Poster
When adversary becomes the guardian - Towards side-channel security with adversarial attacks
Stjepan Picek (Cyber Security)
Dirmanto Jap (Nanyang Technological University)
Shivam Bhasin (Nanyang Technological University)
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Abstract
Machine learning algorithms fall prey to adversarial examples. As profiling side-channel attacks are seeing rapid adoption of machine learning-based approaches that can even defeat commonly used side-channel countermeasures, we investigate the potential of adversarial example as a defense mechanism. We show that adversarial examples have the potential to serve as a countermeasure against machine learning-based side-channel attacks. Further, we exploit the transferability property to show that a common adversarial example can act as a countermeasure against a range of machine learning-based side-channel classifiers.