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Author

B. Deepthi

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Conference Jul 2026

Graph Neural Networks for Threat Intelligence and Cyber-Attack Path Prediction

Graph Neural Networks (GNNs) have become a potent paradigm of complex data related to relations, and it is especially applicable to threat intelligence analysis and prediction of cyber-attack lines. The proposed paper describes a GNN framework that combines the sources of heterogeneous cyber threat intelligence, includ...

D. Rajesh, Adamala Siri, Bandari Vyshnavi et al. · 0 citations
Conference Aug 2026

Intelligent Intrusion Detection System Using Hybrid Swin Transformer-RNN for Efficient Cyber Threat Mitigation

Due to the rising frequency as well as complexity of Cyber-attacks the real-time Intrusion Detection Systems (IDS) have a greater demand for reliable. Conventional IDS techniques frequently encounter performance limitations when dealing with high-dimensional data as well as temporal patterns. In order to efficiently de...

B. Deepthi, M. Sreenivasu, Chichari Rajesh · 0 citations

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