NLP-Based Detection of Insider Threats and Prevention of Data Breaches

Description of the subject
Description of the subject

This PhD project aims to explore and develop innovative techniques in Natural Language Processing (NLP) for the detection of insider threats and prevention of data breaches. The research will focus on applying advanced machine learning algorithms and NLP models to analyze patterns in data and identify potential security risks from within an organization. The objective is to build a proactive security model that uses NLP to analyze behavioral data and detect anomalies that could signal insider threats.

Keywords

Natural Language Processing (NLP), Machine Learning, Insider Threat Detection, Data Breaches, Cybersecurity, Anomaly Detection, Behavioral Analysis

Required profile

The ideal candidate for this project should have:

  • Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • Strong foundation in NLP and Machine Learning techniques.
  • Background or interest in Cybersecurity .
  • Analytical skills and proficiency in programming (Python preferred).
  • Good command of English.
Deadline for Application:

November 11, 2024

a.ammour@ueuromed.org & Cedoc.admission@ueuromed.org

Supervisors

Prof. Alae Ammour
Euromed University of Fez (UEMF)