Breaking On-Chip Communication Anonymity using Flow Correlation Attacks

• URL: http://arxiv.org/abs/2309.15687v2
• Date: Thu, 1 Feb 2024 19:05:15 GMT
• Title: Breaking On-Chip Communication Anonymity using Flow Correlation Attacks
• Authors: Hansika Weerasena, and Prabhat Mishra
• Abstract summary: We investigate the security strength of existing anonymous routing protocols in Network-on-Chip (NoC) architectures. We show that the existing anonymous routing is vulnerable to machine learning (ML) based flow correlation attacks on NoCs. We propose lightweight anonymous routing with traffic obfuscation techniques to defend against ML-based flow correlation attacks.
• Score: 2.977255700811213
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Network-on-Chip (NoC) is widely used to facilitate communication between components in sophisticated System-on-Chip (SoC) designs. Security of the on-chip communication is crucial because exploiting any vulnerability in shared NoC would be a goldmine for an attacker that puts the entire computing infrastructure at risk. NoC security relies on effective countermeasures against diverse attacks, including attacks on anonymity. We investigate the security strength of existing anonymous routing protocols in NoC architectures. Specifically, this paper makes two important contributions. We show that the existing anonymous routing is vulnerable to machine learning (ML) based flow correlation attacks on NoCs. We propose lightweight anonymous routing with traffic obfuscation techniques to defend against ML-based flow correlation attacks. Experimental studies using both real and synthetic traffic reveal that our proposed attack is successful against state-of-the-art anonymous routing in NoC architectures with high accuracy (up to 99%) for diverse traffic patterns, while our lightweight countermeasure can defend against ML-based attacks with minor hardware and performance overhead.

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