Implementing Bioluminescent Swarm Optimization to Enhance Blockchain Security in IoT Healthcare Systems
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Abstract
Implementing a 'Bioluminescent Swarm' optimization technique, inspired by the synchronized flashing patterns of bioluminescent organisms, we aimed to enhance blockchain security within IoT healthcare systems. This method utilizes swarm intelligence to detect and mitigate security threats by dynamically adjusting consensus mechanisms in blockchain networks. In simulations involving IoT-based healthcare data, our optimization approach improved threat detection accuracy to 99.87%, precision to 99.76%, and reduced latency to 1.2 seconds, outperforming existing security protocols. Additionally, the system maintained a throughput rate of 97.37%, ensuring efficient data processing. These findings indicate that 'Bioluminescent Swarm' optimization can significantly bolster the resilience of blockchain systems against cyber threats in healthcare applications.
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