Authors:
G. Chiranjeevi, R. Abhishek Reddy, R. Shyam, Swati Sah, Rejwan Bin Sulaiman

Addresses:
Department of Computer Science/Information Technology, Jain (Deemed-to-be University), Bengaluru, Karnataka, India. Department of Computer Science/Information Technology, Presidency College, Kempapura, Bengaluru, Karnataka, India.  School of Engineering and Technology, Sharda University, Greater Noida, Uttar Pradesh, India. Department of Computer Science and Technology, Northumbria University, London, United Kingdom.                               

Abstract:

Decentralized solutions, widely adopted across industries like banking, health- care, and logistics, face persistent security concerns from potential threats. This study introduces a novel decentralized vulnerability assessment using GPT-3, an artificial intelligence (AI) technology. Employing Dockerized containers for disinfecting environments and creating unique connections to the AI API service enhances system responsiveness. AI algorithms, specifically GPT-3, conduct comprehensive network scans to identify security flaws. Findings are securely distributed to network nodes, fortifying the system’s defence. This departure from centralized control and traditional security audits marks a significant advancement in securing decentralized systems. AI-enabled real-time monitoring facilitates swift responses to security issues, reducing breach risks and aiding effective resource management. Encouraging results from controlled system analysis, focusing on GPT-3 vulnerabilities, highlight the integration of Dockerized containers for enhanced system efficiency. This work lays the foundation for further research, emphasizing the potential of decentralized systems for rigorous security assessments.

Keywords: Decentralization and Scalability; REST API; Artificial Intelligence (AI); Enumeration and Vulnerability Analysis; Peer-To-Peer; Information Security; Generative Pre-trained Transformer 3 (GPT-3); Load Balancing.

Received on: 07/06/2024, Revised on: 11/08/2024, Accepted on: 04/10/2024, Published on: 14/12/2024

DOI: 10.69888/FTSIN.2024.000290

FMDB Transactions on Sustainable Intelligent Networks, 2024 Vol. 1 No. 4, Pages: 220-241

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