56 citations · 256 across the 29 of their papers we have counts for
8 papers · 1 filter
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection
João Vitorino, Isabel Praça, Eva Maia
Machine Learning (ML) can be incredibly valuable to automate anomaly detection and cyber-attack classification, improving the way that Network Intrusion Detection (NID) is performe…
Herb-Drug Interactions: A Holistic Decision Support System in Healthcare
Andreia Martins, Eva Maia, Isabel Praça
Complementary and alternative medicine are commonly used concomitantly with conventional medications leading to adverse drug reactions and even fatality in some cases. Furthermore,…
From Data to Action: Exploring AI and IoT-driven Solutions for Smarter Cities
Tiago Dias, Tiago Fonseca, João Vitorino +3
The emergence of smart cities demands harnessing advanced technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) and promises to unlock cities' potential t…
TestLab: An Intelligent Automated Software Testing Framework
Tiago Dias, Arthur Batista, Eva Maia +1
The prevalence of software systems has become an integral part of modern-day living. Software usage has increased significantly, leading to its growth in both size and complexity.…
Data Privacy with Homomorphic Encryption in Neural Networks Training and Inference
Ivone Amorim, Eva Maia, Pedro Barbosa +1
The use of Neural Networks (NNs) for sensitive data processing is becoming increasingly popular, raising concerns about data privacy and security. Homomorphic Encryption (HE) has t…
Adversarial Robustness and Feature Impact Analysis for Driver Drowsiness Detection
João Vitorino, Lourenço Rodrigues, Eva Maia +2
Drowsy driving is a major cause of road accidents, but drivers are dismissive of the impact that fatigue can have on their reaction times. To detect drowsiness before any impairmen…
Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and Classification
João Vitorino, Isabel Praça, Eva Maia
The Internet of Things (IoT) faces tremendous security challenges. Machine learning models can be used to tackle the growing number of cyber-attack variations targeting IoT systems…
Constrained Adversarial Learning for Automated Software Testing: a literature review
João Vitorino, Tiago Dias, Tiago Fonseca +2
It is imperative to safeguard computer applications and information systems against the growing number of cyber-attacks. Automated software testing tools can be developed to quickl…