Current mobile payment schemes gather detailed information about purchases customers make. This data can then be used to infer a customer’s spending behaviour, potentially violating their privacy. To tackle this problem, we propose an untraceable mobile payment scheme that strikes a better balance, preserving user privacy while allowing the Third-Party Service Provider (TPSP) to collect necessary information such as card details and transaction amount for regulatory compliance. Our scheme offers untraceability for legitimate users from malicious adversaries and curious TPSPs using cryptographic primitives such as partially blind signatures, zero-knowledge proofs and identity-based signatures. It also guarantees that only authorised TPSPs can issue valid payment tokens, and even with limited data the TPSP can still prevent dishonest customers/merchants from double-spending a payment token. We also propose a comprehensive evaluation framework to assess the untraceable payment schemes against seven key criteria such as untraceability, exculpability - merchant double-spending, exculpability - customer double-spending, unforgeability, confidentiality, message authenticity, efficiency and regulatory compliance. We rigorously benchmark the security and privacy of our proposed payment scheme against this framework and other established schemes. Furthermore, we formally verify these properties using complexity-based analysis and Proverif modelling.

Jeyamohan Neera

Xiaomin Chen

Nauman Aslam

Biju Issac

ACM Transactions on Privacy and Security

ACM TRANSACTIONS ON PRIVACY AND SECURITY (TOPS)（前身为 TISSEC）发布信息和系统安全与隐私领域的高质量研究成果。欢迎研究涉及这些领域的各个方面，从技术到系统和应用，再到政策制定。

ACM Transactions on Privacy and Security (TOPS), formerly known as TISSEC, publishes high-quality research findings in the fields of information and system security and privacy. We welcome research covering all aspects of these areas, from technology to systems and applications, as well as policy-making.

《ACM Transactions on Privacy and Security》（前身为 TISSEC）致力于发布信息和系统安全及隐私领域的高质量研究成果。我们欢迎涉及这些领域各个方面的研究，包括技术、系统与应用，以及政策制定。

Category	Quartile
计算机科学	4
计算机科学, 计算机信息系统	4

A Trustworthy and Untraceable Centralised Payment Protocol for Mobile Payment

ivySCI AI Smartly Parses PDF, Answers Researchers' Questions, and Helps You Understand Papers in Seconds

Journal Info

Category	Quartile
COMPUTER SCIENCE, INFORMATION SYSTEMS	2