Open Access

ARTICLE

Security-Critical Components Recognition Algorithm for Complex Heterogeneous Information Systems

Jinxin Zuo^1,2, Yueming Lu^1,2,*, Hui Gao^2,3, Tong Peng^1,2, Ziyv Guo^2,3, Tong An^1,2, Enjie Liu⁴

1 School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, 100876, China
2 Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing, 100876, China
3 School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China
4 University of Bedfordshire, Institute for Research in Applicable Computing (IRAC), Luton, UK

* Corresponding Author: Yueming Lu. Email:

Computers, Materials & Continua 2021, 68(2), 2579-2595. https://doi.org/10.32604/cmc.2021.016623

Received 06 January 2021; Accepted 12 February 2021; Issue published 13 April 2021

Abstract

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.

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Citations