top of page

Anomaly Detection

The identification of deviations from normal behavior in data, systems, or networks to detect potential threats.

Understanding Anomaly Detection


Anomaly detection plays a vital role in cybersecurity by identifying deviations from normal behavior, helping organizations detect cyber threats before they cause significant damage.

Key Techniques


Statistical Analysis

  • Uses mathematical models to define normal behavior.

  • Flags deviations that exceed predefined thresholds.

Machine Learning-Based Detection

  • AI algorithms analyze patterns and detect anomalies in real time.

  • Improves over time through adaptive learning.

Behavioral Analytics

  • Monitors user activity to detect unauthorized access attempts.

  • Identifies insider threats and compromised credentials.

Best Practices


  • Use AI-driven anomaly detection systems for real-time threat identification.

  • Implement multi-layered security controls to verify anomalies.

  • Continuously update anomaly detection models with new threat data.

DC_stationary_R2-08.png

© 2025 DeepCytes. All Rights Reserved.

Locate Us

​Express Towers, Marine Drive,Nariman Point, Mumbai - 400021

Legal

Follow Us

bottom of page