HEMA: A Hands-on Exploration Platform for MEMS Sensor Attacks

2025-07-08

AI Summary

Traditional pedagogical approaches hinder beginners from gaining hands-on experience with MEMS sensor security vulnerabilities, impeding automotive cybersecurity education. To address this, we propose the first low-cost, scalable, teaching- and research-oriented MEMS sensor attack experimentation platform. It integrates embedded development, sensor signal emulation, and physical-layer attack injection capabilities, enabling real-time interference and response analysis for accelerometers and gyroscopes. Designed with security, usability, and reproducibility as core principles, the platform significantly lowers the barrier to learning vehicular sensor security. Evaluated across multiple university courses and research projects, it demonstrably enhances students’ practical understanding of sensor vulnerabilities in Advanced Driver Assistance Systems (ADAS) and associated mitigation mechanisms.

Technology Category

• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

Automotive safety and security are paramount in the rapidly advancing landscape of vehicular technology. Building safe and secure vehicles demands a profound understanding of automotive systems, particularly in safety and security. Traditional learning approaches, such as reading materials or observing demonstrations, often fail to provide the practical, hands-on experience essential for developing this expertise. For novice users, gaining access to automotive-grade systems and mastering their associated hardware and software can be challenging and overwhelming. In this paper, we present a novel, affordable, and flexible exploration platform, hema, that enables users to gain practical, hands-on insights into the security compromises of micro-electromechanical systems (MEMS) sensors, a critical component in modern ADAS systems. Furthermore, we discuss the unique challenges and design considerations involved in creating such a platform, emphasizing its role in enhancing the understanding of automotive safety and security. This framework serves as an invaluable resource for educators, researchers, and practitioners striving to build expertise in the field.

Problem

• Enables hands-on learning of MEMS sensor security compromises
• Addresses challenges in accessing automotive-grade systems for novices
• Enhances understanding of automotive safety and security practically

Innovation

• Affordable flexible platform for MEMS sensor attacks
• Hands-on learning for automotive security compromises
• Enhances understanding of ADAS safety challenges