Quantity-Simulation-Analysis Method based Novel RSA Timing Attack Algorithm for Single-Chip Microcomputer Platform

There are limitations in storage and computational capacity on the single-chip microcomputer platform under the secure edge computing paradigm. A higher success rate is possible via collecting sensitive information on the time side channel by multivariate statistical analysis to crack the RSA private key when attackers decrypt ciphertexts. We proposed a quantity-simulation-analysis (QSA) method to construct Markov model for RSA timing attack tasks, which firstly quantizes the decrypt process to obtain the time-consuming characteristics, then simulates the machine instruction cycles through parallel computing to analyze Markov model with more precise state transition matrix. On this basis, a novel timing attack algorithm with fuzzy clustering state transition probability matrix of the higher order Markov model on different step sizes is proposed, compared with some algorithms from other literatures taking an exhaustive search attack algorithm as a benchmark. Experimental results show that the algorithm achieves better results in terms of success rate.