Download PDFOpen PDF in browserDesign of a Cross-Layer AI Agent for Secure Spectrum-Aware Network Slicing5 pages•Published: April 19, 2026AbstractThe next generation of 6G networks must seamlessly support applications ranging from holographic communications and XR to massive IoT and autonomous systems, all under diverse and stringent QoS demands. While network slicing enables service-specific virtual networks, current solutions remain siloed, with network-level slicing unaware of real-time spectrum conditions and physical-layer sensing lacking application and security context. This paper presents CogniSense-Slice, a cross-layer AI agent that unifies spectrum awareness, intelligent slice orchestration, and proactive security. The framework integrates a 1D CNN–based Perception Module for high-resolution spectrum mapping, a DNN–driven Orchestration Module for dynamic, context-aware slice allocation, and a Guardian Module for real-time, cross-layer threat mitigation. Through simulation using fused DeepSense and DeepSlice datasets augmented with attack scenarios, CogniSense-Slice demonstrates faster slice migration to optimal bands, improved throughput and latency, and superior detection of coordinated physical and network-layer attacks. This work advances AI-native networking by bridging the physical-network layer divide, enabling resilient, adaptive, and spectrum-efficient 6G systems.Keyphrases: edge intelligence, physical layer sensing, proactive threat mitigation, real time spectrum mapping, secure network slicing, spectrum efficiency In: Jernej Masnec, Hamid Reza Karimian, Parisa Kordjamshidi and Yan Li (editors). Proceedings of AI for Accelerated Research Symposium, vol 3, pages 103-107.
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