Abstract
While the recent advances in data science and machine learning attract lots of attention in cyber security because of their promise for effective security analytics, vulnerability analysis, risk assessment, and security policy validation remain slightly aside. This is mainly due to the relatively slow progress in the theoretical formulation and the technological foundation of the cyber security concepts such as logical vulnerability, threats, and risks. In this article, we are proposing a framework for logical analysis, threat intelligence, and validation of security policies in cyber systems. It is based on multi-level model, consisting of ontology of situations and actions under security threats, security policies governing the security-related activities, and graph of the transactions. The framework is validated using a set of scenarios describing the most common security threats in digital banking, and a prototype of an event-driven engine for navigation through the intelligence graphs has been implemented. Although the framework was developed specifically for application in digital banking, the authors believe that it has much wider applicability to security policy analysis, threat intelligence, and security by design of cyber systems for financial, commercial, and business operations.
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Acknowledgements
The work reported here has been carried out at the Cyber Security Research Centre of London Metropolitan University. It was initiated in collaboration with Lloyds Banking Group to investigate the logical vulnerabilities in cross-channel banking. It was granted support from UK DCMS under Cyber ASAP program. It continues under a project dedicated to threat intelligence funded by Lloyds, but all examples in the paper are solely for the purpose of illustration and do not use any internal data from the bank. Any concepts, ideas, and opinions formulated by the authors in this article are not associated with the current security practices of Lloyds Banking Group.
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Vassilev, V., Sowinski-Mydlarz, V., Gasiorowski, P., Ouazzane, K., Phipps, A. (2021). Intelligence Graphs for Threat Intelligence and Security Policy Validation of Cyber Systems. In: Bansal, P., Tushir, M., Balas, V., Srivastava, R. (eds) Proceedings of International Conference on Artificial Intelligence and Applications. Advances in Intelligent Systems and Computing, vol 1164. Springer, Singapore. https://doi.org/10.1007/978-981-15-4992-2_13
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DOI: https://doi.org/10.1007/978-981-15-4992-2_13
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