Shopping Preferences are safeguarded by differential privacy

Computer Engineering

A variety of assaults might cause online banks to reveal the buying interests of their customers. Because of differential privacy, any consumer can alter his consumption quantity locally before submitting it to online banks. However, because current differential privacy systems do not take into account resolving the noise boundary problem, immediately implementing differential privacy in online banking would result in problems in practice. In this research, we provide an Optimized Differential Private Online Transaction Scheme (O-DIOR) for online banks to establish consumption amount ceilings with additional noises. In order to use various bounds while still adhering to the notion of differential privacy, we next modify O-DIOR and create a RO-DIOR scheme. In order to demonstrate that our systems can meet the differential privacy requirement, we also offer a thorough theoretical analysis. Finally, we have used our systems in tests using mobile payments to gauge their performance. According to experimental findings, the relationship between online bank balance and spending quantity is greatly decreased, and reciprocal informational privacy losses are smaller than 0.5.

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