Privacy Vulnerability: Car Tracking via Tire Pressure Monitoring System Transmissions
By
wisdomseaker
Yesterday's bagel. Skim it, don't savour it.
Summary
Researchers demonstrate how Tire Pressure Monitoring System (TPMS) transmissions can be used to track vehicles, revealing privacy vulnerabilities in modern car systems. The study shows that TPMS signals contain unique, persistent identifiers transmitted in clear text, allowing malicious actors to deploy low-cost receivers along roads to monitor car movement patterns over extended periods. The research collected data over 10 weeks from 12 verified cars, but the method could scale to track thousands of vehicles.
Key quotes
· 3 pulledTire Pressure Monitoring System (TPMS) transmissions of modern cars are sent over the air in clear text and entail a unique identifier that does not change over very long periods of time.
In this work, we investigate the privacy implications for car owners of this design choice by collecting and analyzing TPMS transmissions from a network of low-cost spectrum receivers that we deploy along the road over a period of 10 weeks.
Our measurement study comprises data from 12 verified cars, but malicious actors could easily scale their efforts to track several thousands of cars.
You might also wanna read
Wi-Fi Router Beamforming Feature Can Be Exploited to Identify Individuals With 99.5% Accuracy, Study Finds
Researchers at Germany's Karlsruhe Institute of Technology discovered that standard Wi-Fi routers using beamforming feedback information (BF
New phishing campaign targets Signal users to steal chat backup recovery keys
Hackers are targeting Signal users in a new phishing campaign that attempts to steal their chat backups. The attackers pose as Signal's supp
New browser-based side-channel attack uses SSD activity analysis to spy on users
Researchers have discovered a new browser-based side-channel attack that can spy on users by analyzing SSD (Solid State Drive) activity thro
arstechnica.com·1d agoBehavioral feature engineering, not deep learning models, key to Trojan malware detection study finds
A study on Trojan malware detection focuses on behavioral feature engineering for Windows-based IoT and industrial systems. Rather than emph
MemoAttack: A Memory-Driven Framework for Automated LLM Jailbreak Attacks
This paper introduces MemoAttack, a novel memory-driven black-box jailbreak framework for large language models (LLMs). Unlike existing meth
CAPTCHAs remain viable for detecting AI agents by exploiting process differences
The article discusses how while AI vision language models (VLMs) can now solve traditional CAPTCHA image recognition tasks (like identifying
