Decentralised Self-Sovereign Identity (SSI) for Secure Employee Credentialing and Fraud Prevention in AI-Driven Talent Acquisition: A Conceptual Framework and System Architecture

Abstract

The rapid digitisation of human resource management (HRM) has accelerated the adoption of automated talent acquisition systems. However, this transition has also facilitated an unprecedented rise in curriculum vitae (CV) fraud, including credential falsification and employment history padding, which imposes severe financial and reputational liabilities on organisations. Traditional background screening processes are slow, costly, and heavily reliant on centralised third-party verification agencies. To address these challenges, this paper proposes a decentralised Self-Sovereign Identity (SSI) framework for secure employee credentialing and fraud prevention in talent acquisition. Adopting a conceptual framework and systems architecture methodology, and informed by a systematic analysis of 28 core research papers on blockchain, decentralised identity, and macro decentralised in HRM, we design a four-layer architecture. The proposed model successfully resolves the privacy-immutability paradox under the General Data Protection Regulation (GDPR) by storing Verifiable Credentials (VCs) and Decentralised Identifiers (DIDs) in user-controlled wallets while anchoring only cryptographic proofs on a public-permissioned blockchain. Our findings demonstrate that this framework eliminates resume fraud at the point of intake, reduces credential verification latency from weeks to seconds, and provides tamper-proof, structured data inputs that mitigate the 'garbage-in, garbage-out' risk in downstream machine learning applicant tracking systems. Ultimately, this research offers an operational roadmap for secure, privacy-preserving, and highly efficient digital recruitment ecosystems.