Insider Threat Detection using LSTM

Authors

  • Durga Bhandari Faculty of Science and Technology, Pokhara University
  • Kumar Pudashine Faculty of Science and Technology, Pokhara University

DOI:

https://doi.org/10.3126/jost.v3i1.69066

Keywords:

Internal Threat, deep learning, GAN, LSTM, DOS, DDOS

Abstract

Security threats have been the major challenge for any organization. This has even been more threatening since in present days most of the organizational data are in digital form and digital data are easy to access and alter if not properly secured. While most of the threats considered are external threats like Viruses, Worms, DOS, DDOS, hacking etc. Internal threats also cannot be ignored. Many frauds, especially for organizations that perform financial transactions, are done by misusing the internal access to the data. Internal threats happen from the users who have some privileged access to the data. Finding such a threat is not only difficult but also more challenging than that from the external source. Most organizations don’t give internal threats that much consideration but lately many works have been done in the field of internal threat detection.

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Published

2023-12-31

How to Cite

Bhandari, D., & Pudashine, K. (2023). Insider Threat Detection using LSTM. Journal of Science and Technology, 3(1), 57–65. https://doi.org/10.3126/jost.v3i1.69066

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Section

Articles