Beyond the Perimeter: Redefining Insider Threat Modeling through Adaptive Behavioral Analytics in Hybrid Work Environments

@article{1709862,
      author = {Tim Abdiukov},
      title = {Beyond the Perimeter: Redefining Insider Threat Modeling through Adaptive Behavioral Analytics in Hybrid Work Environments},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {6},
      number = {2},
      pages = {393-404},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1709862.pdf},
      abstract = {The rise of the hybrid work model has highlighted the limitations of a perimeter-based approach to security and also reintroduced the concept of insider threats in a new and entirely different way. This research presents an overview of the historical development of the insider threat paradigm from the 1990s to the present year, 2021, and how conventional detection measures, which employ a combination of networks and static rules, no longer suffice in distributed work environments. The paper suggests the need to dynamically reconfigure the modeling of insider threats by introducing versatile, adaptive behavioral analytics ?an approach based on machine learning and ongoing user behavior profiling. The research paper is based on case studies, psychological theory, and technical advances in the field through 2021. It can be generalized as a hybrid-ready security model that combines behavioral cues, contextual awareness, and risk scoring to increase detection accuracy. This cross-functional exploration ultimately offers a broader approach to reducing insider threats in workplaces, which have become increasingly interesting and virtual in contemporary, more fluid work environments.},
      keywords = {Insider Threats; Adaptive Behavioral Analytics; Hybrid Work Environments; Behavioral Risk Scoring; Cybersecurity; UEBA},
      month = {August},
  }