Biblio

A randomly-selective encryption (RSE) algorithm is proposed for HEVC video bitstream in this paper. It is a pioneer algorithm with high efficiency and security. The encryption process is completely independent of video compression process. A randomly-selective sequence (RSS) based on the RC4 algorithm is designed to determine the extraction position in the video bitstream. The extracted bytes are encrypted by AES-CTR to obtain the encrypted video. Based on the high efficiency video coding (HEV C) bitstream, the simulation and analysis results show that the proposed RSE algorithm has low time complexity and high security, which is a promising tool for video cryptographic applications.

The network robustness is defined by how well its vertices are connected to each other to keep the network strong and sustainable. The change of network robustness may reveal events as well as periodic trend patterns that affect the interactions among vertices in the network. The evaluation of network robustness may be helpful to many applications, such as event detection, disease transmission, and network security, etc. There are many existing metrics to evaluate the robustness of networks, for example, node connectivity, edge connectivity, algebraic connectivity, graph expansion, R-energy, and so on. It is a natural and urgent problem how to choose a reasonable metric to effectively measure and evaluate the network robustness in the real applications. In this paper, based on some general principles, we design and implement a benchmark, namely BMNR, for the metrics of network robustness. The benchmark consists of graph generator, graph attack and robustness metric evaluation. We find that R-energy can evaluate both connected and disconnected graphs, and can be computed more efficiently.