IBSBMPC: Design of an Iterative & highly Secure Bioinspired-based Sharding Blockchain Model for Public Cloud Deployments

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 in delay and energy consumption, and suboptimal throughput and packet delivery metrics. This paper introduces a groundbreaking 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 a Public Blockchain with a novel Proof of an iterative Trust (PoIT) mechanism. This integration is pivotal in fortifying the system's resilience against a spectrum of cyber threats. Additionally, the implementation of sharding, a process critical for scalability, is ingeniously executed using the Teacher Learner-based ant Lion an optimizer (TLALO). This method not only significantly diminishes delay but also substantially enhances the energy efficiency of the system sets. The rationale behind employing TLALO lies in its bioinspired algorithms, which mimic natural processes to optimize complex systems. This approach proves to be more effective compared to traditional methods, especially in a blockchain context where delay and energy performance are crucial metrics. The model's superiority is further evidenced by rigorous testing across various cloud platforms, including Apache Cloud, Amazon Cloud, and Google Cloud. The results are compelling – the model demonstrates a 10.5% reduction in delay, an 8.5% decrease in energy consumption, a 5.4% increase in throughput, and ana 5.9% improvement in packet delivery ratio, compared to existing methods. Moreover, a 3.5% decrease in jitter further underscores the model's enhanced stability and efficiency levels.