research
∙
08/11/2023
CyberForce: A Federated Reinforcement Learning Framework for Malware Mitigation
The expansion of the Internet-of-Things (IoT) paradigm is inevitable, bu...
share
research
∙
07/21/2023
Mitigating Communications Threats in Decentralized Federated Learning through Moving Target Defense
The rise of Decentralized Federated Learning (DFL) has enabled the train...
research
∙
06/27/2023
MTFS: a Moving Target Defense-Enabled File System for Malware Mitigation
Ransomware has remained one of the most notorious threats in the cyberse...
research
∙
06/27/2023
RansomAI: AI-powered Ransomware for Stealthy Encryption
Cybersecurity solutions have shown promising performance when detecting ...
research
∙
06/16/2023
Fedstellar: A Platform for Decentralized Federated Learning
In 2016, Google proposed Federated Learning (FL) as a novel paradigm to ...
research
∙
06/14/2023
Single-board Device Individual Authentication based on Hardware Performance and Anomaly Detection for Crowdsensing Platforms
The proliferation of the Internet of Things (IoT) has led to the emergen...
research
∙
12/30/2022
Adversarial attacks and defenses on ML- and hardware-based IoT device fingerprinting and identification
In the last years, the number of IoT devices deployed has suffered an un...
research
∙
12/30/2022
RL and Fingerprinting to Select Moving Target Defense Mechanisms for Zero-day Attacks in IoT
Cybercriminals are moving towards zero-day attacks affecting resource-co...
research
∙
11/15/2022
Decentralized Federated Learning: Fundamentals, State-of-the-art, Frameworks, Trends, and Challenges
In the last decade, Federated Learning (FL) has gained relevance in trai...
research
∙
11/01/2022
Maximum Likelihood Distillation for Robust Modulation Classification
Deep Neural Networks are being extensively used in communication systems...
research
∙
10/20/2022
Analyzing the Robustness of Decentralized Horizontal and Vertical Federated Learning Architectures in a Non-IID Scenario
Federated learning (FL) allows participants to collaboratively train mac...
research
∙
10/14/2022
A Lightweight Moving Target Defense Framework for Multi-purpose Malware Affecting IoT Devices
Malware affecting Internet of Things (IoT) devices is rapidly growing du...
research
∙
04/18/2022
LwHBench: A low-level hardware component benchmark and dataset for Single Board Computers
In today's computing environment, where Artificial Intelligence (AI) and...
research
∙
01/31/2022
Studying the Robustness of Anti-adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors
Device fingerprinting combined with Machine and Deep Learning (ML/DL) re...
research
∙
01/14/2022
CyberSpec: Intelligent Behavioral Fingerprinting to Detect Attacks on Crowdsensing Spectrum Sensors
Integrated sensing and communication (ISAC) is a novel paradigm using cr...
research
∙
11/29/2021
Robust Federated Learning for execution time-based device model identification under label-flipping attack
The computing device deployment explosion experienced in recent years, m...
research
∙
08/19/2021
5G System Security Analysis
Fifth generation mobile networks (5G) are currently being deployed by mo...
research
∙
06/15/2021
Can Evil IoT Twins Be Identified? Now Yes, a Hardware Behavioral Fingerprinting Methodology
The connectivity and resource-constrained nature of IoT, and in particul...
research
∙
05/28/2021
SafeAMC: Adversarial training for robust modulation recognition models
In communication systems, there are many tasks, like modulation recognit...
research
∙
04/15/2021
Federated Learning for Malware Detection in IoT Devices
This work investigates the possibilities enabled by federated learning c...
research
∙
03/27/2021
On the benefits of robust models in modulation recognition
Given the rapid changes in telecommunication systems and their higher de...
research
∙
08/07/2020
