Affiliations: [a] School of Economics and Management, Xidian University, Xi’an, China
| [b] Shaanxi Soft Science Institute of Informatization and Digital Economy, Xidian University, Xi’an, China
Correspondence:
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Corresponding author. Hua Li, School of Economics and Management, Xidian University, Xi’an 710071, China.
E-mail: lihua@xidian.edu.cn.
Abstract: Through advancing in information and communications technology, Smart Cities provide many potential advantages like improved energy efficiency, new economic opportunities and management methods, however the information security in the top-level design of building a quite efficient smart city is easy to be ignored and caused a huge economic losses for citizens. We focus on mining information risks of smart city from the perspective of system, identifying the key risks and determining the importance of each factor, in order to measure the risk accurately. This paper presents a failure mode and effects analysis (FMEA) method to analyze five dimensions of the information security of smart city, and assess the risks on the basis of the fuzzy set theory and the grey relational theory. Due to the problem is the risk assessment of multi-dimension for an organization information security, we present a decision model that provides an efficient framework for calculating the value of risk assessment. The results indicate that aspects of the highest importance of the information security risk of smart city are the threats in natural, contrived and physical aspects, followed by the lack of public security education and training. Through the analysis we can find out the relationship between the failure modes and the overall situation of the system, then it can distinguish the main factors which play a driving role, and the secondary factors which have less impact on the system. According to the assessment results, some suggestions are put forward to guarantee the information security of smart city. The practical application of fuzzy and grey FMEA proposed in this paper helps enhance the reliability of the prediction, and the ranking of risk factors can be used for better decision-making concerning taking measures, which in turn will make smart city safer.
Keywords: Fuzzy set theory, decision making, uncertainty information evaluation, FMEA, information security risk, smart city, grey relational theory
