loading
Papers Papers/2020

Research.Publish.Connect.

Paper

Authors: Leigh Chase ; Alaa Mohasseb and Benjamin Aziz

Affiliation: School of Computing, University of Portsmouth, Portsmouth, U.K.

Keyword(s): Cyber Security, Machine Learning, Threat Intelligence, Estimation Methods, STIX, TTPs.

Abstract: Information Technology plays an increasingly important role in the provision of essential services. For these systems and networks to be reliable and trustworthy, we must defend them from those who would seek to compromise their Confidentiality, Integrity and Availability. Security intelligence tells us about the Tactics, Techniques and Procedures used by threat actors for these very purposes. In this paper, we introduce a novel method for learning malicious behaviours and then estimating how likely it is that a system has been compromised. One of the difficulties encountered when applying machine learning to cyber security, is the lack of ground truth on which to train supervised techniques. This is often compounded by the volume, variety and velocity of data which is far greater than can be processed using only human analyses. The technique, known as LeWiS, includes data preparation and processing phases that learn and later predict the presence of threat actors using a model of th eir behaviours. The method addresses the problems of scale and veracity, by learning Indicators of Attack via feature extraction from security intelligence that has been obtained through empirical methods. This approach shows promising classification performance for detecting learned malicious behaviours, within synthesised systems’ event data. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.162.69.45

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Chase, L.; Mohasseb, A. and Aziz, B. (2021). The LeWiS Method: Target Variable Estimation using Cyber Security Intelligence. In Proceedings of the 17th International Conference on Web Information Systems and Technologies - WEBIST, ISBN 978-989-758-536-4; ISSN 2184-3252, pages 15-26. DOI: 10.5220/0010645000003058

@conference{webist21,
author={Leigh Chase. and Alaa Mohasseb. and Benjamin Aziz.},
title={The LeWiS Method: Target Variable Estimation using Cyber Security Intelligence},
booktitle={Proceedings of the 17th International Conference on Web Information Systems and Technologies - WEBIST,},
year={2021},
pages={15-26},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010645000003058},
isbn={978-989-758-536-4},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Web Information Systems and Technologies - WEBIST,
TI - The LeWiS Method: Target Variable Estimation using Cyber Security Intelligence
SN - 978-989-758-536-4
IS - 2184-3252
AU - Chase, L.
AU - Mohasseb, A.
AU - Aziz, B.
PY - 2021
SP - 15
EP - 26
DO - 10.5220/0010645000003058

0123movie