Visible to the public A Representation of Business Oriented Cyber Threat Intelligence and the Objects Assembly

TitleA Representation of Business Oriented Cyber Threat Intelligence and the Objects Assembly
Publication TypeConference Paper
Year of Publication2020
AuthorsXu, Yuanchen, Yang, Yingjie, He, Ying
Conference Name2020 10th International Conference on Information Science and Technology (ICIST)
Date PublishedSept. 2020
PublisherIEEE
ISBN Number978-1-7281-5558-6
Keywordscomposability, cyber threat intelligence, Feeds, Fuzzy logic, fuzzy set, Fuzzy sets, generalised grey number, Metrics, object oriented security, pubcrawl, representation, Resiliency, rough set, Rough sets, set approximation, Taxonomy, Tools, Uncertainty, usiness
AbstractCyber threat intelligence (CTI) is an effective approach to improving cyber security of businesses. CTI provides information of business contexts affected by cyber threats and the corresponding countermeasures. If businesses can identify relevant CTI, they can take defensive actions before the threats, described in the relevant CTI, take place. However, businesses still lack knowledge to help identify relevant CTI. Furthermore, information in real-world systems is usually vague, imprecise, inconsistent and incomplete. This paper defines a business object that is a business context surrounded by CTI. A business object models the connection knowledge for CTI onto the business. To assemble the business objects, this paper proposes a novel representation of business oriented CTI and a system used for constructing and extracting the business objects. Generalised grey numbers, fuzzy sets and rough sets are used for the representation, and set approximations are used for the extraction of the business objects. We develop a prototype of the system and use a case study to demonstrate how the system works. We then conclude the paper together with the future research directions.
URLhttps://ieeexplore.ieee.org/document/9202271
DOI10.1109/ICIST49303.2020.9202271
Citation Keyxu_representation_2020