Open AccessDetection and Prevention of Cyber Crime Based on Diamond Factor Neural Network
Author(s) -
Li Jin,
Ping He
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1437/1/012011
Subject(s) - cybercrime , artificial neural network , computer science , artificial intelligence , factor (programming language) , machine learning , data mining , computer security , the internet , world wide web , programming language
The purpose of this paper is to provide a quantitative analysis method for cybercrime research, and also provide a new mathematical research method for network behavior analysis. Firstly, a novel factor space research method is established by using the “medium scale”. On this basis, the concept of factor discovery of cybercrime behavior is proposed, and the corresponding cybercrime behavior analysis model is established, namely the criminal factor neural network. Secondly, the learning mechanism of network behavior neural network is discussed by using the factor discovery principle. At the same time, a network behavior learning algorithm based on diamond thinking is obtained. Finally, factor discovery thought, factor neural network learning system are applied to the research of cybercrime model analysis and prevention strategy to provide guiding decision support and problem solution for public security departments.