Internet of things security: A multi-agent-based defense system design

The increasing Internet of Things (IoT) network complexity and sophisticated Distributed Denial of Service (DDoS) attacks at machine speeds make accurate and timely detection and mitigation of these attacks a challenging activity. This study presents a multi-agent-based system design (MAS-IoT) against DDoS attacks in the IoT network. The MAS-IoT consists of different types of agents which communicate using Advanced Encryption Standard (AES). In the context of the study, DDoS attacks were detected using a long-short-term memory (LSTM)-based model (LSTMIoT) developed based on the CIC-IoT-2022 dataset with a 99.48% accuracy rate. The detection time of the LSTM-IoT and its time complexity were calculated and compared using similar methods mentioned in the literature. The results demonstrate the effectiveness of the LSTM-IoT in accurately detecting DDoS attacks. However, the ability to use it effectively and on time is vital to counter real-time attacks. The MAS-IoT system enables this with minimum human intervention.

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Eser Adı
(dc.title)
Internet of things security: A multi-agent-based defense system design
Yazar
(dc.contributor.author)
Hakan Aydın
Yayın Yılı
(dc.date.issued)
2023
Tür
(dc.type)
Makale
Özet
(dc.description.abstract)
The increasing Internet of Things (IoT) network complexity and sophisticated Distributed Denial of Service (DDoS) attacks at machine speeds make accurate and timely detection and mitigation of these attacks a challenging activity. This study presents a multi-agent-based system design (MAS-IoT) against DDoS attacks in the IoT network. The MAS-IoT consists of different types of agents which communicate using Advanced Encryption Standard (AES). In the context of the study, DDoS attacks were detected using a long-short-term memory (LSTM)-based model (LSTMIoT) developed based on the CIC-IoT-2022 dataset with a 99.48% accuracy rate. The detection time of the LSTM-IoT and its time complexity were calculated and compared using similar methods mentioned in the literature. The results demonstrate the effectiveness of the LSTM-IoT in accurately detecting DDoS attacks. However, the ability to use it effectively and on time is vital to counter real-time attacks. The MAS-IoT system enables this with minimum human intervention.
Açık Erişim Tarihi
(dc.date.available)
2023-10-04
Yayıncı
(dc.publisher)
Pergamon-Elsevier Science Ltd
Dil
(dc.language.iso)
En
Konu Başlıkları
(dc.subject)
Internet of things
Konu Başlıkları
(dc.subject)
Encryption
Konu Başlıkları
(dc.subject)
Agents
Konu Başlıkları
(dc.subject)
Distributed denial of service
Konu Başlıkları
(dc.subject)
Network security
Tek Biçim Adres
(dc.identifier.uri)
https://hdl.handle.net/20.500.14081/1948
ISSN
(dc.identifier.issn)
0045-7906
Dergi
(dc.relation.journal)
Computers & Electrıcal Engıneerıng
Esere Katkı Sağlayan
(dc.contributor.other)
Aydin, Hakan
Esere Katkı Sağlayan
(dc.contributor.other)
Aydin, Muhammed Ali
Esere Katkı Sağlayan
(dc.contributor.other)
Sertbas, Ahmet
Esere Katkı Sağlayan
(dc.contributor.other)
Aydin, Gulsum Zeynep Gurkas
DOI
(dc.identifier.doi)
10.1016/j.compeleceng.2023.108961
Orcid
(dc.identifier.orcid)
0000-0002-0122-8512
Dergi Cilt
(dc.identifier.volume)
111
wosquality
(dc.identifier.wosquality)
Q2
wosauthorid
(dc.contributor.wosauthorid)
ADD-2495-2022
Department
(dc.contributor.department)
Bilgisayar Mühendisliği (İngilizce)
Wos No
(dc.identifier.wos)
WOS:001149530600001
Veritabanları
(dc.source.platform)
Wos
Veritabanları
(dc.source.platform)
Scopus
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