1 citations · 1 across the 6 of their papers we have counts for
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AntiFLipper: A Secure and Efficient Defense Against Label-Flipping Attacks in Federated Learning
Aashnan Rahman, Abid Hasan, Sherajul Arifin +5
Federated learning (FL) enables privacy-preserving model training by keeping data decentralized. However, it remains vulnerable to label-flipping attacks, where malicious clients m…
FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning
Md Rafid Haque, Abu Raihan Mostofa Kamal, Md. Azam Hossain
Federated Learning (FL) offers a paradigm for privacy-preserving collaborative AI, but its decentralized nature creates significant vulnerabilities to model poisoning attacks. Whil…
A Pan-cancer Classification Model using Multi-view Feature Selection Method and Ensemble Classifier
Tareque Mohmud Chowdhury, Farzana Tabassum, Sabrina Islam +1
Accurately identifying cancer samples is crucial for precise diagnosis and effective patient treatment. Traditional methods falter with high-dimensional and high feature-to-sample…