INFORMATION SECURITY ASSESSMENT BASED ON MACHINE LEARNING TECHNOLOGY-FUZZY-GRA-AHP

Autor: Mei-Er Zhuang, Wen-Tsao Pan, Zhou, Jia-Yan, Yang, Qian, Wan-Ting Hong
Rok vydání: 2019
Předmět:
DOI: 10.5281/zenodo.3271619
Popis: With the advent of the information age, information security has become an urgent problem to be solved. Various application and platforms have not only brought convenience to people, but also brought hidden dangers - information security risks. This paper uses some of the machine learning technology - fuzzy computing and gray relation analysis (GRA), to analyze data of the three major video platforms of China, and takes the information security level as a new criterion to conduct the evaluation of their performance. An assessment model is constructed based on machine learning technology, namely the combination of fuzzy computing and GRA and analytic hierarchy process (AHP). Conclusions can be drawn as follows. First, consumers’ perception of video platform information security level is constantly being strengthened. Second, information security risks are affecting consumers' choice decisions about video platforms, and the weights will continue to increase. Third, video platforms are paying more attention to information security construction.
Databáze: OpenAIRE