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Cliff C. Zou

Publications and source records attributed to Cliff C. Zou.

4 recordsLinked to original sources

A Critical Roadmap to Driver Authentication via CAN Bus: Dataset Review, Introduction of the Kidmose CANid Dataset (KCID), and Proof of Concept

Modern vehicles remain vulnerable to unauthorized use and theft despite traditional security measures including immobilizers and keyless entry systems. Criminals exploit vulnerabilities in Controller Area Network (CAN) bus systems to bypass authentication mechanisms, while social media trends have expanded auto theft to include recreational joyriding by underage drivers. Driver authentication via CAN bus data offers a promising additional layer of defense-in-depth protection, but existing open-access driver fingerprinting datasets suffer from critical limitations including reliance on decoded diagnostic data rather than raw CAN traffic, artificial fixed-route experimental designs, insufficient sampling rates, and lack of demographic information. This paper provides a comprehensive review of existing open-access driver fingerprinting datasets, analyzing their strengths and limitations to guide practitioners in dataset selection. We introduce the Kidmose CANid Dataset (KCID), which addresses these fundamental shortcomings by providing raw CAN bus data from 16 drivers across four vehicles, including essential demographic information and both daily driving and controlled fixed-route data. Beyond dataset contributions, we present a driver authentication anti-theft framework and implement a proof-of-concept prototype on a single-board computer. Through live road trials with an unaltered passenger vehicle, we demonstrate the practical feasibility of CAN bus-based driver authentication anti-theft systems. Finally, we explore diverse applications of KCID beyond driver authentication, including driver profiling for insurance and safety assessments, mechanical anomaly detection, young driver monitoring, and impaired driving detection. This work provides researchers with both the data and methodological foundation necessary to develop robust, deployable driver authentication systems...

cs.CR

Side-Channel VoIP Profiling Attack against Customer Service Automated Phone System

In many VoIP systems, Voice Activity Detection (VAD) is often used on VoIP traffic to suppress packets of silence in order to reduce the bandwidth consumption of phone calls. Unfortunately, although VoIP traffic is fully encrypted and secured, traffic analysis of this suppression can reveal identifying information about calls made to customer service automated phone systems. Because different customer service phone systems have distinct, but fixed (pre-recorded) automated voice messages sent to customers, VAD silence suppression used in VoIP will enable an eavesdropper to profile and identify these automated voice messages. In this paper, we will use a popular enterprise VoIP system (Cisco CallManager), running the default Session Initiation Protocol (SIP) protocol, to demonstrate that an attacker can reliably use the silence suppression to profile calls to such VoIP systems. Our real-world experiments demonstrate that this side-channel profiling attack can be used to accurately identify not only what customer service phone number a customer calls, but also what following options are subsequently chosen by the caller in the phone conversation.

cs.CR

A Web Infrastructure for Certifying Multimedia News Content for Fake News Defense

In dealing with altered multimedia news content, also referred to as fake news, we present a ready-to-deploy scheme based on existing public key infrastructure as a new fake news defense paradigm. This scheme enables news organizations to certify/endorse a newsworthy multimedia news content and securely and conveniently pass this trust information to end users. A news organization can use our program to digitally sign the multimedia news content with its private key. By installing a browser extension, an end user can easily verify whether a news content has been endorsed and by which organization. It is totally up to the end user whether to trust the news or the endorsing news organization. The underlining principles of our scheme are that fake news will sooner or later be identified as fake by general population, and a news organization puts its long-term reputation on the line when endorsing a news content.

cs.CR

On Runtime Software Security of TrustZone-M based IoT Devices

Internet of Things (IoT) devices have been increasingly integrated into our daily life. However, such smart devices suffer a broad attack surface. Particularly, attacks targeting the device software at runtime are challenging to defend against if IoT devices use resource-constrained microcontrollers (MCUs). TrustZone-M, a TrustZone extension for MCUs, is an emerging security technique fortifying MCU based IoT devices. This paper presents the first security analysis of potential software security issues in TrustZone-M enabled MCUs. We explore the stack-based buffer overflow (BOF) attack for code injection, return-oriented programming (ROP) attack, heap-based BOF attack, format string attack, and attacks against Non-secure Callable (NSC) functions in the context of TrustZone-M. We validate these attacks using the TrustZone-M enabled SAM L11 MCU. Strategies to mitigate these software attacks are also discussed.

cs.CR