69 citations · 109 across the 14 of their papers we have counts for
14 papers
Empowering IoT Security: On-Device Intrusion Detection in Resource Constrained Devices
Vasilis Ieropoulos, Eirini Anthi, Theodoros Spyridopoulos +3
IoT devices particularly microcontrollers are challenged by their inherent limitations in processing capabilities, memory capacity, and energy conservation. Securing communication…
Gotham Dataset 2025: A Reproducible Large-Scale IoT Network Dataset for Intrusion Detection and Security Research
Othmane Belarbi, Theodoros Spyridopoulos, Eirini Anthi +3
In this paper, a dataset of IoT network traffic is presented. Our dataset was generated by utilising the Gotham testbed, an emulated large-scale Internet of Things (IoT) network de…
Energy-Aware Dynamic Neural Inference
Marcello Bullo, Seifallah Jardak, Pietro Carnelli +1
The growing demand for intelligent applications beyond the network edge, coupled with the need for sustainable operation, are driving the seamless integration of deep learning (DL)…
Multi-stage Attack Detection and Prediction Using Graph Neural Networks: An IoT Feasibility Study
Hamdi Friji, Ioannis Mavromatis, Adrian Sanchez-Mompo +3
With the ever-increasing reliance on digital networks for various aspects of modern life, ensuring their security has become a critical challenge. Intrusion Detection Systems play…
Mitigating System Bias in Resource Constrained Asynchronous Federated Learning Systems
Jikun Gao, Ioannis Mavromatis, Peizheng Li +2
Federated learning (FL) systems face performance challenges in dealing with heterogeneous devices and non-identically distributed data across clients. We propose a dynamic global m…
Cybersecurity in Motion: A Survey of Challenges and Requirements for Future Test Facilities of CAVs
Ioannis Mavromatis, Theodoros Spyridopoulos, Pietro Carnelli +12
The way we travel is changing rapidly, and Cooperative Intelligent Transportation Systems (C-ITSs) are at the forefront of this evolution. However, the adoption of C-ITSs introduce…
FROST: Towards Energy-efficient AI-on-5G Platforms -- A GPU Power Capping Evaluation
Ioannis Mavromatis, Stefano De Feo, Pietro Carnelli +2
The Open Radio Access Network (O-RAN) is a burgeoning market with projected growth in the upcoming years. RAN has the highest CAPEX impact on the network and, most importantly, con…
Federated Deep Learning for Intrusion Detection in IoT Networks
Othmane Belarbi, Theodoros Spyridopoulos, Eirini Anthi +3
The vast increase of Internet of Things (IoT) technologies and the ever-evolving attack vectors have increased cyber-security risks dramatically. A common approach to implementing…
Sustainable Edge Intelligence Through Energy-Aware Early Exiting
Marcello Bullo, Seifallah Jardak, Pietro Carnelli +1
Deep learning (DL) models have emerged as a promising solution for the Internet of Things (IoT). However, due to their computational complexity, DL models consume significant amoun…
Resource-Interaction Graph: Efficient Graph Representation for Anomaly Detection
James Pope, Jinyuan Liang, Vijay Kumar +13
Security research has concentrated on converting operating system audit logs into suitable graphs, such as provenance graphs, for analysis. However, provenance graphs can grow very…
LE3D: A Lightweight Ensemble Framework of Data Drift Detectors for Resource-Constrained Devices
Ioannis Mavromatis, Adrian Sanchez-Mompo, Francesco Raimondo +8
Data integrity becomes paramount as the number of Internet of Things (IoT) sensor deployments increases. Sensor data can be altered by benign causes or malicious actions. Mechanism…
A Federated Learning-enabled Smart Street Light Monitoring Application: Benefits and Future Challenges
Diya Anand, Ioannis Mavromatis, Pietro Carnelli +1
Data-enabled cities are recently accelerated and enhanced with automated learning for improved Smart Cities applications. In the context of an Internet of Things (IoT) ecosystem, t…
An Intrusion Detection System based on Deep Belief Networks
Othmane Belarbi, Aftab Khan, Pietro Carnelli +1
The rapid growth of connected devices has led to the proliferation of novel cyber-security threats known as zero-day attacks. Traditional behaviour-based IDS rely on DNN to detect…
A Dataset of Images of Public Streetlights with Operational Monitoring using Computer Vision Techniques
Ioannis Mavromatis, Aleksandar Stanoev, Pietro Carnelli +3
A dataset of street light images is presented. Our dataset consists of images, taken from 140 UMBRELLA nodes installed in the South Gloucestershire region in th…