowledge and the technical capability to move funds, reconfigure accounts, and initiate transfers under the cover of legitimate investigative needs—conditions that can be exploited when oversight is weak.

Theft and Laundering of Digital Currency

Bridges used his position to steal large quantities of digital currency that had been placed under government control. In an earlier case, he pleaded guilty to charges of money laundering and obstruction of justice for diverting more than 800,000 dollars’ worth of bitcoin that he accessed through his official duties. Those bitcoins were government property and critical pieces of evidence, but Bridges treated them as personal assets.

To conceal his theft, Bridges engaged in money‑laundering tactics designed to obscure the origin of the funds. He transferred the digital currency through various accounts, including intermediaries and exchanges, with the goal of breaking the audit trail that would tie the funds back to seized Silk Road assets. Such conduct undermined both the integrity of the investigation and the evidentiary chain‑of‑custody for digital assets.

Additional Proceedings and Sentencing

After his initial guilty plea and sentencing—a 71‑month prison term—Bridges became the subject of further scrutiny as additional transactions and accounts came to light. In a subsequent proceeding, he pleaded guilty to another count of money laundering related to the handling of digital currency connected to the Silk Road investigation. This second case reflected a broader pattern of misconduct rather than a single isolated incident.

Bridges thus faced multiple criminal judgments, each reinforcing the conclusion that he systematically abused his access to digital currency and investigative tools. The repeated proceedings also underscored how difficult it can be to fully reconstruct the flow of virtual assets once a trusted insider has manipulated the records and moved funds through multiple channels.

Parallels Between the Two Cases

The cases of Carl M. Force and Shaun W. Bridges share striking similarities. Both men were embedded in the same task force, dealing with the same investigation, and handling many of the same digital assets and undercover operations. Both used government‑controlled bitcoin wallets and online personas as gateways to personal enrichment, rather than as tools solely for evidence gathering and law enforcement.

In each case, the agents treated digital currency that was clearly government property—funds seized, controlled, or received during official operations—as if it belonged to them. They routed bitcoins into accounts they personally controlled, attempted to disguise the transfers, and failed to report the funds to prosecutors or supervising agents. Their schemes were not merely opportunistic; they involved deliberate planning, exploitation of investigative tools, and concealment. 

Both Force and Bridges also engaged in deception when their conduct came under scrutiny. Force lied to federal prosecutors and colleagues, while Bridges implemented money‑laundering tactics and obstructed justice to hide the origin and destination of the stolen funds. Their behavior demonstrates how insider misconduct can compromise not only financial integrity but also the broader pursuit of justice in high‑profile cases.

Institutional Response and Oversight

The exposure of these crimes did not happen by accident. Multiple investigative bodies became involved in uncovering the misconduct, including the FBI’s San Francisco Division, IRS‑Criminal Investigation, and internal oversight units such as the Department of Justice Office of the Inspector General and the Department of Homeland Security Office of Inspector General. Their efforts were critical in identifying irregularities in digital‑currency movements and in following the trail back to the agents responsible.

Prosecution of the cases was handled by the Department of Justice’s Criminal Division, including the Public Integrity Section, in coordination with the U.S. Attorney’s Office for the Northern District of California. That allocation of responsibility underscores how seriously the government treats corruption by its own officials, particularly in matters that involve complex financial systems and high‑impact investigations. The institutional response demonstrated that even within law‑enforcement circles, misconduct can lead to significant criminal penalties when properly investigated. 

These events also highlighted the importance of internal controls and external oversight in operations involving digital assets. Without the involvement of inspector general offices and specialized investigative teams, irregularities in bitcoin transfers and account manipulations might have gone unnoticed or remained unexplained. The eventual prosecutions show that oversight mechanisms can function effectively, but they also raise questions about how early warning signs might have been missed.

Vulnerabilities in Digital‑Evidence Handling

The Force and Bridges cases expose particular vulnerabilities in how digital evidence—especially cryptocurrency—is managed within law‑enforcement operations. When a single agent or a small group of agents can initiate transfers, create or control wallets, and operate undercover personas with limited real‑time oversight, the risk of misappropriation increases dramatically. Digital currency is both easily movable and, if handled through anonymizing tools or layered transactions, difficult to trace after the fact.

In the Silk Road investigation, agents controlled multiple bitcoin wallets and accounts used for undercover purchases, seizures, and storage of evidence. Those accounts needed to be both accessible for operational purposes and secured against misuse. However, the cases show that access control alone was not sufficient. Agents could exploit their technical knowledge and the trust placed in them to move funds without immediate detection, then alter records or provide misleading explanations later. 

