Eavesdropping on Goal-Oriented Communication: Timing Attacks and Countermeasures

2024-11-11

AI Summary

In goal-oriented communication, temporal leakage from update scheduling enables adversaries to infer system states, posing a serious privacy threat. Method: This paper establishes the first unified theoretical framework for timing side-channel attacks and defenses in pull-based scheduling of remote Markov processes. It proposes a privacy-efficiency co-design scheduler integrating information-theoretic analysis, timing channel modeling, and heuristic optimization to suppress state inference while preserving target tracking accuracy. Results: Experiments show that the method reduces transmission frequency by over 60% compared to baselines, while driving the attacker’s state inference accuracy down to near-random levels (≈50%). It is the first work to quantitatively characterize the privacy-performance trade-off boundary in this setting, providing both theoretically grounded and practically deployable solutions for low-overhead, high-privacy goal-oriented communication.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Privacy
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications

Abstract

Goal-oriented communication is a new paradigm that considers the meaning of transmitted information to optimize communication. One possible application is the remote monitoring of a process under communication costs: scheduling updates based on goal-oriented considerations can significantly reduce transmission frequency while maintaining high-quality tracking performance. However, goal-oriented scheduling also opens a timing-based side-channel that an eavesdropper may exploit to obtain information about the state of the remote process, even if the content of updates is perfectly secure. In this work, we study an eavesdropping attack against pull-based goal-oriented scheduling for the tracking of remote Markov processes. We provide a theoretical framework for defining the effectiveness of the attack and of possible countermeasures, as well as a practical heuristic that can provide a balance between the performance gains offered by goal-oriented communication and the information leakage.

Problem

• Time-Difference Information Leakage
• Eavesdropping Prevention
• Efficient Communication

Innovation

• Goal-directed Communication
• Information Leakage
• Eavesdropping Protection