Article: Statistical analysis and comparison of linear regression attacks on the advanced encryption standard Journal: International Journal of Information and Communication Technology (IJICT) 2015 Vol.7 No.2/3 pp.159 - 184 Abstract: This research investigates profiled linear regression-based attacks for extracting the advanced encryption standard (AES) secret key. Several methods from recent advancements are compared for their capability to correctly build the multivariate distribution for profiling. Attack performance shows greater than 98% success rate with as few as 100 training and test traces. In 8 out of 9 test cases examined, linear regression attacks using the coefficient of determination R2, adjusted coefficient of determination R2a and correlation power analysis (CPA) performed better than or equal to the original stochastic attack and attack using the symmetry metric. Our new method using R2a is proven to suppress unimportant variables and enhance important ones better than other methods. It is successful when the microcontrollers and data collection hardware differ between training and test phases and is found to be more effective in noisy environments than CPA. Inderscience Publishers - linking academia, business and industry through research

Title: Statistical analysis and comparison of linear regression attacks on the advanced encryption standard

Authors: Hiren Patel; Christine Schubert-Kabban; Rusty O. Baldwin; David P. Montminy

Addresses: Department of Electrical and Computer Engineering, Air Force Institute of Technology, 2950 Hobson Way, WPAFB, OH, 45433, USA ' Department of Electrical and Computer Engineering, Air Force Institute of Technology, 2950 Hobson Way, WPAFB, OH, 45433, USA ' Department of Electrical and Computer Engineering, Air Force Institute of Technology, 2950 Hobson Way, WPAFB, OH, 45433, USA ' Department of Electrical and Computer Engineering, Air Force Institute of Technology, 2950 Hobson Way, WPAFB, OH, 45433, USA

Abstract: This research investigates profiled linear regression-based attacks for extracting the advanced encryption standard (AES) secret key. Several methods from recent advancements are compared for their capability to correctly build the multivariate distribution for profiling. Attack performance shows greater than 98% success rate with as few as 100 training and test traces. In 8 out of 9 test cases examined, linear regression attacks using the coefficient of determination R², adjusted coefficient of determination R²_a and correlation power analysis (CPA) performed better than or equal to the original stochastic attack and attack using the symmetry metric. Our new method using R²_a is proven to suppress unimportant variables and enhance important ones better than other methods. It is successful when the microcontrollers and data collection hardware differ between training and test phases and is found to be more effective in noisy environments than CPA.

Keywords: side channel attacks; SCA; linear regression attacks; advanced encryption standard; AES secret key; stochastic attacks; microcontrollers; data collection; cryptography; information security.

DOI: 10.1504/IJICT.2015.068387

International Journal of Information and Communication Technology, 2015 Vol.7 No.2/3, pp.159 - 184

Received: 26 Apr 2013
Accepted: 19 Oct 2013
Published online: 01 Apr 2015 *

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Title: Statistical analysis and comparison of linear regression attacks on the advanced encryption standard

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