Adversarial Learning Inspired Emerging Side-Channel Attacks and Defenses

TL;DR

This paper explores adversarial learning to develop emerging side-channel attacks and defenses, introducing Entropy-Shield as a novel countermeasure for timing attacks and extending it to FPGA hardware implementations.

Contribution

It proposes Entropy-Shield as a new defense mechanism against timing side-channel attacks and extends its application to FPGA-based cryptographic hardware.

Findings

Entropy-Shield effectively mitigates timing SCAs.

Extension of Entropy-Shield to FPGA hardware enhances security.

Discussion of new attack development to improve defenses.

Abstract

Evolving attacks on the vulnerabilities of the computing systems demand novel defense strategies to keep pace with newer attacks. This report discusses previous works on side-channel attacks (SCAs) and defenses for cache-targeted and physical proximity attacks. We then discuss the proposed Entropy-Shield as a defense against timing SCAs, and explain how we can extend the same to hardware-based implementations of crypto applications as "Entropy-Shield for FPGA". We then discuss why we want to build newer attacks with the hope of coming up with better defense strategies.