Please use this identifier to cite or link to this item: http://103.65.197.75:8080/jspui/handle/123456789/309
Title: Secure user authentication mechanism for IoT-enabled Wireless Sensor Networks based on multiple Bloom filters
Authors: Maurya, Anup Kumar
Keywords: Wireless Sensor Networks (WSNs) Internet of Things (IoT) Bloom filter Fuzzy extractor User authentication Security
Issue Date: 2021
Publisher: Elsevier
Abstract: In this article, we propose an efficient Bloom filter and fuzzy extractor based user authentication technique, which is significant for an Internet of Things (IoT)-enabled multi-hop Wireless Sensor Networks (IoT-WSNs). The novelty of the proposed authentication technique is that it prevents fraudulent querying data delivery at the starting phase (i.e., at the querying sensor node itself) to stop false or counterfeit data flooding (which can exhaust the resources of IoT-WSNs) from the resource-constrained IoT-enabled sensor nodes to the nearby gateway node. The proposed authentication technique has the ability to significantly reduce the Bloom filter based false positive for user authentication in IoT-WSNs, while also preserving the constraint resources of WSNs. To estimate the security robustness of the proposed protocol based on the security goals of IoT-WSNs, we perform the formal security analysis using the random oracle and Real-Or-Random (ROR) models, informal security analysis and also the formal security verification using a widely-recognized automated software validation tool, known as Automated Validation of Internet Security Protocols and Applications (AVISPA). Next, communication and computational overheads analysis reveal that the proposed protocol is appropriate for resource-constrained sensor nodes. Furthermore, a correlative security feature and complexity analysis outcomes validate that the proposed protocol is reliable, secure, and efficient in comparison with other existing state of art related user authentication protocols.
URI: http://103.65.197.75:8080/jspui/handle/123456789/309
ISSN: 1383-7621
Appears in Collections:Journal Articles

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