Triple Layer Cyber Security Model for Anomaly Detection

The paper presents a comprehensive approach to fortifying digital assets against sophisticated cyber threats. Combining Machine Learning (ML), reputation-based analysis, and signature-based detection, the model offers a proactive defence mechanism to identify and mitigate anomalies effectively. Traditional security measures often fail to detect evolving threats, highlighting the need for more sophisticated cybersecurity countermeasures. Anomaly detection plays a pivotal role in identifying deviations from normal behaviour, aiding intrusion detection and bolstering overall cybersecurity posture. The model’s adaptability and sophistication address the dynamic nature of cyber threats, providing organizations with a robust defence strategy. This paper has also discussed future enhancements in ML algorithms, integration of Artificial Intelligence (AI) technologies, and scalability considerations.