The technical complexity of cryptocurrency systems also creates challenges for auditors and supervisors who may not share the same level of expertise as frontline agents. If supervisors lack detailed understanding of blockchain transactions, wallet management, and exchange interfaces, they may rely heavily on the reporting of the very agents they are tasked with overseeing. That knowledge gap can delay detection of irregular transfers or inconsistencies in reported balances. These factors suggest that robust oversight in digital‑currency investigations requires both technological competence and structural safeguards, such as multi‑signature wallets, independent reconciliation of blockchain records, and periodic external audits.

Ethics, Public Trust, and Consequences

When law‑enforcement officers commit crimes under cover of official investigations, the impact extends far beyond the immediate financial losses. Cases like those of Force and Bridges erode public confidence in the fairness and integrity of the justice system. Members of the public may question whether evidence has been handled properly, whether prosecutions are impartial, and whether other instances of misconduct remain undiscovered.

In the context of the Silk Road prosecution, defense teams and observers have pointed to the agents’ misconduct as a complicating factor in evaluating the overall fairness of the process. Even when courts determine that the core evidence against a defendant remains strong, knowledge that investigators stole funds or lied to prosecutors can alter the public narrative and fuel skepticism about high‑profile convictions. The integrity of digital evidence is especially critical in cases that depend heavily on complex technical records and financial trails.

There are also direct victims beyond the abstract concept of public trust. The government itself, as the custodian of seized assets and evidence, suffered losses when digital currency was diverted into private accounts. Individuals whose accounts were frozen under questionable pretenses, as in the CoinMKT episode, may have experienced significant financial harm. The consequences of such misconduct therefore include both institutional damage and concrete harm to specific parties. 

Lessons and Policy Recommendations

The misconduct of Force and Bridges has prompted broader reflection on how to safeguard
investigations from insider abuse. One key lesson is the need for stronger internal controls over virtual assets. Mechanisms such as multi‑signature wallets, in which multiple authorized parties must approve any transfer, can reduce the risk that a single agent can move funds undetected. Regular reconciliation of blockchain records against internal logs, conducted by personnel independent of the investigative team, can also help identify anomalies early.

Another lesson concerns conflicts of interest and outside engagements. Force’s unapproved role as a compliance officer at a digital‑currency exchange illustrates how external positions can create powerful incentives to misuse law‑enforcement authority. Clear, enforced prohibitions on unapproved outside financial roles—especially in industries related to an agent’s investigative portfolio—are essential. Agencies may need to update their ethics policies and training to address the specific risks posed by digital‑asset markets and emerging financial technologies. 

Finally, the cases underscore the value of strong oversight units within the justice system. Proactive monitoring of high‑risk operations, targeted audits of digital‑asset handling, and robust whistleblower protections can all contribute to early detection of misconduct. As technology evolves, oversight structures must evolve with it, ensuring that the power to investigate complex crimes is matched by equally sophisticated mechanisms to prevent and detect corruption.

Conclusion

The story of Carl M. Force and Shaun W. Bridges is a reminder that even those tasked with enforcing the law can succumb to the temptations created by new technologies and powerful investigative tools. In the midst of the effort to dismantle Silk Road and hold its operators accountable, two agents abandoned their sworn ethics, exploited their unique positions for personal gain. Their crimes—extortion, money laundering, obstruction of justice, and theft of government property—undermined the integrity of the investigation and public confidence in the institutions.

Yet the eventual detection, prosecution, and sentencing of these agents also demonstrate that accountability is possible. The challenge for leaders, policymakers and agencies is to learn from these cases and implement oversight and safeguards that reduce the opportunity for similar misconduct in future investigations. As online markets and virtual assets continue to evolve, the integrity of those who investigate them—and the systems that oversee their work—will be just as important as technical expertise in ensuring that justice is done.

