TY - JOUR
T1 - Enhancing blockchain-based filtration mechanism via IPFS for collaborative intrusion detection in IoT networks
AU - Li, Wenjuan
AU - Wang, Yu
AU - Li, Jin
N1 - Funding Information:
This work was partially supported by National Natural Science Foundation of China (No. 62102106 ).
Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2022/6
Y1 - 2022/6
N2 - Internet of Things (IoT) has become more important for setting up a smart environment, e.g., smart home. It is a network of connected devices, which can provide many benefits such as automating and controlling the tasks on a daily basis without human intervention. While due to the dispersed structure, IoT networks are vulnerable to various attacks, e.g., Distributed Denial of Service (DDoS). To protect such environment, building a suitable collaborative intrusion detection network (CIDN) is essential by enabling the exchange of required data among nodes. In addition, deploying a packet filtration mechanism with CIDN is necessary to reduce unwanted events and traffic. However, how to safeguard the integrity of exchanged information is a challenge, because a malicious internal node can manipulate and deliver untruthful data. Motivated by the blockchain technology, in this work, we develop a blockchain-based filtration mechanism with CIDN to help protect the security of IoT networks by refining unexpected events. In addition, we leverage IPFS technology to host and share information like blacklist. In the evaluation, we examine the filter performance with three real datasets, a simulated environment and a practical environment, respectively. The results demonstrate the effectiveness and scalability of our filter compared with similar studies.
AB - Internet of Things (IoT) has become more important for setting up a smart environment, e.g., smart home. It is a network of connected devices, which can provide many benefits such as automating and controlling the tasks on a daily basis without human intervention. While due to the dispersed structure, IoT networks are vulnerable to various attacks, e.g., Distributed Denial of Service (DDoS). To protect such environment, building a suitable collaborative intrusion detection network (CIDN) is essential by enabling the exchange of required data among nodes. In addition, deploying a packet filtration mechanism with CIDN is necessary to reduce unwanted events and traffic. However, how to safeguard the integrity of exchanged information is a challenge, because a malicious internal node can manipulate and deliver untruthful data. Motivated by the blockchain technology, in this work, we develop a blockchain-based filtration mechanism with CIDN to help protect the security of IoT networks by refining unexpected events. In addition, we leverage IPFS technology to host and share information like blacklist. In the evaluation, we examine the filter performance with three real datasets, a simulated environment and a practical environment, respectively. The results demonstrate the effectiveness and scalability of our filter compared with similar studies.
KW - Blockchain technology
KW - Distributed Denial-Of-Service attack
KW - Internet of Things
KW - Intrusion detection
KW - Packet filtration
UR - http://www.scopus.com/inward/record.url?scp=85129593860&partnerID=8YFLogxK
U2 - 10.1016/j.sysarc.2022.102510
DO - 10.1016/j.sysarc.2022.102510
M3 - Journal article
AN - SCOPUS:85129593860
SN - 1383-7621
VL - 127
SP - 1
EP - 9
JO - Journal of Systems Architecture
JF - Journal of Systems Architecture
M1 - 102510
ER -