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TaskShuffler++: Real-Time Schedule Randomization for Reducing Worst-Case Vulnerability to Timing Inference Attacks

2019/11/18 by Man-Ki Yoon, Yoon, Man-Ki, Jung-Eun Kim +5
Computer Science · #Cryptography and Security (cs.CR) #Distributed systems and fault tolerance #FOS: Computer and information sciences #Real-Time Systems Scheduling #Security and Verification in Computing

paper · pdf · doi:10.48550/arxiv.1911.07726

openalex publication_date 2019/11/18 · openalex created_date 2019/11/22 · openalex updated_date 2026/07/28

Abstract

This paper presents a schedule randomization algorithm that reduces the vulnerability of real-time systems to timing inference attacks which attempt to learn the timing of task execution. It utilizes run-time information readily available at each scheduling decision point to increase the level of uncertainty in task schedules, while preserving the original schedulability. The randomization algorithm significantly reduces an adversary's best chance to correctly predict what tasks would run at arbitrary times. This paper also proposes an information-theoretic measure that can quantify the worst-case vulnerability, from the defender's perspective, of an arbitrary real-time schedule.

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