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Anitha, A.
- Robust Tristate Security Mechanism to Protect Against Selective Forwarding Attack and Black Hole Attack in Intra-Cluster Multi-Hop Communication
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Authors
A. Anitha
1,
S. Mythili
2
Affiliations
1 Department of Computer Science, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu., IN
2 Department of Information Technology, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu., IN
1 Department of Computer Science, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu., IN
2 Department of Information Technology, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu., IN
Source
International Journal of Computer Networks and Applications, Vol 10, No 3 (2023), Pagination: 443-455Abstract
Security is the most vital issue to be addressed in Wireless Sensor Networks (WSNs). The WSN dominates since it has an effectiveness of applications in numerous fields. Though it has effectiveness towards its applications likewise it is susceptible to two different kinds of attacks (i.e.) external attacks and internal attacks existence of constrained reckoning resources, low memory, inadequate battery lifetime, handling control, and nonexistence of interfere resilient packet. Handle internal attacks such as selective forwarding attacks (SFAs) and black hole attacks (BHA) are considered to be the most common security extortions in wireless sensor networks. The attacker nodes will execute mischievous activities during data communication by creating traffic load, delaying packet delivery, dropping packets selectively or dropping all packets, energy consumption, and depleting all network resources. These attacks can be handled efficiently by implementing the proposed methodology for detecting, preventing, and recovering Cluster Heads (CHs), Cluster Members (CMs), and Transient Nodes (TNs) from SFAs and BHA in intra-cluster multi-hop. It is accomplished by proposing a robust strategy for overcoming internal attacks on cluster head, cluster member, and transient node. The Fuzzy C-Means clustering is used to discover the prominent cluster head. The uncertainty entropy model is used to detect internal attacks by removing the malicious node from the transition path. The intermediate node is been selected based on the degree and dimension. The experimental results of the proposed Robust Tristate Security Mechanism (RTSSM) against SFAs and BHA are evaluated with packet delivery ratio, throughput, and packet drop and the results prove the effectiveness of the proposed methodology and it also aids in the extension of the network lifetime.Keywords
Cluster Head, Cluster Member, Intra-Cluster, Multi-Hop, Clustering, Wireless Sensor Networks, Uncertainty, Robust, Fuzzy Membership, Entropy.Full Text
References
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Abstract Views :99 |
PDF Views:1
Authors
A. Anitha
1,
S. Mythili
2
Affiliations
1 Department of Computer Science, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu, IN
2 Department of Information Technology, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu, IN
1 Department of Computer Science, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu, IN
2 Department of Information Technology, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu, IN
Source
International Journal of Computer Networks and Applications, Vol 10, No 4 (2023), Pagination: 511-526Abstract
Each sensor node functions autonomously to conduct data transmission in wireless sensor networks. It is very essential to focus on energy dissipation and sensor nodes lifespan. There are many existing energy consumption models, and the problem of selecting optimized cluster head along with efficient path selection is still challenging. To address this energy consumption issue in an effective way the proposed work is designed with a two-phase model for performing cluster head selection, clustering, and optimized route selection for the secure transmission of data packets with reduced overhead. The scope of the proposed methodology is to choose the most prominent cluster head and assistant cluster head which aids in prolonging the network lifespan and also securing the inter-cluster components from selective forwarding attack (SFA) and black hole attack (BHA). The proposed methodology is Empowered Chicken Swarm Optimization (ECSO) with Intuitionistic Fuzzy Trust Model (IFTM) in Inter-Cluster communication. ECSO provides an efficient clustering technique and cluster head selection and IFTM provides a secure and fast routing path from SFA and BHA for Inter-Cluster Single-Hop and Multi-Hop Communication. ESCO uses chaos theory for local optima in cluster head selection. The IFTM incorporates reliance of neighbourhood nodes, derived confidence of nodes, estimation of data propagation of nodes and an element of trustworthiness of nodes are used to implement security in inter-cluster communication. Experimental results prove that the proposed methodology outperforms the existing approaches by increasing packet delivery ratio and throughput, and minimizing packet drop ratio and energy consumption.Keywords
Wireless Sensor Networks, Chicken Swarm Optimization, Intuitionistic Fuzzy Trust Model, Energy Aware, Security, Cluster Head, Clustering and Inter-Cluster Communication.Full Text
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