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The Dark Side: Security and Reliability Concerns in Machine Learning for EDA

Publication ,  Journal Article
Xie, Z; Pan, J; Chang, CC; Hu, J; Chen, Y
Published in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
April 1, 2023

The growing integrated circuit complexity has led to a compelling need for design efficiency improvement through new electronic design automation (EDA) methodologies. In recent years, many unprecedented efficient EDA methods have been enabled by machine learning (ML) techniques. While ML demonstrates its great potential in circuit design, however, the dark side about potential security and model reliability problems, is seldomly discussed. This article gives a comprehensive and impartial summary of all security and reliability concerns we have observed in ML for EDA. Many of them are hidden or neglected by practitioners in this field. In this article, we first provide our taxonomy to define four major types of concerns, then we analyze different application scenarios and special properties in ML for EDA. After that, we present our detailed and impartial analysis of each type of concern with experiments.

Duke Scholars

Published In

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

DOI

EISSN

1937-4151

ISSN

0278-0070

Publication Date

April 1, 2023

Volume

42

Issue

4

Start / End Page

1171 / 1184

Related Subject Headings

  • Computer Hardware & Architecture
  • 4607 Graphics, augmented reality and games
  • 4009 Electronics, sensors and digital hardware
  • 1006 Computer Hardware
  • 0906 Electrical and Electronic Engineering
 

Citation

APA
Chicago
ICMJE
MLA
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Xie, Z., Pan, J., Chang, C. C., Hu, J., & Chen, Y. (2023). The Dark Side: Security and Reliability Concerns in Machine Learning for EDA. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 42(4), 1171–1184. https://doi.org/10.1109/TCAD.2022.3199172
Xie, Z., J. Pan, C. C. Chang, J. Hu, and Y. Chen. “The Dark Side: Security and Reliability Concerns in Machine Learning for EDA.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 42, no. 4 (April 1, 2023): 1171–84. https://doi.org/10.1109/TCAD.2022.3199172.
Xie Z, Pan J, Chang CC, Hu J, Chen Y. The Dark Side: Security and Reliability Concerns in Machine Learning for EDA. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 2023 Apr 1;42(4):1171–84.
Xie, Z., et al. “The Dark Side: Security and Reliability Concerns in Machine Learning for EDA.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 42, no. 4, Apr. 2023, pp. 1171–84. Scopus, doi:10.1109/TCAD.2022.3199172.
Xie Z, Pan J, Chang CC, Hu J, Chen Y. The Dark Side: Security and Reliability Concerns in Machine Learning for EDA. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 2023 Apr 1;42(4):1171–1184.

Published In

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

DOI

EISSN

1937-4151

ISSN

0278-0070

Publication Date

April 1, 2023

Volume

42

Issue

4

Start / End Page

1171 / 1184

Related Subject Headings

  • Computer Hardware & Architecture
  • 4607 Graphics, augmented reality and games
  • 4009 Electronics, sensors and digital hardware
  • 1006 Computer Hardware
  • 0906 Electrical and Electronic Engineering