Recent endeavors in machine learning-powered intrusion detection systems for the Internet of Things

Manivannan, D.

doi:10.1016/j.jnca.2024.103925

Journal of Network and Computer Applications

2024

DOI: 10.1016/j.jnca.2024.103925

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Recent endeavors in machine learning-powered intrusion detection systems for the Internet of Things

D. Manivannan

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Cited by 2 publications

References 166 publications

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Generative adversarial networks to detect intrusion and anomaly in IP flow-based networks

da Silva Ruffo,

Lent,

Carvalho

et al. 2025

Future Generation Computer Systems

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Generative adversarial networks to detect intrusion and anomaly in IP flow-based networks

da Silva Ruffo,

Lent,

Carvalho

et al. 2025

Future Generation Computer Systems

View full text Add to dashboard Cite

A Comprehensive Survey on Generative AI Solutions in IoT Security

López Delgado,

López Ramos

2024

Electronics

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The influence of Artificial Intelligence in our society is becoming important due to the possibility of carrying out analysis of the large amount of data that the increasing number of interconnected devices capture and send as well as making autonomous and instant decisions from the information that machines are now able to extract, saving time and efforts in some determined tasks, specially in the cyberspace. One of the key issues concerns security of this cyberspace that is controlled by machines, so the system can run properly. A particular situation, given the heterogeneous and special nature of the environment, is the case of IoT. The limited resources of some components in such a network and the distributed nature of the topology make these types of environments vulnerable to many different attacks and information leakages. The capability of Generative Artificial Intelligence to generate contents and to autonomously learn and predict situations can be very useful for making decisions automatically and instantly, significantly enhancing the security of IoT systems. Our aim in this work is to provide an overview of Generative Artificial Intelligence-based existing solutions for the very diverse set of security issues in IoT environments and to try to anticipate future research lines in the field to delve deeper.

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Recent endeavors in machine learning-powered intrusion detection systems for the Internet of Things

Cited by 2 publications

References 166 publications

Generative adversarial networks to detect intrusion and anomaly in IP flow-based networks

Generative adversarial networks to detect intrusion and anomaly in IP flow-based networks

A Comprehensive Survey on Generative AI Solutions in IoT Security

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