The development of the Internet of Things(IoT)calls for a comprehensive in-formation security evaluation framework to quantitatively measure the safety score and risk(S&R)value of the network urgently.In this pape...The development of the Internet of Things(IoT)calls for a comprehensive in-formation security evaluation framework to quantitatively measure the safety score and risk(S&R)value of the network urgently.In this paper,we summarize the architecture and vulnerability in IoT and propose a comprehensive information security evaluation model based on multi-level decomposition feedback.The evaluation model provides an idea for information security evaluation of IoT and guides the security decision maker for dynamic protection.Firstly,we establish an overall evaluation indicator system that includes four primary indicators of threat information,asset,vulnerability,and management,respectively.It also includes eleven secondary indicators of system protection rate,attack detection rate,confidentiality,availability,controllability,identifiability,number of vulnerabilities,vulnerability hazard level,staff organization,enterprise grading and service continuity,respectively.Then,we build the core algorithm to enable the evaluation model,wherein a novel weighting technique is developed and a quantitative method is proposed to measure the S&R value.Moreover,in order to better supervise the performance of the proposed evaluation model,we present four novel indicators includes residual risk,continuous conformity of residual risk,head-to-tail consistency and decrease ratio,respectively.Simulation results show the advantages of the proposed model in the evaluation of information security for IoT.展开更多
With the skyrocketing development of technologies,there are many issues in information security quantitative evaluation(ISQE)of complex heterogeneous information systems(CHISs).The development of CHIS calls for an ISQ...With the skyrocketing development of technologies,there are many issues in information security quantitative evaluation(ISQE)of complex heterogeneous information systems(CHISs).The development of CHIS calls for an ISQE model based on security-critical components to improve the efficiency of system security evaluation urgently.In this paper,we summarize the implication of critical components in different filed and propose a recognition algorithm of security-critical components based on threat attack tree to support the ISQE process.The evaluation model establishes a framework for ISQE of CHISs that are updated iteratively.Firstly,with the support of asset identification and topology data,we sort the security importance of each asset based on the threat attack tree and obtain the security-critical components(set)of the CHIS.Then,we build the evaluation indicator tree of the evaluation target and propose an ISQE algorithm based on the coefficient of variation to calculate the security quality value of the CHIS.Moreover,we present a novel indicator measurement uncertainty aiming to better supervise the performance of the proposed model.Simulation results show the advantages of the proposed algorithm in the evaluation of CHISs.展开更多
基金This work was supported in part by National Key R&D Program of China under Grant 2019YFB2102400in part by the BUPT Excellent Ph.D.Students Foundation under Grant CX2019117.
文摘The development of the Internet of Things(IoT)calls for a comprehensive in-formation security evaluation framework to quantitatively measure the safety score and risk(S&R)value of the network urgently.In this paper,we summarize the architecture and vulnerability in IoT and propose a comprehensive information security evaluation model based on multi-level decomposition feedback.The evaluation model provides an idea for information security evaluation of IoT and guides the security decision maker for dynamic protection.Firstly,we establish an overall evaluation indicator system that includes four primary indicators of threat information,asset,vulnerability,and management,respectively.It also includes eleven secondary indicators of system protection rate,attack detection rate,confidentiality,availability,controllability,identifiability,number of vulnerabilities,vulnerability hazard level,staff organization,enterprise grading and service continuity,respectively.Then,we build the core algorithm to enable the evaluation model,wherein a novel weighting technique is developed and a quantitative method is proposed to measure the S&R value.Moreover,in order to better supervise the performance of the proposed evaluation model,we present four novel indicators includes residual risk,continuous conformity of residual risk,head-to-tail consistency and decrease ratio,respectively.Simulation results show the advantages of the proposed model in the evaluation of information security for IoT.
基金supported in part by the National Key R&D Program of China under Grant 2019YFB2102400,2016YFF0204001in part by the BUPT Excellent Ph.D.Students Foundation under Grant CX2019117.
文摘With the skyrocketing development of technologies,there are many issues in information security quantitative evaluation(ISQE)of complex heterogeneous information systems(CHISs).The development of CHIS calls for an ISQE model based on security-critical components to improve the efficiency of system security evaluation urgently.In this paper,we summarize the implication of critical components in different filed and propose a recognition algorithm of security-critical components based on threat attack tree to support the ISQE process.The evaluation model establishes a framework for ISQE of CHISs that are updated iteratively.Firstly,with the support of asset identification and topology data,we sort the security importance of each asset based on the threat attack tree and obtain the security-critical components(set)of the CHIS.Then,we build the evaluation indicator tree of the evaluation target and propose an ISQE algorithm based on the coefficient of variation to calculate the security quality value of the CHIS.Moreover,we present a novel indicator measurement uncertainty aiming to better supervise the performance of the proposed model.Simulation results show the advantages of the proposed algorithm in the evaluation of CHISs.