Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Vitorino, João"'
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 pertinent to understand the impacts of different types of perturbations,
Externí odkaz:
http://arxiv.org/abs/2406.08050
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 relevant features, data integrity and model efficiency can be significa
Externí odkaz:
http://arxiv.org/abs/2406.08042
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 selecting the most relevant features for cyber-attack detection, it is
Externí odkaz:
http://arxiv.org/abs/2404.04188
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 robustness of different ML models for cyber-attack detection in enterprise c
Externí odkaz:
http://arxiv.org/abs/2402.16912
Machine Learning (ML) can be incredibly valuable to automate anomaly detection and cyber-attack classification, improving the way that Network Intrusion Detection (NID) is performed. However, despite the benefits of ML models, they are highly suscept
Externí odkaz:
http://arxiv.org/abs/2308.06819
Autor:
Dias, Tiago, Fonseca, Tiago, Vitorino, João, Martins, Andreia, Malpique, Sofia, Praça, Isabel
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 to become more sustainable, efficient, and ultimately livable for their
Externí odkaz:
http://arxiv.org/abs/2306.04653
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 impairment occurs, a promising strategy is using Machine Learning (ML) to monit
Externí odkaz:
http://arxiv.org/abs/2303.13649
Every novel technology adds hidden vulnerabilities ready to be exploited by a growing number of cyber-attacks. Automated software testing can be a promising solution to quickly analyze thousands of lines of code by generating and slightly modifying f
Externí odkaz:
http://arxiv.org/abs/2303.07546
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, but the increasing threat posed by adversarial attacks restates the
Externí odkaz:
http://arxiv.org/abs/2301.13122
Modern organizations face numerous physical security threats, from fire hazards to more intricate concerns regarding surveillance and unauthorized personnel. Conventional standalone fire and intrusion detection solutions must be installed and maintai
Externí odkaz:
http://arxiv.org/abs/2209.00741