Securing Ride-Sharing Platforms with Blockchain: Enhancing Privacy, Fraud Prevention, And Transaction Integrity Using Elliptic Curve Cryptography and Zero- Knowledge Proofs

Abstract

The increasing reliance on centralized ride-sharing platforms has led to significant
security vulnerabilities, including data breaches, fraud, and identity theft. This
study proposes a blockchain-based ride-sharing framework leveraging Elliptic
Curve Cryptography (ECC) and Zero-Knowledge Proofs (ZKPs) to enhance
security, privacy, and transparency. ECC is implemented for secure digital
signatures and authentication, ensuring tamper-proof ride transactions with
reduced computational overhead compared to traditional cryptographic methods.
ZKPs enable anonymous identity verification, allowing users to authenticate
themselves without revealing personal data, thereby mitigating identity fraud and
unauthorized access. A comparative performance evaluation is conducted to assess
the transaction speed, latency, scalability, and security resilience of the proposed
blockchain-based system versus traditional centralized ride-sharing platforms.
The findings reveal that while blockchain transactions experience slightly higher
latency (1.5–2.3s) and lower scalability (900–1,050 TPS) than centralized systems,
they exhibit superior security resilience, successfully blocking over 90% of
cyberattacks. Matplotlib-generated performance charts over seven days of uptime
illustrate blockchain’s advantages in fraud prevention and transaction integrity,
despite its current scalability challenges. The study also provides a detailed
mathematical breakdown of ECC and ZKPs, demonstrating their implementation
in ride-sharing identity verification and secure fare processing. The results suggest
that future ride-sharing architectures should incorporate hybrid blockchain
models to balance scalability and decentralization. The proposed framework
contributes to the advancement of secure, privacy-preserving, and fraud-resistant
decentralized transportation systems, paving the way for real-world deployment
and industry adoption.