Description:
Explore the security challenges of Edge AI against hardware attacks in this tinyML Talks Germany meetup webinar. Delve into the vulnerabilities of neural networks, particularly in edge AI applications where physical access to devices poses additional risks. Learn about potential attack vectors like side-channel analysis and fault attacks, and understand how attackers might attempt to reverse engineer and copy neural networks. Gain insights into countermeasures, including masking techniques, to protect valuable intellectual property. Discover the intricacies of network structure, neuron parameters, power traces, and activation functions in the context of security. Examine the effectiveness of differential power analysis and the implications of increasing traces on retrieving weights. Consider the scalability of attacks with network size and the impact of prior knowledge on attack success. Engage with discussions on hardware counter measures, parallel implementation strategies, and the generation of adversarial examples. Conclude with a comprehensive overview of network security in Edge AI and participate in an interactive Q&A session addressing audience queries.
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Security of Edge AI Against Hardware Attacks
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