Boolean-network-based approach for construction of filter generators

Abstract

In this paper, we view filter generators as Boolean networks (BNs), and discuss their poweranalysis-based side-channel analysis. An incompletely specified binary sequence always contains some bits called unnecessary bits comprising 1 or 0. Our motivation for considering this type of sequence is to reduce direct dependencies between side-channel information and key sequences. An algorithm is proposed to determine the unnecessary bits to increase the key search time required for adversaries rather than simply turning all unnecessary bits to 0 (or 1). Then, to reduce area dissipation, under the framework of semi-tensor product (STP) of matrices, the problem of constructing filter generators with minimum number of stages is converted into the one of determining the corresponding transition matrices. Compared with the existing results, the lower bound of the minimum number of stages is provided, which can reduce the exhaustive search time required to find it. Finally, one example is used to illustrate the efficacy of the proposed algorithm.

Finite-Time Controllability and Set Controllability of Impulsive Probabilistic Boolean Control Networks

“…Q τ = 1 4×4 . Hence, the finite-time controllability of system (19) is affected by impulsive effects, which shows that impulsive effects play an important role in the finite-time controllability analysis of PBCNs.…”

“…As a natural generalization of controllability, Cheng and Hu [6] developed the concept of set controllability for switched linear systems. Set controllability has many applications, such as set stabilization, synchronization, output tracking and so on [4], [19], [23], [29], [34], [51], [55].…”

Research Status of Nonlinear Feedback Shift Register Based on Semi-Tensor Product

“…These results are more novel than previous conclusions and are very helpful for the design of practical stream cipher algorithms and decoding algorithms. According to the specific research object, the main achievements can be roughly divided into the modeling of NFSRs [65][66][67], the analysis of the structure of NFSRs [68][69][70][71][72][73][74][75][76][77][78][79][80][81], and the study of the properties of NFSRs [82][83][84][85][86][87][88][89][90][91][92][93][94][95][96][97]. This paper will give an overview of the latest achievements in NFSR research based on STP from these three aspects.…”

Induced-Equations-Based Stability Analysis and Stabilization of Markovian Jump Boolean Networks

“…In 1969, Kauffman firstly proposed the concept of Boolean networks (BNs) as the dynamical models of genetic regulatory networks (GRNs) [1]. Since then, BNs have attracted considerable attention of numerous scientific researchers, thanks to comprehensive applications of BNs including biology engineering [2]- [5], game theory [6], multi-agent systems [7], as well as shift registers [8]. Under the framework of BNs, the gene activity is approximately quantized into two levels, that is, active and inactive.…”