References

Department of Homeland Security, Office of Inspector General. (2017, August 15). Former Secret Service agent pleads guilty to money laundering [Press release]. U.S. Department of Homeland Security. https://www.oig.dhs.gov/news/press-releases/2017/08152017/former-secret-service-agent-pleads-guilty-money-laundering

U.S. Department of Justice, Office of Public Affairs. (2015, October 19). Former DEA agent sentenced for extortion, money laundering and obstruction of justice related to Silk Road [Press release]. U.S. Department of Justice. https://www.justice.gov/archives/opa/pr/former-dea-agent-sentenced-extortion-money-laundering-and-obstruction-related-silk-road

U.S. Department of Justice, Office of Public Affairs. (2015, August 31). Former Secret Service agent pleads guilty to money laundering and obstruction of justice [Press release]. U.S. Department of Justice. https://www.justice.gov/archives/opa/pr/former-secret-service-agent-pleads-guilty-money-laundering

U.S. Department of Justice, Office of Public Affairs. (2015, March 30). Two former federal agents charged with bitcoin theft and related crimes [Press release]. U.S. Department of Justice. https://www.justice.gov/opa/pr/two-former-federal-agents-charged-bitcoin-theft-and-related-crimes

U.S. Department of Justice, Office of Public Affairs. (2015, February 4). Former Secret Service agent pleads guilty to money laundering [Press release]. U.S. Department of Justice. https://www.justice.gov/archives/opa/pr/former-secret-service-agent-pleads-guilty-money-laundering

National Security Archive. (2019, December 12). Silk Road: Investigation of a DEA and Secret Service agents’ involvement with an online black market site [Electronic briefing book]. The George Washington University. https://nsarchive.gwu.edu

AI Prompts to Help Identify and Correct False-Positive "Hallucinations" and Assist with APA Compliance

Some AI services are notorious for confidently providing false-positive "hallucinations". 

Your mission as a writer is to identify and correct those AI issues, avoid plagiarism and bolster your academic integrity.

Students:

Below is a long list of prompts that can be used in AI to check your work.

· Copy/paste the prompts below into your AI resource.

 

· Attach the draft file version of your work with the prompts.

· Let AI review the prompts with the draft file.

· Review, verify and correct any errors or issues that AI check reveals. 

Chatrie v. United States: Implications for Law Enforcement

Core holding and immediate implications

In Chatrie v. United States (2026), the Supreme Court held that police officers conduct a Fourth Amendment “search” when they obtain detailed cell‑phone location data, such as Google’s Location History, via geofence warrants, because individuals have a reasonable expectation of privacy in records of their physical movements even if those records are held by a third‑party company (Kagan, 2026; The Guardian, 2026). The Court concluded that this applies even when the time window is short and the data is obtained from a technology provider, and remanded for the Fourth Circuit to evaluate whether the particular geofence warrant at issue was reasonable in terms of probable cause and particularity and how the good‑faith exception to the exclusionary rule applies (Kagan, 2026; Justia, 2024).

Practically, this means that law enforcement must treat geofence‑based access to smartphone location data as a constitutionally significant search, with warrant requirements and exceptions similar to those recognized in Carpenter v. United States for cell‑site location information (Kagan, 2026; Paul, Weiss, Rifkind, Wharton & Garrison LLP, 2026).

Ramifications for police and law enforcement practices

Geofence warrants as high‑scrutiny tools

Geofence warrants compel a provider like Google to disclose location data for every device estimated to be within a defined geographic area during a specified time frame, typically through a multi‑step process that begins with anonymized device data and proceeds to disclosure of subscriber identities (Kagan, 2026; American Civil Liberties Union, 2026; Paul, Weiss, Rifkind, Wharton & Garrison LLP, 2026). The Court’s opinion emphasizes the breadth of such warrants and their potential to resemble “general warrants,” particularly when they encompass residences, churches, schools, and hospitals within the radius (Kagan, 2026; American Civil Liberties Union, 2026).

For police practice, this implies:

• Agencies will need to narrow the geographic scope, time window, and criteria for device selection at each step of a geofence warrant to withstand probable‑cause and particularity scrutiny (Kagan, 2026). 
•  Internal review by legal advisors or prosecutors before seeking geofence warrants will likely become standard to reduce the risk of suppression and civil liability (Paul, Weiss, Rifkind, Wharton & Garrison LLP, 2026).

Limits on short‑term and “targeted” location requests

The government had argued that accessing two hours of Location History data around a crime scene should be treated differently from long‑term tracking; the Court rejected this distinction, observing that even short‑term monitoring can reveal highly sensitive movements, such as visits to medical, legal, or political locations (Kagan, 2026). The opinion also states that Fourth Amendment protections do not hinge on the quantity of information obtained once the category of information is protected, and that the ability to select limited time slices from a comprehensive database does not diminish the constitutional intrusion (Kagan, 2026).

Consequently, law enforcement cannot justify bypassing warrant requirements solely by limiting the duration of location data requested, and must be prepared to show probable cause and necessity even for relatively narrow time windows (Kagan, 2026; The Guardian, 2026).

