DetectX—Adversarial Input Detection Using Current Signatures in Memristive XBar Arrays

Author:

Moitra AbhishekORCID,Panda PriyadarshiniORCID

Funder

Center for Brain-Inspired Computing

Joint University Microelectronics Program (JUMP) Center sponsored by DARPA and Semiconductor Research Corporation

National Science Foundation

Technology Innovation Institute, Abu Dhabi

Amazon Research Award

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems;IEEE Transactions on Emerging Topics in Computational Intelligence;2024-04

2. AD 2 VNCS: A dversarial D efense and D evice V ariation-tolerance in Memristive Crossbar-based N euromorphic C omputing S ystems;ACM Transactions on Design Automation of Electronic Systems;2023-11-15

3. Robustness for Embedded Machine Learning Using In-Memory Computing;Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing;2023-10-07

4. XploreNAS : Explore Adversarially Robust and Hardware-efficient Neural Architectures for Non-ideal Xbars;ACM Transactions on Embedded Computing Systems;2023-07-24

5. Enhancing Adversarial Attacks on Single-Layer NVM Crossbar-Based Neural Networks with Power Consumption Information;2022 IEEE 35th International System-on-Chip Conference (SOCC);2022-09-05

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