| Title | The Location-Centric Approach to Employee's Interaction Pattern Detection |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Novikova, Evgenia, Bekeneva, Yana, Shorov, Andrey |
| Conference Name | 2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP) |
| Keywords | Access Control, access control system, authorisation, business data processing, business processes, Collaboration, Data analysis, data mining, data visualisation, Data visualization, employee interaction pattern detection, Human Behavior, Information security, insider threat, Insider Threat Detection, location-centric approach, location-centric bevavior patterns, Metrics, Organizations, Personnel, policy-based governance, pubcrawl, resilience, Resiliency, security policies, Sensors, step charts, Task Analysis, visualization-driven technique |
| Abstract | The task of the insider threat detection is one of the most sophisticated problems of the information security. The analysis of the logs of the access control system may reveal on how employees move and interact providing thus better understanding on how personnel observe security policies and established business processes. The paper presents an approach to the detection of the location-centric employees' interaction patterns. The authors propose the formal definition of the interaction patterns and present the visualization-driven technique to the extraction of the patterns from the data when any prior information about existing interaction routine and procedures is not available. The proposed approach is demonstrated on the data set provided within VAST MiniChallenge-2 2016 contest. |
| DOI | 10.1109/EMPDP.2019.8671546 |
| Citation Key | novikova_location-centric_2019 |
The Location-Centric Approach to Employee's Interaction Pattern Detection