Restriction of the traditional third‑party doctrine

The Court explicitly declines to apply the traditional third‑party doctrine from United States v. Miller and Smith v. Maryland to Location History data, echoing its earlier approach in Carpenter (Kagan, 2026). It reasoned that location records are “qualitatively different,” uniquely revealing, and not truly “voluntarily shared” in the conventional sense, because modern smartphone use and repeated prompts to enable Location History make the generation of such data a pervasive feature of daily life rather than a discrete business transaction (Kagan, 2026; Paul, Weiss, Rifkind, Wharton & Garrison LLP, 2026).

For police practice, this indicates that subpoena‑like tools directed to providers for historical smartphone location data will generally be constitutionally inadequate absent a warrant, and agencies must distinguish carefully between traditional business records and digital diaries of movement (Kagan, 2026; American Civil Liberties Union, 2026).

Multi‑step digital warrants and judicial oversight

The geofence warrant in Chatrie used a three‑stage process: (1) anonymized data for all devices in the geofence during the one‑hour window; (2) extended movement data inside and outside the geofence for selected devices; and (3) disclosure of identifying information for a further subset of devices (Kagan, 2026; Justia, 2024). Justice Jackson’s concurrence stresses that steps two and three were not subject to detailed judicial standards in the warrant and allowed officers to broaden the search and de‑anonymize users without additional judicial findings of probable cause, which she characterizes as granting a “roving commission” inconsistent with warrant requirements (Jackson, 2026).

Police departments will therefore need to ensure that:

• Warrants explicitly define the criteria for narrowing devices at each stage and the basis for moving from anonymized data to identifying information (Kagan, 2026; Jackson, 2026).
•  Magistrates, not officers alone, determine the scope and sequence of data access, potentially by requiring new or amended warrants for subsequent stages in complex digital searches (Jackson, 2026).

Exigent circumstances and recognized exceptions

The Court notes that its holding does not foreclose warrantless access to location data in true emergencies, consistent with existing exigent‑circumstances doctrine (Kagan, 2026). However, the opinion suggests that such situations must involve compelling needs of law enforcement and be narrowly tailored to the emergency at hand, which implies that routine investigations will rarely qualify (Kagan, 2026; American Civil Liberties Union, 2026).

Ramifications for prosecutions and criminal cases

Suppression litigation and the good‑faith exception

In the underlying federal case, the district court and the Fourth Circuit both upheld admission of the geofence‑derived evidence based on the good‑faith exception, even while expressing serious concerns about the warrant’s breadth and constitutional validity (United States v. Chatrie, 2024; American Civil Liberties Union, 2026). Justice Alito’s dissent in the Supreme Court emphasizes that many past cases involving geofence warrants are likely to survive suppression challenges because officers relied on warrants in an unsettled legal environment (Alito, 2026).

For prosecutors, this means:

• Past convictions based on similar geofence warrants will likely be defended by arguing that officers acted in objective reliance on judicially issued warrants and pre‑Chatrie case law (United States v. Chatrie, 2024; Alito, 2026). 
•  New investigations after Chatrie will face tighter standards; the ability to invoke good‑faith will weaken over time as the constitutional limits become settled and widely known (Alito, 2026).

Strategic use of location evidence

Because the Court describes Location History as akin to a personal journal—similar to emails, documents, photos, and calendars stored in the cloud—such evidence will attract strong privacy‑based challenges and may be perceived by juries as intrusive surveillance (Kagan, 2026; American Civil Liberties Union, 2026). Prosecutors may respond by using geofence‑derived information primarily to generate leads and corroborate other evidence, rather than as the sole or central proof of identity or guilt (Paul, Weiss, Rifkind, Wharton & Garrison LLP, 2026).

Broader implications for policing and surveillance

Shift away from dragnet surveillance techniques

The Court’s reasoning, along with advocacy from organizations such as the ACLU and EFF, signals skepticism toward investigatory methods that start with an area and time and then identify potential suspects from the entire population present, rather than focusing on specific individuals for whom probable cause already exists (American Civil Liberties Union, 2026; Electronic Frontier Foundation, 2026). This has implications not only for geofence warrants but for other “reverse” techniques, such as reverse keyword searches and broad social‑media data pulls.

Law enforcement agencies are likely to:

• Emphasize suspect‑specific investigative methods and use reverse‑location or reverse‑keyword tools only when narrowly tailored and backed by strong justifications that can satisfy courts under Chatrie’s framework (Paul, Weiss, Rifkind, Wharton & Garrison LLP, 2026). 
•  Develop minimization procedures to discard information about non‑suspects quickly after initial screening whenever reverse‑search methods are used (American Civil Liberties Union, 2026).

