Optimal Security Hardening over a Probabilistic Attack Graph

被引:0
|
作者
Buczkowski, Przemyslaw [1 ]
Malacaria, Pasquale [1 ]
Hankin, Chris [2 ]
Fielder, Andrew [2 ]
机构
[1] Queen Mary Univ London, Sch Elect Engn & Comp Sci, London, England
[2] Imperial Coll London, Inst Secur Sci & Technol, London, England
基金
英国工程与自然科学研究理事会;
关键词
threat modelling; multi-objective optimisation; probabilistic attack graph; industrial control system; cybersecurity risk assessment tool; MANAGEMENT;
D O I
10.1145/3510547.3517919
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
CySecTool is a tool that finds a cost-optimal security controls portfolio in a given budget for a probabilistic attack graph. A portfolio is a set of counter-measures, or controls, against vulnerabilities adopted for a computer system, while an attack graph is a type of a threat scenario model. In an attack graph, nodes are privilege states of the attacker, edges are vulnerabilities escalating privileges, and controls reduce the probabilities of some vulnerabilities being exploited. The tool builds on an optimisation algorithm published by [1], enabling a user to quickly create, edit, and incrementally improve models, analyse results for given portfolios and display the best solutions for all possible budgets in the form of a Pareto frontier. A case study was performed utilising a system graph and suspected attack paths prepared by industrial security engineers based on an industrial source with which they work. The goal of the case study is to model a supervisory control and data acquisition (SCADA) industrial system which, due to having a potential to harm people, necessitates strong protection while not allowing to use typical penetration tools like vulnerability scanners. Results are analysed to show how a cyber-security analyst would use CySecTool to store cyber-security intelligence and draw further conclusions.
引用
收藏
页码:21 / 30
页数:10
相关论文
共 50 条
  • [41] Study of network security evaluation based on attack graph model
    Electronic Engineering Institute, Hefei 230037, China
    不详
    [J]. Tongxin Xuebao, 2007, 3 (29-34):
  • [42] A Quantitative Method for Evaluating Network Security Based on Attack Graph
    Zheng, Yukun
    Lv, Kun
    Hu, Changzhen
    [J]. NETWORK AND SYSTEM SECURITY, 2017, 10394 : 349 - 358
  • [43] Exploring risk flow attack graph for security risk assessment
    Dai, Fangfang
    Hu, Ying
    Zheng, Kangfeng
    Wu, Bin
    [J]. IET INFORMATION SECURITY, 2015, 9 (06) : 344 - 353
  • [44] Complex Network Security Analysis based on Attack Graph Model
    Liu, Zhiming
    Li, Sheng
    He, Jin
    Xie, Di
    Deng, Zhantao
    [J]. PROCEEDINGS OF THE 2012 SECOND INTERNATIONAL CONFERENCE ON INSTRUMENTATION & MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC 2012), 2012, : 183 - 186
  • [45] MAGD: Minimal Attack Graph Generation Dynamically in Cyber Security
    Mohammadzad, Maryam
    Karimpour, Jaber
    Mahan, Farnaz
    [J]. COMPUTER NETWORKS, 2023, 236
  • [46] An Attack Graph Based Metric for Security Evaluation of Computer Networks
    Keramati, Marjan
    Akbari, Ahmad
    [J]. 2012 SIXTH INTERNATIONAL SYMPOSIUM ON TELECOMMUNICATIONS (IST), 2012, : 1094 - 1098
  • [47] Probabilistic Event Graph to Model Safety and Security for Diagnosis Purposes
    Bourget, Edwin
    Cuppens, Frederic
    Cuppens-Boulahia, Nora
    Dubus, Samuel
    Foley, Simon
    Laarouchi, Youssef
    [J]. DATA AND APPLICATIONS SECURITY AND PRIVACY XXXII, DBSEC 2018, 2018, 10980 : 38 - 47
  • [48] Probabilistic Graph Security for Networked Multi-Robot Systems
    Wehbe, Remy
    Williams, Ryan K.
    [J]. 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2018, : 7646 - 7653
  • [49] Scalable min-max multi-objective cyber-security optimisation over probabilistic attack graphs
    Khouzani, M. H. R.
    Liu, Zhengliang
    Malacaria, Pasquale
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2019, 278 (03) : 894 - 903
  • [50] Algorithm of optimal security hardening measures against insider threat
    Chen, Xiaojun
    Shi, Jinqiao
    Xu, Fei
    Pu, Yiguo
    Guo, Li
    [J]. Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 2014, 51 (07): : 1565 - 1577