TY - GEN
T1 - Enhancing Blackslist-Based Packet Filtration Using Blockchain in Wireless Sensor Networks
AU - Li, Wenjuan
AU - Meng, Weizhi
AU - Wang, Yu
AU - Li, Jin
N1 - Funding Information:
Acknowledgment. This work was partially supported by National Natural Science Foundation of China (No. 61802080 and 61802077), and Guangzhou University Research Project (No. RQ2020085 and RD2020076).
Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021/6
Y1 - 2021/6
N2 - A wireless sensor network (WSN) consists of distributed sensors for monitoring network status and recording data, which is playing a major role in Internet of Things (IoT). This type of wireless network is driven by the availability of inexpensive and low-powered components. However, WSN is vulnerable to many kinds of attacks like Distributed Denial of Service (DDoS) due to its dispersed structure and unreliable transmission. In the literature, constructing a suitable distributed packet filter is a promising solution to help mitigate unwanted traffic. While how to ensure the integrity of exchanged data is a challenge as malicious internal node can share manipulated data to degrade the effectiveness of filtration. In this work, we design a blockchain-based blacklist packet filter with collaborative intrusion detection that can be deployed in WSNs. The blockchain technology is used to help build a robust blacklist for reducing unwanted traffic. In the evaluation, we investigate the performance of our filter with a real dataset and in a practical WSN environment. The results demonstrate that our proposed filter can enhance the robustness of blacklist generation.
AB - A wireless sensor network (WSN) consists of distributed sensors for monitoring network status and recording data, which is playing a major role in Internet of Things (IoT). This type of wireless network is driven by the availability of inexpensive and low-powered components. However, WSN is vulnerable to many kinds of attacks like Distributed Denial of Service (DDoS) due to its dispersed structure and unreliable transmission. In the literature, constructing a suitable distributed packet filter is a promising solution to help mitigate unwanted traffic. While how to ensure the integrity of exchanged data is a challenge as malicious internal node can share manipulated data to degrade the effectiveness of filtration. In this work, we design a blockchain-based blacklist packet filter with collaborative intrusion detection that can be deployed in WSNs. The blockchain technology is used to help build a robust blacklist for reducing unwanted traffic. In the evaluation, we investigate the performance of our filter with a real dataset and in a practical WSN environment. The results demonstrate that our proposed filter can enhance the robustness of blacklist generation.
KW - Blockchain technology
KW - Distributed denial-of-service attack
KW - Network security
KW - Packet filtration
KW - Wireless sensor network
UR - http://www.scopus.com/inward/record.url?scp=85115734475&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-86130-8_49
DO - 10.1007/978-3-030-86130-8_49
M3 - Conference article published in proceeding or book
AN - SCOPUS:85115734475
SN - 9783030861292
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 624
EP - 635
BT - Wireless Algorithms, Systems, and Applications - 16th International Conference, WASA 2021, Proceedings
A2 - Liu, Zhe
A2 - Wu, Fan
A2 - Das, Sajal K.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 16th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2021
Y2 - 25 June 2021 through 27 June 2021
ER -