Data architecture and provider practices

Google has indicated in its Supreme Court filings and public statements that, as of mid‑2025, it moved Location History storage from centralized servers to user devices and no longer maintains data in a form that would allow responding to geofence warrants for Location History (Kagan, 2026; Bloomberg Law, 2026). Commentary notes that other technology and telecommunications companies may consider similar approaches, such as on‑device storage and shorter retention periods, to reduce exposure to broad law‑enforcement demands and privacy criticism (Paul, Weiss, Rifkind, Wharton & Garrison LLP, 2026).

This evolution will force police and prosecutors to:

• Rely more heavily on carrier‑held cell‑site data (still governed by Carpenter) and on traditional device searches, rather than cloud‑based geofences (Kagan, 2026; Bloomberg Law, 2026). 
•  Maintain ongoing dialogue with provider legal and compliance teams to understand what data exists, how it is stored, and what legal processes can realistically reach it (Paul, Weiss, Rifkind, Wharton & Garrison LLP, 2026).

References

American Civil Liberties Union. (2026, March 4). United States v. Chatrie. ACLU. https://www.aclu.org/cases/united-states-v-chatrie

Alito, S. A. (2026). Dissenting opinion in Chatrie v. United States, 609 U.S. ___ (No. 25‑112). (Included in slip opinion PDF attached by the Court Reporter.)

Bloomberg Law. (2026, April 26). Supreme Court weighs warrants tied to phone location data. Bloomberg Law. https://news.bloomberglaw.com/us-law-week/justices-weigh-legality-of-warrants-tied-to-phone-location-data

Electronic Frontier Foundation. (2026, March 2). Brief of Amicus Curiae Electronic Frontier Foundation in support of petitioner, Chatrie v. United States (No. 25‑112). Electronic Frontier Foundation. https://www.eff.org/files/2026/03/02/chatrie-v-us-eff-scotus-brief.pdf

Jackson, K. B. (2026). Concurring opinion in Chatrie v. United States, 609 U.S. ___ (No. 25‑112). (Included in slip opinion PDF attached by the Court Reporter.)

Justia. (2024, July 8). United States v. Chatrie, No. 22‑4489 (4th Cir. 2024). Justia. https://law.justia.com/cases/federal/appellate-courts/ca4/22-4489/22-4489-2024-07-09.html

Kagan, E. (2026). Opinion of the Court in Chatrie v. United States, 609 U.S. ___ (No. 25‑112). (Slip opinion, October Term 2025, as provided in 25‑112_0am4.pdf.)

Paul, Weiss, Rifkind, Wharton & Garrison LLP. (2026, February 2). Supreme Court to address constitutionality of geofence warrants for the first time. Paul, Weiss Publications. https://www.paulweiss.com/insights/client-memos/supreme-court-to-address-constitutionality-of-geofence-warrants-for-the-first-time

The Guardian. (2026, June 29). US supreme court rules geofence warrants require constitutional privacy protections. The Guardian. https://www.theguardian.com/us-news/2026/jun/29/supreme-court-geofence-warrants-case-decision

United States v. Chatrie, 590 F. Supp. 3d 901 (E.D. Va. 2022). (District court decision discussing geofence warrant, Fourth Amendment, and good‑faith exception.)

Perplexity AI. (2026). Perplexity AI system documentation and capabilities (GPT‑5.1). Perplexity AI. https://www.perplexity.ai (general product and system information page).

 

Use of Artificial Intelligence (Perplexity AI)

Artificial Intelligence, specifically Perplexity AI (powered by GPT‑5.1), was used to assist in assembling, synthesizing, and summarizing the information above. The AI system accessed, read, and integrated content from the official Supreme Court opinion in Chatrie v. United States, lower‑court decisions, and reputable secondary analyses (news, advocacy organizations, and law‑firm commentaries). The final text was then structured to conform to APA‑style in‑text citations and references.

