Defense Against On-Chip Trojans Enabling Traffic Analysis Attacks Based on Machine Learning and Data Augmentation-Reference-Cited by-同舟云学术

Defense Against On-Chip Trojans Enabling Traffic Analysis Attacks Based on Machine Learning and Data Augmentation

Published:2023-12 Issue:12 Volume:42 Page:4681-4694
ISSN:0278-0070
Container-title:IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
language:
Short-container-title:IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

Author:

Dhavlle Abhijitt¹^ORCID,Ahmed M. Meraj²^ORCID,Mansoor Naseef³^ORCID,Basu Kanad⁴^ORCID,Ganguly Amlan²^ORCID,Pudukotai Dinakarrao Sai Manoj¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA

2. Computer Engineering Department, Rochester Institute of Technology, Rochester, NY, USA

3. Computer Information Science Department, Minnesota State University Mankato, Mankato, MN, USA

4. Electrical and Computer Engineering Department, The University of Texas at Dallas, Richardson, TX, USA

Funder

U.S. National Science Foundation (NSF) CAREER

U.S. Defense Advanced Research Projects Agency

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Software

Link

Reference35 articles.

2. Differential power analysis;kocher;Advances in Cryptology (CRYPTO),1999

5. Packet Security with Path Sensitization for NoCs;travis boraten;Design Automation Test in Europe Conference Exhibition (DATE),2016

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