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Security of neuromorphic computing: Thwarting learning attacks using memristor's obsolescence effect

Publication ,  Conference
Yang, C; Liu, B; Li, H; Chen, Y; Wen, W; Barnell, M; Wu, Q; Rajendran, J
Published in: IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
November 7, 2016

Neuromorphic architectures are widely used in many applications for advanced data processing, and often implements proprietary algorithms. In this work, we prevent an attacker with physical access from learning the proprietary algorithm implemented by the neuromorphic hardware. For this purpose, we leverage the obsolescence effect in memristors to judiciously reduce the accuracy of outputs for any unauthorized user. For a legitimate user, we regulate the obsolescence effect, thereby controlling the accuracy of outputs. We also analyze the security vs. cost trade-offs for different applications. Our methodology is compatible with mainstream classification applications, memristor devices, and security and performance constraints.

Duke Scholars

Published In

IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD

DOI

ISSN

1092-3152

ISBN

9781450344661

Publication Date

November 7, 2016

Volume

07-10-November-2016
 

Citation

APA
Chicago
ICMJE
MLA
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Yang, C., Liu, B., Li, H., Chen, Y., Wen, W., Barnell, M., … Rajendran, J. (2016). Security of neuromorphic computing: Thwarting learning attacks using memristor's obsolescence effect. In IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD (Vol. 07-10-November-2016). https://doi.org/10.1145/2966986.2967074
Yang, C., B. Liu, H. Li, Y. Chen, W. Wen, M. Barnell, Q. Wu, and J. Rajendran. “Security of neuromorphic computing: Thwarting learning attacks using memristor's obsolescence effect.” In IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD, Vol. 07-10-November-2016, 2016. https://doi.org/10.1145/2966986.2967074.
Yang C, Liu B, Li H, Chen Y, Wen W, Barnell M, et al. Security of neuromorphic computing: Thwarting learning attacks using memristor's obsolescence effect. In: IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD. 2016.
Yang, C., et al. “Security of neuromorphic computing: Thwarting learning attacks using memristor's obsolescence effect.” IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD, vol. 07-10-November-2016, 2016. Scopus, doi:10.1145/2966986.2967074.
Yang C, Liu B, Li H, Chen Y, Wen W, Barnell M, Wu Q, Rajendran J. Security of neuromorphic computing: Thwarting learning attacks using memristor's obsolescence effect. IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD. 2016.

Published In

IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD

DOI

ISSN

1092-3152

ISBN

9781450344661

Publication Date

November 7, 2016

Volume

07-10-November-2016