UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 3 | March 2026

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Volume 13 Issue 3
March-2026
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2603206


Registration ID:
577010

Page Number

c28-c36

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Title

Quantum-Resistance AI Web3 Threat Firewall Multi-Chain Security With Intelligent Detection

Abstract

The rapid progress in quantum computing poses a severe risk to contemporary blockchain systems, as their reliance on vulnerable primitives like ECDSA and RSA allows quantum algorithms (e.g., Shor's) to break discrete logarithm and factorization problems, potentially enabling attackers to forge signatures, steal assets, impersonate users, and compromise ledger immutability—undermining the core trust model of decentralized finance and Web3 applications.To preempt this crisis, we propose a next-generation quantum-resistant multicchain blockchain architecture fused with an intelligent AI-powered Web3 threat firewall. The framework natively adopts NIST-approved post-quantum cryptography, integrating lattice-based ML-DSA (Dilithium) and hash-based SLH-DSA (SPHINCS+) schemes throughout the protocol stack: from secure key-pair generation in wallets, through transaction signing, to rigorous multi-node verification during consensus. This design ensures end-to-end protection against foreseeable quantum threats across diverse chains without requiring disruptive hard forks or retrofits.Comprehensive testnet experiments quantify the trade-offs: post-quantum signatures incur larger payload sizes (typically 2–4× compared to ECDSA) and modestly increased signing/verification times, yet the overall transaction processing capacity remains practical for everyday use, with throughput and latency suitable for high-volume decentralized applications. Storage and bandwidth overheads stay manageable through optimized encoding and pruning techniques.Augmenting cryptographic hardening, the AI threat firewall leverages machine learning models to perform real-time anomaly detection across multichain interactions, identifying subtle signature irregularities, suspicious patterns, and novel attack vectors—including those exploiting transitional quantum vulnerabilities—thereby providing adaptive, proactive defense beyond static primitives.These findings confirm that fully quantum-secure blockchain systems are deployable today with acceptable performance penalties, paving the way for resilient, future-proof Web3 infrastructure capable of withstanding the quantum era while preserving usability, scalability, and economic viability for global adoption.

Key Words

Quantum Computing, Post-Quantum Cryptography, Blockchain Security, AI-based Threat Detection, Web3 Security, Multichain Architecture.

Cite This Article

"Quantum-Resistance AI Web3 Threat Firewall Multi-Chain Security With Intelligent Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 3, page no.c28-c36, March-2026, Available :http://www.jetir.org/papers/JETIR2603206.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Quantum-Resistance AI Web3 Threat Firewall Multi-Chain Security With Intelligent Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 3, page no. ppc28-c36, March-2026, Available at : http://www.jetir.org/papers/JETIR2603206.pdf

Publication Details

Published Paper ID: JETIR2603206
Registration ID: 577010
Published In: Volume 13 | Issue 3 | Year March-2026
DOI (Digital Object Identifier):
Page No: c28-c36
Country: Yadadri Bhuvanagiri, Telangana, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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