Ahmed, Abdulghani Ali and Noorul Ahlami, Kamarul Zaman (2017) AIRSE : an approach for attack intention recognition based on similarity of evidences. In: 1st EAI International Conference on Computer Science and Engineering, COMPSE 2016 , 11-12 November 2016 , Penang, Malaysia. . ISBN 9781631901362
|
Pdf
AIRSE - an approach for attack intention recognition based.pdf Download (340kB) | Preview |
|
Pdf
AIRSE an approach for attack intention recognition based on similarity of evidences.pdf - Published Version Restricted to Repository staff only Download (742kB) | Request a copy |
Abstract
Sensitive information can be exposed to critical risks when communicated through computer networks. The ability of attackers in hiding their attacks' intention obstructs existing protection systems to early prevent their attacks and avoid any possible sabotage in network systems. In this paper, we propose a similarity approach called Attack Intention Recognition based on Similarity of Evidences (AIRSE). In particular, the proposed approach AIRSE aims to recognize attack intention in real time. It classifies attacks according to their characteristics and uses the similar metric method to identify attacks motives and predict their intentions. In this study, attack intentions are categorized into specific and general intentions. General intentions are recognized by investigating violations against the security metrics of confidentiality, integrity, availability, and authenticity. Specific intentions are recognized by investigating the network attacks used to achieve a violation. The obtained results demonstrate that the proposed approach is capable of investigating similarity of attack signatures and recognizing the intentions of network attack.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Additional Information: | Indexed by Scopus |
Uncontrolled Keywords: | Cyberattacks; Network forensics; Attack intention recognition; Similarity of evidences |
Subjects: | Q Science > QA Mathematics > QA76 Computer software |
Faculty/Division: | Faculty of Computer System And Software Engineering |
Depositing User: | Mrs Norsaini Abdul Samat |
Date Deposited: | 18 Dec 2019 02:14 |
Last Modified: | 18 Dec 2019 02:14 |
URI: | http://umpir.ump.edu.my/id/eprint/27010 |
Download Statistic: | View Download Statistics |
Actions (login required)
View Item |