Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/91606
Title: Enhancing blackslist-based packet filtration using blockchain in wireless sensor networks
Authors: Li, WJ 
Meng, WZ
Wang, Y
Li, J
Issue Date: 2021
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2021, v. 12938 LNCS, p. 624-635
Abstract: 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.
Keywords: Wireless sensor network
Distributed denial-of-service attack
Blockchain technology
Network security
Packet filtration
Publisher: Springer
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-030-86130-8_49
Description: International Conference on Wireless Algorithms, Systems, and Applications (WASA 2021), 25-27 June 2021, Nanjing, China
Appears in Collections:Conference Paper

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