Energy-Latency Attacks to On-Device Neural Networks via Sponge Poisoning-Reference-Cited by-同舟云学术

Energy-Latency Attacks to On-Device Neural Networks via Sponge Poisoning

Published:2023-07-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 Secure and Trustworthy Deep Learning Systems Workshop
language:
Short-container-title:

Author:

Wang Zijian¹^ORCID,Huang Shuo²^ORCID,Huang Yujin¹^ORCID,Cui Helei³^ORCID

Affiliation:

1. Monash University, Australia

2. Northwestern Polytechnical University, China and Monash University, Australia

3. Northwestern Polytechnical University, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3591197.3591307

Reference62 articles.

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3. John Bellardo and Stefan Savage . 2003 . 802.11 { Denial-of-Service} Attacks: Real Vulnerabilities and Practical Solutions . In 12th USENIX Security Symposium (USENIX Security 03) . John Bellardo and Stefan Savage. 2003. 802.11 { Denial-of-Service} Attacks: Real Vulnerabilities and Practical Solutions. In 12th USENIX Security Symposium (USENIX Security 03).

4. David Brazdil. 2018. Improving Stability by Reducing Usage of non-SDK Interfaces. https://android-developers.googleblog.com/2018/02/improving-stability-by-reducing-usage.html David Brazdil. 2018. Improving Stability by Reducing Usage of non-SDK Interfaces. https://android-developers.googleblog.com/2018/02/improving-stability-by-reducing-usage.html

5. Deep learning in computer vision: A critical review of emerging techniques and application scenarios

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