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Blockchain-based proof-of-authenticity frameworks for Explainable AI

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Abstract

Explainable Artificial Intelligence (XAI) model generates explanations that assist a regulator in tracing offenders responsible for failures and penalizing them accordingly. However, these explanations are traditionally stored in the central database and are hence susceptible to changes. The owner of an automated system intentionally forges the information and later denies the same to safeguard its company's reputation. Here, Blockchain technology can prove beneficial to the regulator in order to confirm the traceability, non-repudiation, and auditability of the records. Hence, the paper proposes a novel public Blockchain-based proof-of-authenticity framework (BXAI) to ensure traceability and auditability in XAI. The framework has been developed on the Ethereum Blockchain, Smart contract, and the Interplanetary File System (IPFS). Furthermore, we design a peer-to-peer network with a distributed database to incorporate another essential feature of Blockchain, i.e., queryability, and propose a novel Blockchain database-based framework (BdXAI). Lastly, to understand the use of both proposed frameworks based on the requirements and availability of resources, a detailed comparative analysis is presented on parameters like time taken, cost, and queryability. However, after analyzing, one can opt for either of the two Blockchain-based frameworks, depending on the user's needs and the availability of resources.

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Data availability statement

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Authors and Affiliations

  1. Computer Science and Engineering Department, Punjab Engineering College (Deemed to Be University), Chandigarh, India

    Diksha Malhotra & Poonam Saini

  2. Computer Engineering Department, National Institute of Technology, Kurukshetra, India

    Awadhesh Kumar Singh

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  1. Diksha Malhotra
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  2. Poonam Saini
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  3. Awadhesh Kumar Singh
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Correspondence to Diksha Malhotra.

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Malhotra, D., Saini, P. & Singh, A.K. Blockchain-based proof-of-authenticity frameworks for Explainable AI. Multimed Tools Appl 83, 37889–37911 (2024). https://doi.org/10.1007/s11042-023-16951-0

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