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Blockchain for AI: Smarter Contracts to Secure Artificial Intelligence Algorithms

In this dissertation, I investigate the existing smart contract problems that limit cognitive abilities. I use Taylor's serious expansion, polynomial equation, and fraction-based computations to overcome the limitations of calculations in smart contracts. To prove the hypothesis, I use these mathematical models to compute complex operations of naive Bayes, linear regression, decision trees, and neural network algorithms on Ethereum public test networks. The smart contracts achieve 95\% prediction accuracy compared to traditional programming language models, proving the soundness of the numerical derivations. Many non-real-time applications can use our solution for trusted and secure prediction services.

Identiferoai:union.ndltd.org:unt.edu/info:ark/67531/metadc2179338
Date07 1900
CreatorsBadruddoja, Syed
ContributorsDantu, Ram, He, Yanyan, Tunc, Cihan, Bhowmick, Sanjukta
PublisherUniversity of North Texas
Source SetsUniversity of North Texas
LanguageEnglish
Detected LanguageEnglish
TypeThesis or Dissertation
FormatText
RightsPublic, Badruddoja, Syed, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved.

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