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The Journal of Supercomputing
Erschienen in: The Journal of Supercomputing 10/2018

19.05.2018

NBC-MAIDS: Naïve Bayesian classification technique in multi-agent system-enriched IDS for securing IoT against DDoS attacks

verfasst von: Amjad Mehmood, Mithun Mukherjee, Syed Hassan Ahmed, Houbing Song, Khalid Mahmood Malik

Erschienen in: The Journal of Supercomputing | Ausgabe 10/2018

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Abstract

Internet of Things (IoT) makes physical objects and devices interact with each other through wireless technologies. IoT is expected to deliver a significant role in our lives in near future. However, at the current stage, IoT is vulnerable to various kinds of security threats just like other wired and wireless networks. Our work mainly focuses on protecting an IoT infrastructure from distributed denial-of-service attacks generated by the intruders. We present a new approach of using Naïve Bayes classification algorithm applied in intrusion detection systems (IDSs). IDSs are deployed in the form of multi-agents throughout the network to sense the misbehaving or irregular traffic and actions of nodes. In the paper, we also discuss the fundamental concepts related to our work and recent research done in similar area.
Vorheriger Artikel An efficient approach for publishing microdata for multiple sensitive attributes
Nächster Artikel A security review of local government using NIST CSF: a case study

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Fußnoten
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Metadaten
Titel
NBC-MAIDS: Naïve Bayesian classification technique in multi-agent system-enriched IDS for securing IoT against DDoS attacks
verfasst von
Amjad Mehmood
Mithun Mukherjee
Syed Hassan Ahmed
Houbing Song
Khalid Mahmood Malik
Publikationsdatum
19.05.2018
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 10/2018
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-018-2413-7

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