TY - GEN
T1 - Understanding Insider Threats Behaviour
T2 - 16th International Conference on Intelligent Human Computer Interaction, IHCI 2024
AU - Ivan, Maria Ioana Andreea
AU - van den Hout, Niek Jan
AU - Treur, Jan
AU - Hendrikse, Sophie C.F.
AU - Roelofsma, Peter
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - This paper addresses computational analysis of insider threats. Organisational security is significantly at risk from insider threats, which are commonly caused by changes inside the organisation and worsened by unfavourable psychological characteristics and external involvements. In order to provide a comprehensive understanding of the adaptive dynamics that influence insider threats, the presented network model incorporates a variety of factors, including employee satisfaction, interactions, work performance, psychological traits, and technological methods. The simulations demonstrated that organisational changes can have a significant impact on employee behaviour, resulting in altered perceptions of the work environment, reduced satisfaction, reduced communication, and signs of isolation. These factors collectively create an environment where the risk of insider threats is heightened, as disgruntled, isolated, and dissatisfied employees are more likely to engage in malicious or negligent actions. The model’s adaptive characteristics improve its capacity to accurately represent the ever-changing interactions between human behaviour and organisational contexts. This study offers significant insights for companies aiming to improve their security frameworks by identifying crucial triggers and action points. Future efforts involve optimising model characteristics and incorporating sophisticated psychological models to improve the accuracy and practicality of predictions in real-life scenarios.
AB - This paper addresses computational analysis of insider threats. Organisational security is significantly at risk from insider threats, which are commonly caused by changes inside the organisation and worsened by unfavourable psychological characteristics and external involvements. In order to provide a comprehensive understanding of the adaptive dynamics that influence insider threats, the presented network model incorporates a variety of factors, including employee satisfaction, interactions, work performance, psychological traits, and technological methods. The simulations demonstrated that organisational changes can have a significant impact on employee behaviour, resulting in altered perceptions of the work environment, reduced satisfaction, reduced communication, and signs of isolation. These factors collectively create an environment where the risk of insider threats is heightened, as disgruntled, isolated, and dissatisfied employees are more likely to engage in malicious or negligent actions. The model’s adaptive characteristics improve its capacity to accurately represent the ever-changing interactions between human behaviour and organisational contexts. This study offers significant insights for companies aiming to improve their security frameworks by identifying crucial triggers and action points. Future efforts involve optimising model characteristics and incorporating sophisticated psychological models to improve the accuracy and practicality of predictions in real-life scenarios.
KW - Adaptive
KW - Computational analysis
KW - Cybersecurity
KW - Insider Threats
KW - Psychological Traits
UR - https://www.scopus.com/pages/publications/105007535313
UR - https://www.scopus.com/inward/citedby.url?scp=105007535313&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-88705-5_33
DO - 10.1007/978-3-031-88705-5_33
M3 - Conference contribution
AN - SCOPUS:105007535313
SN - 9783031887048
VL - 1
T3 - Lecture Notes in Computer Science
SP - 396
EP - 410
BT - Intelligent Human Computer Interaction
A2 - Singh, Dhananjay
A2 - van ’t Klooster, Jan-Willem
A2 - Tiwary, Uma Shanker
PB - Springer Nature
Y2 - 13 November 2024 through 16 November 2024
ER -