Using improved neural network for the risk assessment of information security

Abstract

Because of the information age, protecting information is very important to satisfy the three main aspects of information security, namely confidentiality, integrity and availability. In this case, information security has become one of the most important problems in information technology. Information security is a very important activity and risk assessment is the kernel of information security. However, most of the current risk assessment activities are comparatively subjective and the performances are not good enough. To understand this problem, we propose the improved neural network for the risk assessment of information security. Basically, it is processed under back-propagation neural network (BPN). Moreover, particle swarm optimization (PSO) is used for fine parameter optimization of BPN. The experimental results show that the proposed algorithm has the best performance among these compared approaches.

Data Analysis on the Influencing Factors of the Real Estate Price

“…In addition, the real estate industry can also adjust prices appropriately through these influencing factors. In the future work, authors will use other approaches such as weighted concept lattice and Hamming distance, Shannon entropy, and deep learning to do more research for finding out the influencing factors of real estate price [17][18][19].…”