18282983. DIFFERENTIAL PRIVACY-BASED SERVICE ANALYSIS METHOD AND APPARATUS simplified abstract (Alipay (Hangzhou) Information Technology Co., Ltd.)

DIFFERENTIAL PRIVACY-BASED SERVICE ANALYSIS METHOD AND APPARATUS

Organization Name

Alipay (Hangzhou) Information Technology Co., Ltd.

Inventor(s)

Ruofan Wu of Hangzhou (CN)

DIFFERENTIAL PRIVACY-BASED SERVICE ANALYSIS METHOD AND APPARATUS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18282983 titled 'DIFFERENTIAL PRIVACY-BASED SERVICE ANALYSIS METHOD AND APPARATUS

Simplified Explanation

The patent application describes methods and apparatuses for differential privacy-based service analysis. The process involves multiple rounds of operations, including obtaining target data through anonymization processing, performing service analysis on the target data, and adjusting the privacy budget based on the success or failure of the analysis.

• Differential privacy-based service analysis methods and apparatuses:

   * The methods include at least one service analysis stage with multiple rounds of operations.
   * Each round involves obtaining target data through anonymization processing and performing service analysis.
   * The privacy budget is adaptively adjusted based on the success or failure of the service analysis.

Potential Applications

This technology can be applied in various industries such as healthcare, finance, and marketing for analyzing sensitive data while maintaining privacy.

Problems Solved

1. Ensuring privacy protection while analyzing sensitive data. 2. Adapting the privacy budget to enhance flexibility in the privacy protection process.

Benefits

1. Improved availability of privacy protection for data. 2. Enhanced flexibility in adjusting the privacy budget.

Potential Commercial Applications

Optimizing data analysis processes in industries such as healthcare, finance, and marketing.

Possible Prior Art

One possible prior art could be the use of differential privacy techniques in data analysis processes to protect user privacy.

How does this technology compare to existing privacy protection methods in terms of effectiveness and efficiency?

This article does not provide a direct comparison with existing privacy protection methods, leaving the reader to wonder about the advantages and disadvantages of this technology in comparison to others.

What are the potential limitations or challenges in implementing this technology on a large scale?

The article does not address the scalability or potential challenges of implementing this technology on a large scale, leaving room for speculation on the practicality of widespread adoption.

Original Abstract Submitted

This specification provides differential privacy-based service analysis methods and apparatuses. According to the methods, the methods include at least one service analysis stage, and any service analysis stage includes at least one round of operations. An nround of operations of the service analysis stage include the following steps: obtaining target data, where the target data are obtained by performing anonymization processing on to-be-processed data; performing predetermined service analysis on the target data; and if the service analysis succeeds, ending the service analysis stage; or if the service analysis fails, determining an (n+1)round of privacy budget, and sending the (n+1)round of privacy budget to the multiple user devices. As such, in a process of performing differential privacy processing on data, a privacy budget can be adaptively adjusted to enhance flexibility of a privacy protection process and improving availability of privacy protection data.