AI RESEARCH
Hardware-Aware Neural Architecture Search for Encrypted Traffic Classification on Resource-Constrained Devices
arXiv CS.LG
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ArXi:2506.11319v2 Announce Type: replace-cross This paper presents a hardware-efficient deep neural network (DNN), optimized through hardware-aware neural architecture search (HW-NAS); the DNN s the classification of session-level encrypted traffic on resource-constrained Internet of Things (IoT) and edge devices. Thanks to HW-NAS, a 1D convolutional neural network (CNN) is tailored on the ISCX VPN-nonVPN dataset to meet strict memory and computational limits while achieving robust performance.