Agentic AI powered Cryptographic Blockchain for Secured Data Aggregation in WSN

MOHANAPRIYA D; SARAVANAN V

doi:10.36948/ijfmr.2026.v08i02.72774

Agentic AI powered Cryptographic Blockchain for Secured Data Aggregation in WSN

Author(s)	Ms. MOHANAPRIYA D, Dr. SARAVANAN V
Country	India
Abstract	Wireless sensor network (WSN) comprises of randomly distributed sensor nodes for sensing and collecting the information in a particular region and transmit to the base station (BS). Due to increasing large volume of data generated, secured data aggregation process is used to protect data aggregation process with higher communication efficiency. Many classification and existing methods were introduced for performing efficient and secured data aggregation in WSN. However it faced significant challenges to achieve the higher confidentiality and integrity in wireless communication system. In order to address these issues, a novel Agentic AI Powered Cryptographic Hash Blockchain (AAIPCHB) method is introduced for secure data aggregation in WSN. The main aim of AAIPCHB method is to perform secure data aggregation with higher data confidentiality and integrity. The AAIPCHB method includes two major processes namely node classification and secure data aggregation. First, the number of sensor nodes is collected as an input. After that, Agentic AI technique is employed for classifying the sensor nodes as normal nodes or intruders based on energy and trust value and signal strength. After the classification process, the data packets are collected from the normal nodes. Then, Koorde Cryptographic hash Blockchain is used to perform the secure transaction from sensor node to the base station. Koorde Cryptographic hash function generates the hash value for every sensor node data packets using Davies–Meyer compression function for preserving the data from the illegal access. This guarantees the integrity during the data aggregation in WSN. Experimental evaluation is carried out for factors such as classification accuracy, data confidentiality, integrity rate, Packet delivery ratio, data aggregation delay and throughput with respect to number of data packets and sensor nodes. Performance comparison analyses illustrate that the proposed AAIPCHB method improves the classification accuracy, throughput, data confidentiality, integrity rate, packet delivery ratio and minimizes the data aggregation delay.
Keywords	Keywords: WSN, secure data aggregation, resource optimization, Agentic AI, Koorde Cryptographic hash Blockchain, Davies–Meyer compression function
Field	Computer > Network / Security
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-03-29
DOI	https://doi.org/10.36948/ijfmr.2026.v08i02.72774

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Agentic AI powered Cryptographic Blockchain for Secured Data Aggregation in WSN

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