Biblio

Cyber 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.

Insider threat makes great damage to the security of information system, traditional security methods are extremely difficult to work. Insider attack identification plays an important role in insider threat detection. Monitoring user's abnormal behavior is an effective method to detect impersonation, this method is applied to insider threat identification, to built user's behavior attribute information database based on weights changeable feedback tree augmented Bayes network, but data is massive, using the dimensionality reduction based on rough set, to establish the process information model of user's behavior attribute. Using the minimum risk Bayes decision can effectively identify the real identity of the user when user's behavior departs from the characteristic model.