Privacy policy compliance detection and analysis based on knowledge graph

The personal information protection law (PIPL) of the People’s Republic of China served as an important legal framework for safeguarding personal information rights. It established clear regulations for personal information controllers in their activities involving the collecting, storing, using, an...

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Main Authors: ZHANG Xiheng, LI Xin, TANG Peng, HUANG Ruiqi, HE Yuan, QIU Weidong
Format: Article
Language:English
Published: POSTS&TELECOM PRESS Co., LTD 2024-12-01
Series:网络与信息安全学报
Subjects:
Online Access:http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2024087
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author ZHANG Xiheng
LI Xin
TANG Peng
HUANG Ruiqi
HE Yuan
QIU Weidong
author_facet ZHANG Xiheng
LI Xin
TANG Peng
HUANG Ruiqi
HE Yuan
QIU Weidong
author_sort ZHANG Xiheng
collection DOAJ
description The personal information protection law (PIPL) of the People’s Republic of China served as an important legal framework for safeguarding personal information rights. It established clear regulations for personal information controllers in their activities involving the collecting, storing, using, and sharing of personal information. It also required that these controllers provide explanations within their privacy policies for the services they offered. This meant that any company providing services in China must first offer a privacy policy that complied with the requirements of the PIPL. Therefore, in order to analyze the compliance of privacy policies with respect to the PIPL, an intelligent method was presented for assessing privacy policy compliance based on a knowledge graph. First, a comprehensive analysis of the PIPL was conducted, and a multi-level privacy policy knowledge graph was proposed that covered concepts related to information protection that needed to be explained in privacy policies. Next, a semi-automated method was built for collecting privacy policies and collected the privacy policies of 400 Chinese Apps. 100 policies were cross-annotated based on the knowledge graph, resulting in the creation of the first Chinese privacy policy corpus tailored to the PIPL called APPCP-100 (APP-privacy-policy-corpus-for-PIPL-100). Using this corpus, a Chinese concept classifier model CPP-BERT was constructed to achieve efficient detection of privacy policy compliance. Finally, the knowledge graph was applied to conduct a comprehensive compliance analysis of privacy policies, and the results indicate that the current compliance of Chinese App privacy policies with the fine-grained concepts of the PIPL still needs improvement.
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spelling doaj-art-0343b53eb9fe45fdad72ae916887a0d62025-02-08T19:00:10ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2024-12-011015116380361782Privacy policy compliance detection and analysis based on knowledge graphZHANG XihengLI XinTANG PengHUANG RuiqiHE YuanQIU WeidongThe personal information protection law (PIPL) of the People’s Republic of China served as an important legal framework for safeguarding personal information rights. It established clear regulations for personal information controllers in their activities involving the collecting, storing, using, and sharing of personal information. It also required that these controllers provide explanations within their privacy policies for the services they offered. This meant that any company providing services in China must first offer a privacy policy that complied with the requirements of the PIPL. Therefore, in order to analyze the compliance of privacy policies with respect to the PIPL, an intelligent method was presented for assessing privacy policy compliance based on a knowledge graph. First, a comprehensive analysis of the PIPL was conducted, and a multi-level privacy policy knowledge graph was proposed that covered concepts related to information protection that needed to be explained in privacy policies. Next, a semi-automated method was built for collecting privacy policies and collected the privacy policies of 400 Chinese Apps. 100 policies were cross-annotated based on the knowledge graph, resulting in the creation of the first Chinese privacy policy corpus tailored to the PIPL called APPCP-100 (APP-privacy-policy-corpus-for-PIPL-100). Using this corpus, a Chinese concept classifier model CPP-BERT was constructed to achieve efficient detection of privacy policy compliance. Finally, the knowledge graph was applied to conduct a comprehensive compliance analysis of privacy policies, and the results indicate that the current compliance of Chinese App privacy policies with the fine-grained concepts of the PIPL still needs improvement.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2024087personal information protection law of the People's Republic of Chinaprivacy policyprivacy protectioncompliance check
spellingShingle ZHANG Xiheng
LI Xin
TANG Peng
HUANG Ruiqi
HE Yuan
QIU Weidong
Privacy policy compliance detection and analysis based on knowledge graph
网络与信息安全学报
personal information protection law of the People's Republic of China
privacy policy
privacy protection
compliance check
title Privacy policy compliance detection and analysis based on knowledge graph
title_full Privacy policy compliance detection and analysis based on knowledge graph
title_fullStr Privacy policy compliance detection and analysis based on knowledge graph
title_full_unstemmed Privacy policy compliance detection and analysis based on knowledge graph
title_short Privacy policy compliance detection and analysis based on knowledge graph
title_sort privacy policy compliance detection and analysis based on knowledge graph
topic personal information protection law of the People's Republic of China
privacy policy
privacy protection
compliance check
url http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2024087
work_keys_str_mv AT zhangxiheng privacypolicycompliancedetectionandanalysisbasedonknowledgegraph
AT lixin privacypolicycompliancedetectionandanalysisbasedonknowledgegraph
AT tangpeng privacypolicycompliancedetectionandanalysisbasedonknowledgegraph
AT huangruiqi privacypolicycompliancedetectionandanalysisbasedonknowledgegraph
AT heyuan privacypolicycompliancedetectionandanalysisbasedonknowledgegraph
AT qiuweidong privacypolicycompliancedetectionandanalysisbasedonknowledgegraph