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Detection of Sybil Attacks and their Countermeasures in Cluster-based LEACH Protocol - Student Mian Ahmad Jan

Project Member(s): Nanda, P., He, X.

Funding or Partner Organisation: Commonwealth Scientific and Industrial Research Organisation (CSIRO ICT Scholarship Fund)

Start year: 2013

Summary: LEACH (Low-Energy Adaptive Clustering Hierarchical) is a self-organizing, adaptive clustering protocol that uses randomization to distribute the energy load evenly among the sensors in the network. Like any protocol, LEACH is vulnerable to various threats. In Sybil attack, a malicious device illegitimately takes on multiple identities. Malicious device┬┐s additional identities are known as Sybil nodes. In this project, we will explore various forms of Sybil attacks and how to combat them by proposing various solutions based on simulation and also building a prototype with sensor nodes to validate our proposed scheme. In our proposed solution, we will detect malicious nodes (both fixed and mobile) based on various factors and prevent them from injecting malicious code and fabricated data into the clusters.

Publications:

Usman, M, Jan, MA, He, X & Alam, M 2018, 'Performance evaluation of High Definition video streaming over Mobile Ad Hoc Networks', Signal Processing, vol. 148, pp. 303-313.
View/Download from: UTS OPUS or Publisher's site

Jan, M, Nanda, P, Usman, M & He, X 2017, 'PAWN: A Payload-based mutual Authentication scheme for Wireless Sensor Networks', Concurrency and Computation: Practice and Experience, vol. 29, no. 17.
View/Download from: UTS OPUS or Publisher's site

Tan, Z, Nagar, U, He, X, Nanda, P & Liu, R 2014, 'Enhancing Big Data Security with Collaborative Intrusion Detection', IEEE Cloud Computing Magazine, pp. 34-40.
View/Download from: UTS OPUS

Keywords: LEACH (Low-Energy Adaptive Clustering Hierarchical), Sybil attack, Wireless Sensor Network (WSN),

FOR Codes: Computer Communications Networks, Wireless Communications, Communication not elsewhere classified, Energy Conservation and Efficiency not elsewhere classified