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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 | Rights: | © Springer Nature Switzerland AG 2021 This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-030-86130-8_49. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms. |
| Appears in Collections: | Conference Paper |
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| Li_Blackslist-Based_Packet_Filtration.pdf | Pre-Published version | 385.93 kB | Adobe PDF | View/Open |
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