56 citations · 256 across the 29 of their papers we have counts for
11 papers · 1 filter
Flow Exporter Impact on Intelligent Intrusion Detection Systems
Daniela Pinto, João Vitorino, Eva Maia +2
High-quality datasets are critical for training machine learning models, as inconsistencies in feature generation can hinder the accuracy and reliability of threat detection. For t…
Network Simulation with Complex Cyber-attack Scenarios
Tiago Dias, João Vitorino, Eva Maia +1
Network Intrusion Detection (NID) systems can benefit from Machine Learning (ML) models to detect complex cyber-attacks. However, to train them with a great amount of high-quality…
Intelligent Green Efficiency for Intrusion Detection
Pedro Pereira, Paulo Mendes, João Vitorino +2
Artificial Intelligence (AI) has emerged in popularity recently, recording great progress in various industries. However, the environmental impact of AI is a growing concern, in te…
SCoPE: Evaluating LLMs for Software Vulnerability Detection
José Gonçalves, Tiago Dias, Eva Maia +1
In recent years, code security has become increasingly important, especially with the rise of interconnected technologies. Detecting vulnerabilities early in the software developme…
FuzzTheREST: An Intelligent Automated Black-box RESTful API Fuzzer
Tiago Dias, Eva Maia, Isabel Praça
Software's pervasive impact and increasing reliance in the era of digital transformation raise concerns about vulnerabilities, emphasizing the need for software security. Fuzzy tes…
Adversarial Evasion Attack Efficiency against Large Language Models
João Vitorino, Eva Maia, Isabel Praça
Large Language Models (LLMs) are valuable for text classification, but their vulnerabilities must not be disregarded. They lack robustness against adversarial examples, so it is pe…
Efficient Network Traffic Feature Sets for IoT Intrusion Detection
Miguel Silva, João Vitorino, Eva Maia +1
The use of Machine Learning (ML) models in cybersecurity solutions requires high-quality data that is stripped of redundant, missing, and noisy information. By selecting the most r…
S3PHER: Secure and Searchable System for Patient-driven HEalth data shaRing
Ivan Costa, Ivone Amorim, Eva Maia +2
Healthcare data contains some of the most sensitive information about an individual, yet sharing this data with healthcare practitioners can significantly enhance patient care and…
EnergAIze: Multi Agent Deep Deterministic Policy Gradient for Vehicle to Grid Energy Management
Tiago Fonseca, Luis Ferreira, Bernardo Cabral +2
This paper investigates the increasing roles of Renewable Energy Sources (RES) and Electric Vehicles (EVs). While indicating a new era of sustainable energy, these also introduce c…
Reliable Feature Selection for Adversarially Robust Cyber-Attack Detection
João Vitorino, Miguel Silva, Eva Maia +1
The growing cybersecurity threats make it essential to use high-quality data to train Machine Learning (ML) models for network traffic analysis, without noisy or missing data. By s…
An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection
João Vitorino, Miguel Silva, Eva Maia +1
As cyber-attacks become more sophisticated, improving the robustness of Machine Learning (ML) models must be a priority for enterprises of all sizes. To reliably compare the robust…