Earticle

초록

영어

Bringing together artificial intelligence (AI) and blockchain technology in the NFT space has not only changed the overall idea of digital ownership but also opened up new avenues for content authentication, asset management, and smart contract-based management through automation. The expansion of this technology, however, also brought security issues to the fore. Among these concerns are side-channel leakage, identity spoofing, and man-in-the-middle (MitM) attacks. This work proposes a detailed AI-supported NFT security framework that brings together three main technologies: X.509 Certificate Validation, CacheShield, and Context-Based Node Acceptance (CBNA), forming a system that is secure, private, and trusted. The X.509 system fights against replay and impersonation attacks by authenticating blockchain nodes and users, and also TransCert validation. CacheShield blocks the leakage of confidential information by determining the cache contention using K-Means clustering and hardware performance counters, while the CBNA algorithm (Random Forest Classifier) keeps secure connections in the SDN network by detecting malicious nodes. The outcomes revealed that the system significantly boosts performance in terms of accuracy, authentication latency, and tolerance of attacks. This framework not only fortifies the trust and security of decentralized AI-NFT applications but also opens the door to quantum-safe and context-aware blockchain systems in the future.

목차

Abstract
I. INTRODUCTION
II. USE RELATED WORK
III. PROPOSED FRAMEWORK
A. Architecture Overview
B. X.509 Certificate Validation
C. CacheShield-Based Protection
D. CBNA Algorithm for Node Validation
IV. IMPLEMENTATION & EVALUATION
A. Experimental Setup
B. Results Summary (Placeholder)
V. DISCUSSION
VI. CONCLUSION
REFERENCES

키워드

저자

• Misbah Noor [ Faculty of Languages and Communication Universiti Sultan Zainal Abidin (UniSZA), Kuala Trengganu, Malaysia ]
• Muhammad Akram [ Faculty of computer science and IT, Superior University Lahore Pakistan ]
• Muhammad Waseem Iqbal [ Department of Computer Science and IT, Superior University Lahore, 54000, Pakistan ]
• Md Tanvir Islam [ Department of Computer Science and Engineering Kyunkpook National University, Daegu, 41566, Republic of Korea ]
• Muhammad Tayyab Khan [ Department of Computer Science, National College of Business Administration & Economics Lahore, Pakistan ]
• Muhammad Adnan Khan [ Department of Software, Faculty of AI & Software, Seongnam-si, Republic of Korea. ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004