Addressing Insider Threat Through Big Data Analytics

Nov 01, 2013

Employees with authorized access to an organization’s network infrastructure pose a significant risk for employers. Individuals within an organization, whether disgruntled or otherwise motivated, possess the potential to cause harm in a variety of ways.

  • How do we protect against such an individual who is involved in nefarious activity?
  • Someone who seeks to harm the organization or exploit information from within the organization for the purpose of political or financial gain?
  • How can we internally track the spread of information?
  • How do we determine what is normal and abnormal behavior within our computer networks?

This paper address these types of questions and presents a new approach leveraging Big Data analytics that advances the state-of-the-art for tracking a user’s behavior within a computer network system and reduces the threat of malicious insider behavior.


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