Formulation Of Association Rule Mining (ARM) For An Effective Cyber Attack Attribution In Cyber Threat Intelligence (CTI)

In recent year, an adversary has improved their Tactic, Technique and Procedure (TTPs) in launching cyberattack that make it less predictable, more persistent, resourceful and better funded. So many organisation has opted to use Cyber Threat Intelligence (CTI) in their security posture in attributin...

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Main Authors: Abu, Md Sahrom, Ariffin, Aswami, Yusof, Robiah, Selamat, Siti Rahayu
Format: Article
Language:en
Published: The Science And Information (SAI) Organization Limited 2021
Online Access:http://eprints.utem.edu.my/id/eprint/25367/2/PAPER_18-FORMULATION_OF_ASSOCIATION_RULE_MINING.PDF
http://eprints.utem.edu.my/id/eprint/25367/
https://thesai.org/Downloads/Volume12No4/Paper_18-Formulation_of_Association_Rule_Mining.pdf
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_version_ 1832718149516001280
author Abu, Md Sahrom
Ariffin, Aswami
Yusof, Robiah
Selamat, Siti Rahayu
author_facet Abu, Md Sahrom
Ariffin, Aswami
Yusof, Robiah
Selamat, Siti Rahayu
author_sort Abu, Md Sahrom
building UTEM Library
collection Institutional Repository
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
continent Asia
country Malaysia
description In recent year, an adversary has improved their Tactic, Technique and Procedure (TTPs) in launching cyberattack that make it less predictable, more persistent, resourceful and better funded. So many organisation has opted to use Cyber Threat Intelligence (CTI) in their security posture in attributing cyberattack effectively. However, to fully leverage the massive amount of data in CTI for threat attribution, an organisation needs to spend their focus more on discovering the hidden knowledge behind the voluminous data to produce an effective cyberattack attribution. Hence this paper emphasized on the research of association analysis in CTI process for cyber attack attribution. The aim of this paper is to formulate association ruleset to perform the attribution process in the CTI. The Apriori algorithm is used to formulate association ruleset in association analysis process and is known as the CTI Association Ruleset (CTI-AR). Interestingness measure indicator specially support (s), confidence (c) and lift (l) are used to measure the practicality, validity and filtering the CTI-AR. The results showed that CTI-AR effectively identify the attributes, relationship between attributes and attribution level group of cyberattack in CTI. This research has a high potential of being expanded into cyber threat hunting process in providing a more proactive cybersecurity environment.
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spelling my.utem.eprints-253672021-12-20T13:00:05Z http://eprints.utem.edu.my/id/eprint/25367/ Formulation Of Association Rule Mining (ARM) For An Effective Cyber Attack Attribution In Cyber Threat Intelligence (CTI) Abu, Md Sahrom Ariffin, Aswami Yusof, Robiah Selamat, Siti Rahayu In recent year, an adversary has improved their Tactic, Technique and Procedure (TTPs) in launching cyberattack that make it less predictable, more persistent, resourceful and better funded. So many organisation has opted to use Cyber Threat Intelligence (CTI) in their security posture in attributing cyberattack effectively. However, to fully leverage the massive amount of data in CTI for threat attribution, an organisation needs to spend their focus more on discovering the hidden knowledge behind the voluminous data to produce an effective cyberattack attribution. Hence this paper emphasized on the research of association analysis in CTI process for cyber attack attribution. The aim of this paper is to formulate association ruleset to perform the attribution process in the CTI. The Apriori algorithm is used to formulate association ruleset in association analysis process and is known as the CTI Association Ruleset (CTI-AR). Interestingness measure indicator specially support (s), confidence (c) and lift (l) are used to measure the practicality, validity and filtering the CTI-AR. The results showed that CTI-AR effectively identify the attributes, relationship between attributes and attribution level group of cyberattack in CTI. This research has a high potential of being expanded into cyber threat hunting process in providing a more proactive cybersecurity environment. The Science And Information (SAI) Organization Limited 2021-04 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/25367/2/PAPER_18-FORMULATION_OF_ASSOCIATION_RULE_MINING.PDF Abu, Md Sahrom and Ariffin, Aswami and Yusof, Robiah and Selamat, Siti Rahayu (2021) Formulation Of Association Rule Mining (ARM) For An Effective Cyber Attack Attribution In Cyber Threat Intelligence (CTI). International Journal Of Advanced Computer Science And Applications (IJASCA), 12 (4). pp. 134-143. ISSN 2158-107X https://thesai.org/Downloads/Volume12No4/Paper_18-Formulation_of_Association_Rule_Mining.pdf 10.14569/IJACSA.2021.0120418
spellingShingle Abu, Md Sahrom
Ariffin, Aswami
Yusof, Robiah
Selamat, Siti Rahayu
Formulation Of Association Rule Mining (ARM) For An Effective Cyber Attack Attribution In Cyber Threat Intelligence (CTI)
title Formulation Of Association Rule Mining (ARM) For An Effective Cyber Attack Attribution In Cyber Threat Intelligence (CTI)
title_full Formulation Of Association Rule Mining (ARM) For An Effective Cyber Attack Attribution In Cyber Threat Intelligence (CTI)
title_fullStr Formulation Of Association Rule Mining (ARM) For An Effective Cyber Attack Attribution In Cyber Threat Intelligence (CTI)
title_full_unstemmed Formulation Of Association Rule Mining (ARM) For An Effective Cyber Attack Attribution In Cyber Threat Intelligence (CTI)
title_short Formulation Of Association Rule Mining (ARM) For An Effective Cyber Attack Attribution In Cyber Threat Intelligence (CTI)
title_sort formulation of association rule mining (arm) for an effective cyber attack attribution in cyber threat intelligence (cti)
url http://eprints.utem.edu.my/id/eprint/25367/2/PAPER_18-FORMULATION_OF_ASSOCIATION_RULE_MINING.PDF
http://eprints.utem.edu.my/id/eprint/25367/
https://thesai.org/Downloads/Volume12No4/Paper_18-Formulation_of_Association_Rule_Mining.pdf
url_provider http://eprints.utem.edu.my/