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祝贺我们的论文被IEEE SYST J接收!
Authors: Lin, Chao; Luo, Min; Huang, Xinyi; Choo, Kim-Kwang Raymond; He, Debiao
Title: An Efficient Privacy-Preserving Credit Score System Based on Non-Interactive Zero-Knowledge Proof
Journal: IEEE Systems Journal
 
Abstract: Credit system is generally associated with the banking and financial institutions, although it has far reaching implications for residents of countries such as U.S. particularly for those with a poor credit history. Specifically, a credit score computation (CSC) quantifies an individual's credit value or credit risk, which is used by banking and financial institutions, as well as other entities (e.g., during purchasing of insurance policies and application of rental properties), to facilitate their decision-making (e.g., whether to approve the insurance policy purchase or the level of premium). Although a number of CSC models have been proposed in the literature for supporting different application scenarios, privacy protection of CSC is rarely considered despite the potential for leakage of user private information (e.g., registration, hobbies, credit, relationships and inquiry). Such information can then be abused for other nefarious activities, such as identity theft and credit card fraud. Thus, in this paper, we first analyze the privacy strength of existing CSC models, prior to presenting the formal definition of a privacy-preserving credit score computation (PCSC) system alongside its security requirements. Then, we propose a concrete construction based on Paillier Encryption with three proposed NIZK schemes. To demonstrate feasibility of our proposal, we evaluate both its security and performance.
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