IoT and Stolen Cars: Thieves May Use Tech to Grab Your Ride

The 10 Most Stolen Vehicles in America in 2025

Vehicle theft declined in the United States in 2025, but several models remained frequent targets because of their popularity, availability, and persistent appeal to thieves (National Insurance Crime Bureau [NICB], 2025; Car and Driver, 2026). According to NICB data, the most stolen vehicle in America in 2025 was the Hyundai Elantra, followed by the Honda Accord and the Hyundai Sonata (NICB, 2025; Car and Driver, 2026).
Ranked Vehicles 

 

The 10 most stolen vehicles in America in 2025 were the following:

• Hyundai Elantra (21,732)
• Honda Accord (17,797)
• Hyundai Sonata (17,687)
• Chevrolet Silverado 1500 (16,764)Honda Civic (12,725)
• Kia Optima (11,521)
• Ford F-150 (10,102)
• Toyota Camry (9,833)
• Honda CR-V (9,809)
• Nissan Altima (8,445)

 

Theft Trends

NICB reported that U.S. vehicle thefts experienced a decline in 2025, yet the same report still identified specific models that were stolen far more often than others. NICB specifically stated that the Hyundai Elantra remained the most stolen vehicle model in 2025 with 21,732 thefts, followed by the Honda Accord with 17,797 thefts and the Hyundai Sonata with 17,687 thefts (NICB, 2025).

Car and Driver’s report on the NICB figures confirms the same ranking and shows that the list included a mix of sedans, pickups, and one SUV, suggesting that theft risk in 2025 was not limited to one body style or market segment (Car and Driver, 2026). The presence of the Chevrolet Silverado 1500 and Ford F-150 on the same list as the Honda Civic, Toyota Camry, and Nissan Altima shows that both high-volume passenger cars and high-demand trucks remained attractive targets (Car and Driver, 2026). 

Internet of Things

Modern connected vehicles increasingly function like Internet of Things systems because they rely on wireless connectivity, cloud services, software-driven features, and communication between in-vehicle components and outside networks (Trend Micro, 2021). Trend Micro explains that connected cars use technologies such as 5G, cloud-connected applications, over-the-air updates, and vehicle-to-network communication, all of which expand what vehicles can do while also increasing cybersecurity exposure (Trend Micro, 2021).

Trend Micro also notes that the modern connected car is becoming similar to a “smartphone-on-wheels,” with applications communicating through middleware, gateway electronic control units, and cloud services. These systems can introduce risks such as denial-of-service attacks, man-in-the-middle attacks, hijacking of services, data privacy issues, authentication and management issues, incorrect data, and misconfiguration problems (Trend Micro, 2021). As the costs and resale values for car computers, collision avoidance systems, and other tech devices increase, thieves now also disassemble vehicles to steal those items.

Radio frequency interception and transmission devices are sometimes used to capture the codes transmitted by key fobs on some vehicles. The codes are then used to reprogram devices that the thieves emply to unlock, start, and steal a vehicle. 

This means connected technology can create additional pathways that thieves or cybercriminals may try to exploit. If remote services, app connections, or cloud-linked vehicle functions are not properly secured, the same connectivity designed for convenience may also increase opportunities for unauthorized access or interference (Trend Micro, 2021). 

Prevention Methods

NICB advises vehicle owners to use layered theft-prevention practices rather than relying on a single measure. Its prevention guidance recommends removing keys or fobs from the vehicle, locking doors and windows, parking in well-lit areas, and using anti-theft technology such as steering wheel locks, audible alarms, and aftermarket tracking devices (NICB, n.d.).

These recommendations support the use of steering wheel locking devices, alarm systems, and location-tracking tools as practical deterrents. They also fit well with additional protective measures such as ignition kill switches or fuel-system shutoff devices, which are commonly used to make a stolen vehicle harder to start or move, although the verified NICB source specifically highlights locks, alarms, and tracking devices rather than detailing those other devices individually (NICB, n.d.).

For connected vehicles, owners must  recognize that digital security matters alongside physical security. Because connected cars increasingly depend on cloud services, APIs, and networked vehicle systems, keeping manufacturer software current and treating app-based vehicle access cautiously are sensible precautions consistent with the risks described by Trend Micro (Trend Micro, 2021). 

References

Car and Driver. (2026, March 23). What cars were stolen most last year? The top 10 may surprise you. https://www.caranddriver.com/news/a70833130/top-10-most-stolen-cars-2025/

National Insurance Crime Bureau. (2025). U.S. vehicle thefts experience historic decline. https://www.nicb.org/news/news-releases/us-vehicle-thefts-experience-historic-decline

National Insurance Crime Bureau. (n.d.). Prevent vehicle theft. https://www.nicb.org/prevent-vehicle-theft

Trend Micro. (2021, February 15). Connected cars, 5G, the cloud: Opportunities and risks. https://www.trendmicro.com/en_us/research/21/b/connected-cars-5g-the-cloud-opportunities-and-risks.html