Doctoral Dissertations

Keywords and Phrases

Blockchain; Internet of Things; Machine-learning; Security

Abstract

"Blockchain is one of the fastest technologies that rivals the Internet in terms of adoption speed. This security method is applicable to data-centric environments for validating data in the presence of faults. However, traditional blockchain implementation introduces bottlenecks with computationally intense security measures to prevent malicious spam and resolve conflicts. This dissertation explores a new direction for blockchain technology that allows limited nodes, like IoT devices, to make independent decisions with compressed knowledge of past blockchain history through the use of machine-learning for active decisions (or the first machine-intelligent blockchain protocol). Proposing to introduce machine-intelligence into the rapidly evolving paradigm creates unique security challenges, which this dissertation addresses. Each effort explored was analyzed for both its theoretical proofs and implemented in a realistic IoT blockchain environment.

The dissertation effort is organized into several sections. The first section addresses blockchain-empowered evasion attacks through a novel reward function and robust multi-arm bandit algorithm. The second section synthesizes realistic blockchain attack transaction data to empower learning in a distributed setting. The third and fourth sections together create a reputation system and consensus scheme for finalizing transactions based on observations of a monitored deep classifier. The reputation system prevents distributed learning poisoning through the use of game theory, while the consensus scheme prevents reputation poisoning and finalizes transactions. The fifth section creates a novel lightweight optimization technique for implementation with white-box machine-learning algorithms for auditing in a blockchain setting", -- Abstract, p. iv

Advisor(s)

Jagannathan, Sarangapani, 1965-

Committee Member(s)

Zawodniok, Maciej Jan, 1975-
Sedigh, Sahra
Luo, Tony T.
Madria, Sanjay Kumar

Department(s)

Electrical and Computer Engineering

Degree Name

Ph. D. in Computer Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2024

Pagination

xiv, 292 pages

Note about bibliography

Includes_bibliographical_references_(pages 39, 90, 142, 192, 232 & 273-291)

Rights

©2024 Charles Connor Rawlins , All Rights Reserved

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 12406

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