@article{ART003130946},
author={Dong-Hyun Kim and Ye-Seul Cho and Tae-Jong Kim},
title={A Study on Measuring the Risk of Re-identification of Personal Information in Conversational Text Data using AI},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2024},
volume={29},
number={10},
pages={77-87},
doi={10.9708/jksci.2024.29.10.077}
TY - JOUR
AU - Dong-Hyun Kim
AU - Ye-Seul Cho
AU - Tae-Jong Kim
TI - A Study on Measuring the Risk of Re-identification of Personal Information in Conversational Text Data using AI
JO - Journal of The Korea Society of Computer and Information
PY - 2024
VL - 29
IS - 10
PB - The Korean Society Of Computer And Information
SP - 77
EP - 87
SN - 1598-849X
AB - With the recent advancements in artificial intelligence, various chatbots have emerged, efficiently performing everyday tasks such as hotel bookings, news updates, and legal consultations. Particularly, generative chatbots like ChatGPT are expanding their applicability by generating original content in fields such as education, research, and the arts. However, the training of these AI chatbots requires large volumes of conversational text data, such as customer service records, which has led to privacy infringement cases domestically and internationally due to the use of unrefined data. This study proposes a methodology to quantitatively assess the re-identification risk of personal information contained in conversational text data used for training AI chatbots. To validate the proposed methodology, we conducted a case study using synthetic conversational data and carried out a survey with 220 external experts, confirming the significance of the proposed approach.
KW - Personal Information;AI Chatbot;Conversational Data;Risk Measurement
DO - 10.9708/jksci.2024.29.10.077
ER -
Dong-Hyun Kim, Ye-Seul Cho and Tae-Jong Kim. (2024). A Study on Measuring the Risk of Re-identification of Personal Information in Conversational Text Data using AI. Journal of The Korea Society of Computer and Information, 29(10), 77-87.
Dong-Hyun Kim, Ye-Seul Cho and Tae-Jong Kim. 2024, "A Study on Measuring the Risk of Re-identification of Personal Information in Conversational Text Data using AI", Journal of The Korea Society of Computer and Information, vol.29, no.10 pp.77-87. Available from: doi:10.9708/jksci.2024.29.10.077
Dong-Hyun Kim, Ye-Seul Cho, Tae-Jong Kim "A Study on Measuring the Risk of Re-identification of Personal Information in Conversational Text Data using AI" Journal of The Korea Society of Computer and Information 29.10 pp.77-87 (2024) : 77.
Dong-Hyun Kim, Ye-Seul Cho, Tae-Jong Kim. A Study on Measuring the Risk of Re-identification of Personal Information in Conversational Text Data using AI. 2024; 29(10), 77-87. Available from: doi:10.9708/jksci.2024.29.10.077
Dong-Hyun Kim, Ye-Seul Cho and Tae-Jong Kim. "A Study on Measuring the Risk of Re-identification of Personal Information in Conversational Text Data using AI" Journal of The Korea Society of Computer and Information 29, no.10 (2024) : 77-87.doi: 10.9708/jksci.2024.29.10.077
Dong-Hyun Kim; Ye-Seul Cho; Tae-Jong Kim. A Study on Measuring the Risk of Re-identification of Personal Information in Conversational Text Data using AI. Journal of The Korea Society of Computer and Information, 29(10), 77-87. doi: 10.9708/jksci.2024.29.10.077
Dong-Hyun Kim; Ye-Seul Cho; Tae-Jong Kim. A Study on Measuring the Risk of Re-identification of Personal Information in Conversational Text Data using AI. Journal of The Korea Society of Computer and Information. 2024; 29(10) 77-87. doi: 10.9708/jksci.2024.29.10.077
Dong-Hyun Kim, Ye-Seul Cho, Tae-Jong Kim. A Study on Measuring the Risk of Re-identification of Personal Information in Conversational Text Data using AI. 2024; 29(10), 77-87. Available from: doi:10.9708/jksci.2024.29.10.077
Dong-Hyun Kim, Ye-Seul Cho and Tae-Jong Kim. "A Study on Measuring the Risk of Re-identification of Personal Information in Conversational Text Data using AI" Journal of The Korea Society of Computer and Information 29, no.10 (2024) : 77-87.doi: 10.9708/jksci.2024.29.10.077