Faculty Publications
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Item A Hybrid Trust Management Scheme for Wireless Sensor Networks(Springer New York LLC barbara.b.bertram@gsk.com, 2017) Karthik, N.; Ananthanarayana, V.S.Wireless sensor network (WSN) consists of wireless small sensor nodes deployed in the terrain for continuous observation of physical or environmental conditions. The data collected from the WSN is used for making decisions. The condition for making critical decision is to assure the trustworthiness of the data generated from sensor nodes. However, the approaches for scoring the sensed data alone is not enough in WSN since there is an interdependency between node and data item. If the overall trust score of the network is based on one trust component, then the network might be misguided. In this work, we propose the hybrid approach to address the issue by assigning the trust score to data items and sensor nodes based on data quality and communication trust respectively. The proposed hybrid trust management scheme (HTMS) detects the data fault with the help of temporal and spatial correlations. The correlation metric and provenance data are used to score the sensed data. The data trust score is utilized for making decision. The communication trust and provenance data are used to evaluate the trust score of intermediate nodes and source node. If the data item is reliable enough to make critical decisions, a reward is given by means of adding trust score to the intermediate nodes and source node. A punishment is given by reducing the trust score of the source and intermediate nodes, if the data item is not reliable enough to make critical decisions. Result shows that the proposed HTMS detects the malicious, faulty, selfish node and untrustworthy data. © 2017, Springer Science+Business Media, LLC.Item Trust Based Data Gathering in Wireless Sensor Network(Springer New York LLC barbara.b.bertram@gsk.com, 2019) Karthik, N.; Ananthanarayana, V.S.Wireless sensor nodes have been successfully employed in various pervasive applications. In all pervasive applications, a gathering of sensor data from the environment is the main operation held in a sensor network, where sink node or base station gathers all generated data to do data analysis and decision making. The data generated by the sensor node in the pervasive environment should be transmitted to the sink node for data analysis and decision making. We strongly conceive that each process from perceiving the environment to decision making, demands trust based process to ease and ensure the trustworthy data exchange among trustworthy nodes such as trust-based data collection, trust-based data aggregation, trust-based data reconstruction and trust-based data analysis for decision making. In this work, we propose a Trust-based Data Gathering which focus on trust-based data collection, data aggregation, and data reconstruction to show that the absence of trust in a sensor-driven pervasive environment could affect the normal functionality of an application. Experimental results show that the proposed method achieves better performance in detecting data faults, malicious nodes and demonstrates that the absence of trust based process in data collection, data aggregation, and data reconstruction in harsh environment consumes more energy and delay for handling untrustworthy data, untrustworthy node and affects the normal functionality of the application. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.