2 citations · 2 across the 5 of their papers we have counts for
6 papers
RepTC: Representation-Aware Optimization for Efficient Traffic Classification on Edge IoT Devices
Adel Chehade, Edoardo Ragusa, Paolo Gastaldo +1
Traffic classification (TC) is crucial to secure Internet of Things (IoT) networks, whose edge nodes often operate under privacy, bandwidth, and energy constraints. Yet, encrypted…
Adversarial Robustness of Traffic Classification under Resource Constraints: Input Structure Matters
Adel Chehade, Edoardo Ragusa, Paolo Gastaldo +1
Traffic classification (TC) plays a critical role in cybersecurity, particularly in IoT and embedded contexts, where inspection must often occur locally under tight hardware constr…
Intrusion Detection on Resource-Constrained IoT Devices with Hardware-Aware ML and DL
Ali Diab, Adel Chehade, Edoardo Ragusa +4
This paper proposes a hardware-aware intrusion detection system (IDS) for Internet of Things (IoT) and Industrial IoT (IIoT) networks; it targets scenarios where classification is…
Energy-Efficient Deep Learning for Traffic Classification on Microcontrollers
Adel Chehade, Edoardo Ragusa, Paolo Gastaldo +1
In this paper, we present a practical deep learning (DL) approach for energy-efficient traffic classification (TC) on resource-limited microcontrollers, which are widely used in Io…
Hardware-Aware Neural Architecture Search for Encrypted Traffic Classification on Resource-Constrained Devices
Adel Chehade, Edoardo Ragusa, Paolo Gastaldo +1
This paper presents a hardware-efficient deep neural network (DNN), optimized through hardware-aware neural architecture search (HW-NAS); the DNN supports the classification of ses…
Tiny Neural Networks for Session-Level Traffic Classification
Adel Chehade, Edoardo Ragusa, Paolo Gastaldo +1
This paper presents a system for session-level traffic classification on endpoint devices, developed using a Hardware-aware Neural Architecture Search (HW-NAS) framework. HW-NAS op…