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Tripathi, Khushboo, Singh, Shalu, Kaushik, Sheetal, Vyas, Shubham, Khan, Mohd Anas and Ahmadian, Ali (2026) TITAN: logarithm-based trust-aware integrated technique for robust anomaly neutralization in industrial WSNs. Peer-to-Peer Networking and Applications, 19 (3) (79): 79. pp. 1-35. ISSN 1936-6450
Trust between sensor nodes is very essential to improve security, dependability, energy efficiency, scalability, and cooperation in Industrial Wireless Sensor Networks (IWSNs). In order to enhance cooperation and security on a large scale in IWSNs, we suggest a Trust-based Integrated Techniques for Anomaly Neutralization (TITAN), where unequal clustering can be used to detect and shrink unacceptable sensor nodes and save resources. Disparate strategic clustering helps in boosting energy efficiency through the creation of smaller clusters close to the sink and larger ones at the distances, therefore encouraging the more tolerable distribution of power and communication encumbrance. Heads of the clusters are dynamically selected depending on the fitness of the nodes within the cluster through a new Optimal Cluster Representative Election Algorithm (OCREA). The fitness of a node is based on its residual power, connection quality, signal strength and distance to the sink. TITAN applies distributed intra-cluster trust to make decisions combining with centralized inter-cluster methodologies, merging attack-resistant trust evaluations and effective trust aggregation. In addition, TITAN applies an appealing dynamic logarithmic trust fund distribution of rewards and sanctions based on the actions of sensor nodes, it is possible to distinguish between reliable and faulty nodes. Also, it includes key indicators of communication trust, data trust, and energy measurement to allow proper trust measurement. TITAN considers a dynamic aging factor and damping factor, which ensures that reliability of sensor nodes is considered on account of recent exchanges, and, therefore, minimizing the influence of old information. To a larger extent, the model incorporates a logarithmic penalty term that punishes the node when the rate of unsuccessful interactions goes up hence effectively isolating with untrustworthy nodes. TITAN enhances better and reliable and robust trust assessment as it incorporates feedback provided by trustworthy neighbor’s nodes and the manipulation of trust levels using an extensive analysis. The combination of these features contributes to the overall performance and improves it’s security of IWSNs, which enables them to be better resistant to attacks and use less resource to run in resource-constrained environments. Due to its communication overhead, trust evaluation and detected malicious nodes, the solution proposed is superior in its capabilities compared to other solutions authenticated with extensive simulations. TITAN manages to recognize the presence of the malicious nodes with 87 percent even when the malicious nodes are less than 60 percent, meaningfully better than such comparative models as SDTS and DTMS. The positive error rate and the negative error rate is minimized with a precision in detection increased to 9% and 6% respectively. TITAN also maintains high packets delivery ratio of above 89% and reduced the average packet loss to only 36 as compared to more than 60 in the baseline schemes. Also, the energy consumption is lowered by about 14% that confirms the effectiveness of TITAN. These findings all indicate the strength and scalability of TITAN Energy-constrained environment performance and threat-prone IWSN environments performance.
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0.
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