TY - JOUR
T1 - Intrusion detection system for the internet of things based on blockchain and multi-agent systems
AU - Liang, Chao
AU - Shanmugam, Bharanidharan
AU - Azam, Sami
AU - Karim, Asif
AU - Islam, Ashraful
AU - Zamani, Mazdak
AU - Kavianpour, Sanaz
AU - Idris, Norbik Bashah
PY - 2020/7/10
Y1 - 2020/7/10
N2 - With the popularity of Internet of Things (IoT) technology, the security of the IoT network has become an important issue. Traditional intrusion detection systems have their limitations when applied to the IoT network due to resource constraints and the complexity. This research focusses on the design, implementation and testing of an intrusion detection system which uses a hybrid placement strategy based on a multi-agent system, blockchain and deep learning algorithms. The system consists of the following modules: data collection, data management, analysis, and response. The National security lab–knowledge discovery and data mining NSL-KDD dataset is used to test the system. The results demonstrate the efficiency of deep learning algorithms when detecting attacks from the transport layer. The experiment indicates that deep learning algorithms are suitable for intrusion detection in IoT network environment.
AB - With the popularity of Internet of Things (IoT) technology, the security of the IoT network has become an important issue. Traditional intrusion detection systems have their limitations when applied to the IoT network due to resource constraints and the complexity. This research focusses on the design, implementation and testing of an intrusion detection system which uses a hybrid placement strategy based on a multi-agent system, blockchain and deep learning algorithms. The system consists of the following modules: data collection, data management, analysis, and response. The National security lab–knowledge discovery and data mining NSL-KDD dataset is used to test the system. The results demonstrate the efficiency of deep learning algorithms when detecting attacks from the transport layer. The experiment indicates that deep learning algorithms are suitable for intrusion detection in IoT network environment.
KW - Blockchain
KW - Internet of Things
KW - Intrusion detection system
KW - Multi-agent system
UR - http://www.scopus.com/inward/record.url?scp=85087904312&partnerID=8YFLogxK
U2 - 10.3390/electronics9071120
DO - 10.3390/electronics9071120
M3 - Article
AN - SCOPUS:85087904312
SN - 2079-9292
VL - 9
SP - 1
EP - 27
JO - Electronics (Switzerland)
JF - Electronics (Switzerland)
IS - 7
M1 - 1120
ER -