Abstract:
In addressing the ever-evolving demands of public cloud security, there arises an imperative need for innovative and
robust blockchain models. Traditional approaches often grapple with limitations such as vulnerability to attacks, inefficiencies,
delay, energy consumption, suboptimal throughput and packet delivery metrics. This paper introduces a ground breaking
iterative and highly secure bioinspired based sharding blockchain model, tailored for public cloud deployments, which
fundamentally challenges these constraints. The cornerstone of our proposed model is the integration of public blockchain with
a novel proof of iterative trust (POIT) mechanism. This integration is pivotable in fortifying system resilience against spectrum
of cyber threats. Additionally, the implementation of sharding, a process critical for scalability is ingeniously executed using
teacher learner-based ant-lion optimizer (TLALO). The method not only significantly diminishes delay but also substantially
enhances the energy efficiency of the system. The rationale behind employing TLALO lies in its bioinspired algorithms, which
mimic natural processes to optimize complex systems. The model superiority is further evidenced by rigorous testing across
various clod platforms, including Apache cloud, Amazon cloud, Google cloud. The model demonstrates 10.5% reduction in
delay,8.5% decrease in energy consumption,5.4% increase in throughput,5.9%improvement in packet delivery ratio compared
to existing methods. Moreover,3.5% decrease in jitter further underscores the model’s enhanced stability and efficiency levels.
