AI-Driven Secure Event Ticketing with Blockchain, Dynamic Pricing, and Fraud Analytics

The rapid growth of online event ticketing over the past decade has brought convenience alongside a persistent set of problems: bot-driven scalping, counterfeit or duplicated tickets, and resale channels that remain opaque to organizers and attendees alike. Centralized platforms generally offer no independently verifiable record of ownership and no automated way to recognize abnormal purchasing behavior before it results in unfair access or inflated resale prices. This paper presents the design of an AI-driven, blockchain-based ticketing framework in which every ticket is minted as a non-fungible token (NFT) under smart-contract control, while a machine-learning module continuously scores purchase and behavioral signals to assign each transaction a numerical risk level. High-risk transactions can be flagged for review or blocked before issuance, and an organizercontrolled resale workflow, paired with QR-code and on-chain verification at the venue, limits unauthorized transfer and duplication. A demand-aware dynamic pricing component is further proposed to close the gap between face value and marketclearing price that makes scalping profitable, letting ticket price track real demand instead of remaining fixed. The paper sets out the system's architecture, methodology, algorithms, and security posture, positions the work against two closely related published systems, and reports its implementation status candidly as a design-and-development-stage academic project rather than presenting premature or fabricated results. Keywords—Blockchain, Non-Fungible Tokens (NFT), Smart Contracts, Artificial Intelligence, Fraud Detection, Ticket Scalping, Dynamic Pricing, Event Ticketing, Ethereum, ERC-721.