| Title | An Exploratory Study of Security Data Analysis Method for Insider Threat Prevention |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Kim, Jawon, Chang, Hangbae |
| Conference Name | 2022 13th International Conference on Information and Communication Technology Convergence (ICTC) |
| Keywords | convergence, Data analysis, Data Analysis Method, Human Behavior, human factors, information and communication technology, insider threat, insider threats, Metrics, Policy Based Governance, policy-based governance, pubcrawl, resilience, Resiliency, security, Security Data Analysis |
| Abstract | Insider threats are steadily increasing, and the damage is also enormous. To prevent insider threats, security solutions, such as DLP, SIEM, etc., are being steadily developed. However, they have limitations due to the high rate of false positives. In this paper, we propose a data analysis method and methodology for responding to a technology leak incident. The future study may be performed based on the proposed methodology. |
| DOI | 10.1109/ICTC55196.2022.9952395 |
| Citation Key | kim_exploratory_2022 |
An Exploratory Study of Security Data Analysis Method for Insider Threat Prevention