Assessment of insider attack with learning statistics methods

Kotsiuba, Igor

Abstract

The popularity of mobile devices, wearable devices used in collaborative information systems, has dramatically exploded over the past decade. Thus, we understand that in ordinary office, a single person can use plenty of active interfaces like wireless data transfer interfaces, which can help, among direct usage, strengthen access control and information security subsystem. Despite the fact that enterprises quite rightly develop controls and prevention techniques to combat cyberattacks, threats from users within the corporate network pose a significant risk to information assets. Existing users with accounts, permissions and access required to perform their jobs are increasingly becoming a major risk to information security through account misuse, data loss and fraudulent activities. This article reviews the definition of an insider threat and its impact, and
provides an overview of the techniques to control and remediate these threats

Citation

Kotsiuba, I. (2016, February). Assessment of insider attack with learning statistics methods. Presented at ICISSP 2016 - 2nd International Conference on Information Systems Security and Privacy, Doctoral Consortium

• Presentation Conference Type: Other
• Conference Name: ICISSP 2016 - 2nd International Conference on Information Systems Security and Privacy, Doctoral Consortium
• Start Date: Feb 19, 2016
• End Date: Feb 21, 2016
• Deposit Date: Nov 10, 2023
• Public URL: https://durham-repository.worktribe.com/output/1904004
• Additional Information: No file attached - before author joined DU; ; Can be found here: https://www.scopus.com/record/display.uri?eid=2-s2.0-84966633295&origin=inward&txGid=6abd2a3e8ec83a37ff068bbe382e6508