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Mostrando ítems 11-19 de 19
Multi-objective evolutionary optimization for dimensionality reduction of texts represented by synsets
(PeerJ, 2023)
Despite new developments in machine learning classification techniques, improving the accuracy of spam filtering is a difficult task due to linguistic phenomena that limit its effectiveness. In particular, we highlight ...
Gotham Testbed: A Reproducible IoT Testbed for Security Experiments and Dataset Generation
(IEEE, 2023)
The growing adoption of the Internet of Things (IoT) has brought a significant increase in attacks targeting those devices. Machine learning (ML) methods have shown promising results for intrusion detection; however, the ...
Clustered federated learning architecture for network anomaly detection in large scale heterogeneous IoT networks
(Elsevier, 2023)
There is a growing trend of cyberattacks against Internet of Things (IoT) devices; moreover, the sophistication and motivation of those attacks is increasing. The vast scale of IoT, diverse hardware and software, and being ...
Deobfuscating leetspeak with deep learning to improve spam filtering
(UNIR - Universidad Internacional de La Rioja, 2023)
The evolution of anti-spam filters has forced spammers to make greater efforts to bypass filters in order to distribute content over networks. The distribution of content encoded in images or the use of Leetspeak are ...
Novel email spam detection method using sentiment analysis and personality recognition
(Oxford Academic, 2020)
Unsolicited email campaigns remain as one of the biggest threats affecting millions of users per day. During the past years several techniques to detect unsolicited emails have been developed. This work provides means to ...
Federated Explainability for Network Anomaly Characterization
(ACM, 2023)
Machine learning (ML) based systems have shown promising results for intrusion detection due to their ability to learn complex patterns. In particular, unsupervised anomaly detection approaches offer practical advantages ...
Latentziarik gabeko sareko identifikatzaileen aleatorizazioa kontrol industrialerako sistemetan proaktiboki errekonozimendu erasoak mitigatzeko
(UEU, 2023)
Kontrol industrialerako sistemak askotariko instalazio industrialetan erabiltzen dira, azpiegitura kritikoetan barne, segurtasun-eraso anitzen helburu nagusi bihurtuz. Sare industrialen konfigurazio eta topologia estatikoek, ...
On the use of MiniCPS for conducting rigorous security experiments in Software-Defined Industrial Control Systems
(Springer, 2024)
Software-Defined Networking (SDN) offers a global view over the network and the ability of centrally and dynamically managing network flows, making them ideal for creating security threat detection and mitigation solutions. ...
Software-Defined Networking approaches for intrusion response in Industrial Control Systems: A survey
(Elsevier, 2023)
Industrial Control Systems (ICSs) are a key technology for life-sustainability, social development and economic progress used in a wide range of industrial solutions, including Critical Infrastructures (CIs), becoming the ...