A novel risk assessment model for privacy security in Internet of Things
Aiming at issues of privacy security in Internet of Things(IOT) applications,this paper proposes an effective model to handle probabilistic causality of evaluation factors and derive weights of influence-relation of propagation paths.Utilizing Bayesian causal relation-network and prior probability.the model can undertake probabilistic inference and generate values of risk probability for assets and propagation paths According to Bayesian Network (BN) structure.the risk analyst can easily find relevant risk propagation paths and calculate weight values of each path by utilizing decision making trial and evaluation laboratory ( DEMATEL) Ultimately the model can be determined risk level of asset and each risk propagation path,and implement countermeasure of recommendation in accordance with evaluation results Instancing analysis of demonstration.this model can efficiently revise recommendation of countermeasures for decision-makers and thus mitigate risk to an acceptable range Moreover,it can provide the theoretical basis for decision-making of privacy security risk assessment (PSRA) for further development in IoT area.
Internet of Things Bayesian Network decision making trial and evaluation laboratory privacy security assessment
国内会议
湖北恩施
英文
1-8
2014-09-13（万方平台首次上网日期，不代表论文的发表时间）