Author

Kazım Yıldız

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Open access Oct 2026

Adversarial attack detection in resource-constrained environments: a stable and sequential federated learning architecture with TinyLlama-1.1B

Large language models (LLMs) create significant training bottlenecks on resource-constrained edge devices because of their massive size. Existing federated learning architectures typically require clients to train simultaneously; however, this leads to system crashes due to the high amount of VRAM required by LLMs. Whi...

Sevim Ceylan Böcekçi, Kazım Yıldız · Cluster Computing · 0 citations

Preprint Jul 2026

Federated Learning Architecture: Data Privacy and System Security Approaches

It was concluded that strategies such as the careful selection of differential privacy parameters and training settings, along with the use of larger datasets, can improve the efficiency of FL and demonstrate that privacy-preserving and high-performance artificial intelligence systems can be securely applied in sensiti...

Cagdas Karatas, Hibanur Karadogan, A. Ertug et al. · 0 citations