A METHOD FOR PROTECTING MODULAR EXPONENTIAL ALGORITHMS AGAINST DEEP-LEARNING SIDE-CHANNEL ATTACK (DL-SCA)

摘要

A method (220) for countering a profiling of deep-learning (100) side channel (SCA) algorithm to disrupt a training phase of a deep-learning model is provided. It alters and interleaves an execution sequence (163) of modular exponentiations or point additions in a counter SCA algorithm. The mixing, loops (206-210) through bits of a private key, D, along a sliding window, wherein for each loop, an N-bit tuple from the private key (102) is compared (207) to the random number plus a linear increment, and, if the value is a match, it indexes (208) into said precomputed vector according to said random number, r, thereby extracting and interleaving values into an execution path of said counter SCA algorithm from said precomputed vector according to an index represented by said random number; otherwise. Other embodiments are provided.