Visible to the public Identifying interdependencies using attack graph generation methods

TitleIdentifying interdependencies using attack graph generation methods
Publication TypeConference Paper
Year of Publication2015
AuthorsLever, K. E., Kifayat, K., Merabti, M.
Conference Name2015 11th International Conference on Innovations in Information Technology (IIT)
Date Publishednov
Keywordsattack graph generation methods, Attack Graphs, Cascading Failures, Collaboration, Collaborative Infrastructures, communication assets, complex interconnected networks, Complexity theory, critical infrastructures, distributed schema, e-health, generation complexity, graph theory, heterogeneous collaborative infrastructures, industrial manufacturing automation, information and communication technologies, interdependencies identification, interdependencies modelling, Interdependency, Internet of Things, interoperability, power system faults, Power system protection, pubcrawl170107, pubcrawl170108, risk assessment methods, risk management, safety-critical systems, security, security metrics, security of data, system complexity, vulnerabilities identification, wireless communications

Information and communication technologies have augmented interoperability and rapidly advanced varying industries, with vast complex interconnected networks being formed in areas such as safety-critical systems, which can be further categorised as critical infrastructures. What also must be considered is the paradigm of the Internet of Things which is rapidly gaining prevalence within the field of wireless communications, being incorporated into areas such as e-health and automation for industrial manufacturing. As critical infrastructures and the Internet of Things begin to integrate into much wider networks, their reliance upon communication assets by third parties to ensure collaboration and control of their systems will significantly increase, along with system complexity and the requirement for improved security metrics. We present a critical analysis of the risk assessment methods developed for generating attack graphs. The failings of these existing schemas include the inability to accurately identify the relationships and interdependencies between the risks and the reduction of attack graph size and generation complexity. Many existing methods also fail due to the heavy reliance upon the input, identification of vulnerabilities, and analysis of results by human intervention. Conveying our work, we outline our approach to modelling interdependencies within large heterogeneous collaborative infrastructures, proposing a distributed schema which utilises network modelling and attack graph generation methods, to provide a means for vulnerabilities, exploits and conditions to be represented within a unified model.

Citation Keylever_identifying_2015