Abstract

The insider threat has increasingly become the cyber security challenge that threatens organisation, financial enterprises, and governmental agencies. Insider threat is being carryout by former and current employees. Meanwhile, insider threat had authorised access to an organisation asset, thus they have better opportunity to undermine the confidentiality, availability, or data integrity than an external attacker. The detection process consists of different techniques, including detecting suspicious activities in the system. This paper focus on insider threat detection through behavior analysis of user’s activities. A deep machine learning approach has been proposed to detect insiders’ threat with better accuracy with low false positive rate. The publicly available dataset used is the CMU CERT synthetic malicious insider threat dataset r4.2. Our empirical evidence outperforms compared to similar existing models, it proved that our approach (LMT) has high accuracy (99.6%), precision (99.6%) and ROC (99.6%).
Original languageEnglish
Title of host publicationProceedings of the 2023 International Conference on Advances in Computing Research (ACR’23)
EditorsKevin Daimi, Abeer Al Sadoon
PublisherSpringer
Pages359-368
Number of pages10
ISBN (Electronic)9783031337437
ISBN (Print)9783031337420
DOIs
Publication statusPublished - May 2023
EventThe 2023 International Conference on Advances in Computing Research (ACR'23) - Avanti Palms Resort, Orlando, United States
Duration: 08 May 202310 May 2023
https://iicser.org/ACR23/
https://iicser.org/ACR23/images/ACR23_Program.pdf (Program)
https://link-springer-com.ezproxy.csu.edu.au/book/10.1007/978-3-031-33743-7 (Proceedings)

Publication series

NameLecture Notes in Networks and Systems
PublisherSpringer
Volume700
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceThe 2023 International Conference on Advances in Computing Research (ACR'23)
Country/TerritoryUnited States
CityOrlando
Period08/05/2310/05/23
OtherWelcome to the 2023 International Conference on Advances in Computing Research (ACR’23). This conference is organized by the Institute for Innovations in Computer Science and Engineering Research (IICSER). The goal of this conference is to bring together researchers from academia, business, industry, and government to exchange significant and innovative contributions and research ideas and to act as a platform for international research collaboration. To this extent, ACR’23 is seeking submissions that furnish innovative ideas, techniques, methodologies and applications. ACR’23 is currently composed of six tracks.
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