Statistical analysis and comparison of linear regression attacks on the advanced encryption standard. (10th April 2015)

• Record Type: Journal Article
• Authors: Patel, Hiren; Schubert–Kabban, Christine; Baldwin, Rusty O.; Montminy, David P.
• Is Part Of: International journal of information and communication technology. Volume 7:Number 2/3(2015)
• Page Start: 159
• Page End: 184
• Publication Date: 2015-04-10
• Subjects: side channel attacks -- SCA -- linear regression attacks -- advanced encryption standard -- AES secret key -- stochastic attacks -- microcontrollers -- data collection -- cryptography -- information security; Information technology -- Periodicals; Computer science -- Periodicals; Telecommunication -- Periodicals; 004.05
• Languages: English
• ISSNs: 1466-6642

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 R 2, adjusted coefficient of determination R 2 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 R 2 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.