Case Study: Uncovering User-Based Insider Threats with Machine-Learning Algorithms

Case Study: Uncovering User-Based Insider Threats with Machine-Learning Algorithms

One of the world's largest Internet companies manages all customer data in a proprietary account management system, which is at the heart of its business operations. This company has a large security team and invests huge efforts to ensure the privacy and integrity of its customer data.

Aware of the dangers of today's cyber threats, the company's security team realized that it required smarter tools to protect its infrastructure and internal systems from hard-to-detect user-based threats.

Download this case study to explore:

  • How malicious insiders can exploit legitimate user credentials, leading to data breaches
  • How machine-learning algorithms can help pinpointing user-based insider threats
  • Why using behavior analytics helps produce accessible, easily visualized alerts and reports



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