
Federated learning can achieve comparable performance to centralized training for cyber threat detection tasks like SMS spam detection and Android malware detection, while being resilient to practical adversarial attacks and efficient in realistic non-IID data distribution scenarios.


coremsg

federated-learning-for-privacy-preserving-cyber-threat-detection-evaluating-effectiveness-adversarial-resistance-and-efficiency


Federated Learning for Privacy-Preserving Cyber Threat Detection: Evaluating Effectiveness, Adversarial Resistance, and Efficiency


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A machine learning-based model is developed to predict individuals who may be victims of cyber attacks by analyzing socioeconomic factors. Key risk factors are identified through association rule mining.


predictive-analysis-on-cyber-security-threats-with-key-risk-factors


Predictive Analysis on Cyber Security Threats with Key Risk Factors
