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Siva Alagesh, S., Bhavna, B., Swati, A., Aruna, J.R., Samrat, R. and Amit, K. (2022) Privacy Preservation Using Block chain for Credit Card Data. 2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM), Gautam Buddha Nagar, 23-25 February 2022, 725-730. https://doi.org/10.1109/ICIPTM54933.2022.9754015

has been cited by the following article:

• TITLE: A Method to Improve the Accuracy of Personal Information Detection

  AUTHORS: Chih-Chieh Chiu, Chu-Sing Yang, Ce-Kuen Shieh

  KEYWORDS: Data Leakage, Privacy, Personal Information Factors

  JOURNAL NAME: Journal of Computer and Communications, Vol.11 No.6, June 30, 2023

  ABSTRACT: 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.