SECURITY ISSUES IN RECOMMENDATION SYSTEMS AND THEIR SOLUTIONS

Аннотация

The rapid expansion of recommendation systems has significantly improved user experiences across digital platforms. However, these systems also present substantial security risks, including data poisoning, adversarial attacks, model inversion, privacy leakage, and fake account manipulations. Such vulnerabilities can degrade recommendation quality, expose sensitive user information, and compromise system integrity. This paper provides a comprehensive analysis of security threats in recommendation systems, their impact on users and businesses, and potential mitigation strategies. By implementing advanced security measures such as anomaly detection, differential privacy, encryption, and continuous monitoring, organizations can enhance the resilience and trustworthiness of recommendation systems. Addressing these challenges is essential for maintaining data security and ensuring reliable, user-centric recommendations.