Cookies

We use cookies to ensure that we give you the best experience on our website. By continuing to browse this repository, you give consent for essential cookies to be used. You can read more about our Privacy and Cookie Policy.


Durham Research Online
You are in:

Insider threats : identifying anomalous human behaviour in heterogeneous systems using Beneficial Intelligent Software (Ben-ware).

McGough, A. Stephen and Wall, David and Brennan, John and Theodoropoulos, Georgios and Ruck-Keene, Ed and Arief, Budi and Gamble, Carl and Fitzgerald, John and van Moorsel, Aad (2015) 'Insider threats : identifying anomalous human behaviour in heterogeneous systems using Beneficial Intelligent Software (Ben-ware).', in 7th ACM CCS International Workshop on Managing Insider Security Threats, MIST '15, 12-16 October 2015, Denver, Colorado ; proceedings. New York: Association for Computing Machinery (ACM), pp. 1-12.

Abstract

In this paper, we present the concept of "Ben-ware" as a beneficial software system capable of identifying anomalous human behaviour within a 'closed' organisation's IT infrastructure. We note that this behaviour may be malicious (for example, an employee is seeking to act against the best interest of the organisation by stealing confidential information) or benign (for example, an employee is applying some workaround to complete their job). To help distinguish between users who are intentionally malicious and those who are benign, we use human behaviour modelling along with Artificial Intelligence. Ben-ware has been developed as a distributed system comprising of probes for data collection, intermediate nodes for data routing and higher nodes for data analysis. This allows for real-time analysis with low impact on the overall infrastructure, which may contain legacy and low-power resources. We present an analysis of the appropriateness of the Ben-ware system for deployment within a large closed organisation, comprising of both new and legacy hardware, to protect its essential information. This analysis is performed in terms of the memory footprint, disk footprint and processing requirements of the different parts of the system.

Item Type:Book chapter
Keywords:Insider threats, Detection, Anomalous behaviour, Human behaviour, Artificial intelligence, Assistive tool, Ethics
Full text:(AM) Accepted Manuscript
Download PDF
(1296Kb)
Status:Peer-reviewed
Publisher Web site:http://dx.doi.org/10.1145/2808783.2808785
Publisher statement:© 2015 ACM. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in 7th ACM CCS International Workshop on Managing Insider Security Threats, MIST '15, 12-16 October 2015, Denver, Colorado ; proceedings, 2015, http://dx.doi.org/10.1145/2808783.2808785
Date accepted:No date available
Date deposited:24 November 2015
Date of first online publication:2015
Date first made open access:No date available

Save or Share this output

Export:
Export
Look up in GoogleScholar