AI-Based Blockchain Consensus for Real-Time Security Policy Enforcement in Containerized Environments

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@article{1702287,
      author = {Deepak Kaul},
      title = {AI-Based Blockchain Consensus for Real-Time Security Policy Enforcement in Containerized Environments},
      journal = {Iconic Research And Engineering Journals},
      year = {2020},
      volume = {3},
      number = {11},
      pages = {327-340},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1702287.pdf},
      abstract = {Docker or Kubernetes leading toward the containerized environment based on the microservices? architecture, flexibility, scalability and portability have emerged as the new-age application deployment systems. However, the distributed nature of these systems brings about a variety of managerial security issues such as system policy, protection tamper, and dynamic threat changes. Conventionally, systems? security models that have been proffered for application pose great difficulties in handling these challenges; these frameworks base their security strategies on prescribed configurations that are rigid, and centralized enforcement points that present easy targets for hackers. 
This paper introduces a novelty disruptive approach that proposes to combine AI with blockchain-based consensus systems to enforce real-time security policies in the containerized environments. AI models are used to monitor runtime behavior to create dynamic security policies for threats arising from the dynamic environment. These policies are then retrieved and placed on a blockchain network, harnessing the system?s distributed and secure nature to guarantee the inviolable dissemination and implementation of specific container clusters. 
The proposed solution achieves a dual objective: First, policy dynamism and adaptability leveraging AI mechanisms and, second, policy trust-minimization and trust-reconstruction through blockchain technology. This approach reduces chances of a single failure point, increases operation system?s reliability as well as develop a robust defense mechanism which can grow in proportion to the containerized system. 
Using simulation and analysis, the framework shows that the proposed work provides better security policies accuracy, lower enforcement latency, and is less vulnerable to tampering. These results demonstrate its possibility as a revolutionary solution for protecting novel, containerized environments and provide valuable knowledge for future and current investigation in both academic and business settings. 
The outcomes of this research are significant and would be useful in the domains of cybersecurity, blockchain, and AI to establish a typical foundation for a smarter and more secure security framework across distributed structures.},
      month = {May},
  }