Enhancing Blackslist-Based Packet Filtration Using Blockchain in Wireless Sensor Networks

Wenjuan Li, Weizhi Meng, Yu Wang*, Jin Li

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


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.

Original languageEnglish
Title of host publicationWireless Algorithms, Systems, and Applications
EditorsZhe Liu, Fan Wu, Sajal K. Das
Publication date2021
ISBN (Print)9783030861292
Publication statusPublished - 2021
Event16th International Conference on Wireless Algorithms, Systems, and Applications - Nanjing, China
Duration: 25 Jun 202127 Jun 2021


Conference16th International Conference on Wireless Algorithms, Systems, and Applications
SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12938 LNCS

Bibliographical note

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.


  • Blockchain technology
  • Distributed denial-of-service attack
  • Network security
  • Packet filtration
  • Wireless sensor network


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