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Generic Attribute Scoring for Information Decay in Threat Information Sharing Platform

Mohammed Alshehri*

Department of Information Technology, Majmaah University, Majmaah, 11952, Saudi Arabia

* Corresponding Author: Mohammed Alshehri. Email:

(This article belongs to this Special Issue: Emerging Trends in Cyber Security for Communication Networks)

Computers, Materials & Continua 2021, 67(1), 917-931.


Cyber Threat Intelligence (CTI) has gained massive attention to collect hidden knowledge for a better understanding of the various cyber-attacks and eventually paving the way for predicting the future of such attacks. The information exchange and collaborative sharing through different platforms have a significant contribution towards a global solution. While CTI and the information exchange can help a lot in focusing and prioritizing on the use of the large volume of complex information among different organizations, there exists a great challenge ineffective processing of large count of different Indicators of Threat (IoT) which appear regularly, and that can be solved only through a collaborative approach. Collaborative approach and intelligence sharing have become the mandatory element in the entire world of processing the threats. In order to covet the complete needs of having a definite standard of information exchange, various initiatives have been taken in means of threat information sharing platforms like MISP and formats such as SITX. This paper proposes a scoring model to address information decay, which is shared within TISP. The scoring model is implemented, taking the use case of detecting the Threat Indicators in a phishing data network. The proposed method calculates the rate of decay of an attribute through which the early entries are removed.


Cite This Article

M. Alshehri and . , "Generic attribute scoring for information decay in threat information sharing platform," Computers, Materials & Continua, vol. 67, no.1, pp. 917–931, 2021.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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