Advanced Risk Measurement Approach to Insider Threats in Cyberspace
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cho, Inhyun | - |
dc.contributor.author | Lee, Kyungho | - |
dc.date.accessioned | 2021-09-04T05:20:53Z | - |
dc.date.available | 2021-09-04T05:20:53Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2016 | - |
dc.identifier.issn | 1079-8587 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/90304 | - |
dc.description.abstract | Inside jobs have been a source of critical threats in cyberspace. To manage such insider threats, a proper measurement approach is required for effective risk-based decision-making. The measurement approach should include insider-related information (e.g. the significance of jobs, the position level, the required authority for data, and the type of employment) in order to better measure and analyze insider risks. In this paper, we suggest an approach that takes into account the insider-related information in calculating data leakage risk of insiders in the banking sector. We implement this approach by utilizing real-world data to calculate insider risks. We present an effective risk measurement approach, which we believe can enhance decision-making process for risk management for insider threats. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | TAYLOR & FRANCIS INC | - |
dc.title | Advanced Risk Measurement Approach to Insider Threats in Cyberspace | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Kyungho | - |
dc.identifier.doi | 10.1080/10798587.2015.1121617 | - |
dc.identifier.scopusid | 2-s2.0-84953286434 | - |
dc.identifier.wosid | 000380901000010 | - |
dc.identifier.bibliographicCitation | INTELLIGENT AUTOMATION AND SOFT COMPUTING, v.22, no.3, pp.405 - 413 | - |
dc.relation.isPartOf | INTELLIGENT AUTOMATION AND SOFT COMPUTING | - |
dc.citation.title | INTELLIGENT AUTOMATION AND SOFT COMPUTING | - |
dc.citation.volume | 22 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 405 | - |
dc.citation.endPage | 413 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Automation & Control Systems | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Automation & Control Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.subject.keywordAuthor | Insider threat | - |
dc.subject.keywordAuthor | risk measurement | - |
dc.subject.keywordAuthor | data leakage | - |
dc.subject.keywordAuthor | banking Sector | - |
dc.subject.keywordAuthor | cyberspace | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.