Biblio

The motion process of multi-dimensional chaotic system is complex and variable, the randomness of motion state is stronger, and the motion state is more unpredictable within a certain range. This feature of multi-dimensional chaotic system can effectively improve the security performance of digital image encryption algorithm. In this paper, the hyper-chaotic Lorenz map is used to design the encryption sequence to improve the random performance of the encryption sequence, thus optimizing the performance of the digital image encryption algorithm. In this paper, the chaotic sequence is used to randomly select the row vector of the Hadamard matrix to form the Hadamard matrix to determine the measurement matrix, which simplifies the computational difficulty of the algorithm and solves the problem of the discontinuity of the key space in the random matrix design.

As wireless mesh networks (WMNs) develop rapidly, security issue becomes increasingly important. Intrusion Detection System (IDS) is one of the crucial ways to detect attacks. However, IDS in wireless networks including WMNs brings high detection overhead, which degrades network performance. In this paper, we apply compressed sensing (CS) theory to IDS and propose a CS based IDS for hybrid WMNs. Since CS can reconstruct a sparse signal with compressive sampling, we process the detected data and construct sparse original signals. Through reconstruction algorithm, the compressive sampled data can be reconstructed and used for detecting intrusions, which reduces the detection overhead. We also propose Active State Metric (ASM) as an attack metric for recognizing attacks, which measures the activity in PHY layer and energy consumption of each node. Through intensive simulations, the results show that under 50% attack density, our proposed IDS can ensure 95% detection rate while reducing about 40% detection overhead on average.