Authors : Sohail Sayed; Nauman Sayed

Volume/Issue : Volume 11 - 2026, Issue 8 - August

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Google Scholar : https://tinyurl.com/2kdt75km

DOI : https://doi.org/10.38124/ijisrt/26aug1100

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

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Abstract : Global supply chains are increasingly exposed to disruptions whose effects propagate across organizational boundaries, yet the data needed to predict such risks is fragmented among firms reluctant to share it for competitive, contractual, and regulatory reasons. Centralized machine learning therefore under-utilizes collective evidence, and organizations with inadequate datasets cannot predict risk reliably on their own [1].

Keywords : Federated Learning, Differential Privacy, Homomorphic Encryption, Secure Aggregation, Supply Chain Risk Management, Supply Chain Resilience, Collaborative AI.

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