Threat‐Aware Mutual Authentication in Web3: A Privacy‐Preserving Framework With <scp>ZKP</scp> ‐ <scp>DID</scp> and Real‐Time <scp>GNN</scp> Integration

ABSTRACT Phishing attacks in decentralized Web3 systems continue to evolve beyond the detection capabilities of traditional Web2 security models. Existing decentralized authentication systems typically lack either mutual verification or dynamic threat awareness. We present PhishGuard++, a cross‐chain, privacy‐preserving authentication framework that introduces two core innovations: (1) a novel mutual Zero‐Knowledge Proof (ZKP) protocol that validates both users and services using Decentralized Identifiers (DIDs), and (2) a real‐time, on‐chain Graph Neural Network (GNN) threat oracle that assigns phishing risk scores integrated directly into smart contract‐based access control logic. A stake‐based validator reputation system with anti‐collusion incentives further reinforces trust without sacrificing decentralization or privacy. Experimental results on a simulated Arbitrum testnet show a statistically significant 40.4% reduction in phishing success rate across five attack vectors, 98.6% authentication accuracy, and sub‐second latency with gas‐efficient operations. Unlike prior works that independently apply ZKPs, DIDs, or GNNs, this framework offers the first privacy‐preserving, mutual authentication system that combines these technologies with stake‐based economic enforcement and real‐time smart contract enforcement. The novelty lies in the architecture's real‐time threat‐aware access decisions, validator‐linked risk accountability, and practical cross‐chain deployment—an integration not previously achieved.

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Publication Details

Journal
Security and Privacy
Published
2025-12-17
DOI
https://doi.org/10.1002/spy2.70146
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
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article

Threat‐Aware Mutual Authentication in Web3: A Privacy‐Preserving Framework With ZKP ‐ DID and Real‐Time GNN Integration

S. Karuppusamy, Ruth Ramya Kalangi
Security and Privacy
Spam and Phishing Detection
article

Threat‐Aware Mutual Authentication in Web3: A Privacy‐Preserving Framework With ZKP ‐ DID and Real‐Time GNN Integration

S. Karuppusamy, Ruth Ramya Kalangi
article en

Abstract

ABSTRACT Phishing attacks in decentralized Web3 systems continue to evolve beyond the detection capabilities of traditional Web2 security models. Existing decentralized authentication systems typically lack either mutual verification or dynamic threat awareness. We present PhishGuard++, a cross‐chain, privacy‐preserving authentication framework that introduces two core innovations: (1) a novel mutual Zero‐Knowledge Proof (ZKP) protocol that validates both users and services using Decentralized Identifiers (DIDs), and (2) a real‐time, on‐chain Graph Neural Network (GNN) threat oracle that assigns phishing risk scores integrated directly into smart contract‐based access control logic. A stake‐based validator reputation system with anti‐collusion incentives further reinforces trust without sacrificing decentralization or privacy. Experimental results on a simulated Arbitrum testnet show a statistically significant 40.4% reduction in phishing success rate across five attack vectors, 98.6% authentication accuracy, and sub‐second latency with gas‐efficient operations. Unlike prior works that independently apply ZKPs, DIDs, or GNNs, this framework offers the first privacy‐preserving, mutual authentication system that combines these technologies with stake‐based economic enforcement and real‐time smart contract enforcement. The novelty lies in the architecture's real‐time threat‐aware access decisions, validator‐linked risk accountability, and practical cross‐chain deployment—an integration not previously achieved.

Security and PrivacyVol. 9(1)
Excel Life Sciences (India) (IN)
Openalex Percentile: Top 47%
Spam and Phishing Detection
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