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Detecting insider threats using Ben-ware : beneficial intelligent software for identifying anomalous human behaviour.

McGough, Andrew Stephen and Arief, Budi and Gamble, Carl and Wall, David and Brennan, John and Fitzgerald, John and van Moorsel, Aad and Alwis, Sujeewa and Theodoropoulos, Georgios and Ruck-Keene, Ed (2015) 'Detecting insider threats using Ben-ware : beneficial intelligent software for identifying anomalous human behaviour.', Journal of wireless mobile networks, ubiquitous computing, and dependable applications., 6 (4). pp. 1-44.

Abstract

The insider threat problem is a significant and ever present issue faced by any organisation. While security mechanisms can be put in place to reduce the chances of external agents gaining access to a system, either to steal assets or alter records, the issue is more complex in tackling insider threat. If an employee already has legitimate access rights to a system, it is much more difficult to prevent them from carrying out inappropriate acts, as it is hard to determine whether the acts are part of their official work or indeed malicious. We present in this paper the concept of “Ben-ware”: a beneficial software system that uses low-level data collection from employees’ computers, along with Artificial Intelligence, to identify anomalous behaviour of an employee. By comparing each employee’s activities against their own ‘normal’ profile, as well as against the organisational’s norm, we can detect those that are significantly divergent, which might indicate malicious activities. Dealing with false positives is one of the main challenges here. Anomalous behaviour could indicate malicious activities (such as an employee trying to steal confidential information), but they could also be benign (for example, an employee is carrying out a workaround or taking a shortcut to complete their job). Therefore it is important to minimise the risk of false positives, and we do this by combining techniques from human factors, artificial intelligence, and risk analysis in our approach. Developed as a distributed system, Ben-ware has a three-tier architecture composed of (i) probes for data collection, (ii) intermediate nodes for data routing, and (iii) high level nodes for data analysis. The distributed nature of Ben-ware allows for near-real-time analysis of employees without the need for dedicated hardware or a significant impact on the existing infrastructure. This will enable Ben-ware to be deployed in situations where there are restrictions due to legacy and low-power resources, or in cases where the network connection may be intermittent or has a low bandwidth. We demonstrate the appropriateness of Ben-ware, both in its ability to detect potentially malicious acts and its lowimpact on the resources of the organisation, through a proof-of-concept system and a scenario based on synthetically generated user data.

Item Type:Article
Keywords:Insider threats, Detection, Anomalous behaviour, Human behaviour, Artificial intelligence, Assistive tool, Ethics.
Full text:Publisher-imposed embargo
(VoR) Version of Record
File format - PDF
(2201Kb)
Status:Peer-reviewed
Publisher Web site:http://jowua.yolasite.com/vol6no4.php
Date accepted:16 December 2015
Date deposited:20 January 2016
Date of first online publication:December 2015
Date first made open access:No date available

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