Leaking your engine speed by spectrum analysis of real-time scheduling sequences

• Main Authors: Liu, Songran, Guan, Nan, Ji, Dong, Liu, Weichen, Liu, Xue, Yi, Wang
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2020
• Subjects: Engineering::Computer science and engineering; Real-time System; Scheduling Sequences
• Online Access: https://hdl.handle.net/10356/144755
• Institution: Nanyang Technological University

This paper identifies and studies a new security/privacy issue for automobile vehicles. Specifically, attackers can infer the engine speed of a vehicle by observing and analyzing the real-time scheduling sequences on the Engine Control Unit (ECU). First, we present the problem model of engine-triggered task executed on ECU. And then, we introduce two Engine-triggered Task Period Tracing methods (DFT-based ETPT and FRSP-based ETPT) to infer the period variation of engine-triggered task. Finally, simulation experiments are conducted to demonstrate the effect of this new timing side-channel information leakage with our proposed methods.