An Automatically Privacy Protection Solution for Implementing the Right to Be Forgotten in Embedded System

Zhao, Yanan; Si, Nong; Sun, Yu; Gao, Xin; Tong, Haopeng; Yuan, Geng

doi:10.1109/access.2022.3162238

Cited by 1 publication

(1 citation statement)

References 37 publications

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“…If the user is a salesperson, they might be deceived by being told, I am interested in purchasing products from you. As criminals become increasingly adept at tailoring their scams to individuals by using their personal data, the best way to protect oneself is to avoid disclosing too much private information [9].…”

Section: Impact Of Personal Data Leakagementioning

confidence: 99%

A Method to Improve the Accuracy of Personal Information Detection

Chiu¹,

Yang²,

Shieh³

2023

JCC

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It is necessary to confirm the personal data factors and the rules of verification before conducting personal data detection. So that the detection method can be written in the subsequent implementation of the automatic detection tool. This paper will conduct experiments on common personal data factor rules, including domestic personal identity numbers and credit card numbers with checksums. We use ChatGPT to test the accuracy of identifying personal information like ID card identification numbers or credit card numbers. And then use personal data correlation to reduce the time for personal data identification. Although the number of personal information factors found has decreased, it has had a better effect on the actual manual personal data identification. The result shows that it saves about 45% of the calculation time, and the execution efficiency of the accuracy is also improved with the original method by about 22%, which is about 2.2 times higher than the general method. Therefore, the method proposed in this paper can accurately and effectively find out the leftover personal information in the enterprise.

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Section: Impact Of Personal Data Leakagementioning

confidence: 99%