Please wait a minute...
Data Analysis and Knowledge Discovery
Current Issue | Archive | Adv Search |
Evaluating the Compliance of Mobile Health APP Privacy Policy with Machine Learning
Zhao Yang,Yan Zhouzhou,Shen Qiqi,Li Zhonghang
(School of Information Management, Wuhan University, Wuhan 430072, China) (School of National Secrecy, Wuhan University, Wuhan 430072, China)
Export: BibTeX | EndNote (RIS)      

[Objective] This paper evaluates the compliance of China's mobile health APP privacy policy with machine learning, aiming to improve the efficiency and accuracy of privacy policy compliance evaluation.

[Methods] According to relevant national policies and regulations, this paper firstly constructs the evaluation index system for the privacy policy compliance of mobile health apps. Secondly, based on the hard voting classifier, the compliance evaluation model is established by integrating three machine learning algorithms: CNN, RNN and LSTM. Finally, using the data of 1210 mobile health apps in the Android mobile phone application market, we verify the effectiveness of the model and evaluate the compliance of privacy policy.

[Results] The overall compliance of the mobile health APP privacy policy is poor, and there are many violations in the six evaluation indicators. The privacy policy compliance scores of online medical APP, medical services APP, health management APP, and medical information APP are 0.63, 0.59, 0.61and 0.66.

[Limitations] Due to the limited amount of annotated privacy policy data, the compliance evaluation model may not be able to fully learn the features of evaluation indicators.

[Conclusions] This model can conduct large-scale, fine-grained automatic evaluation of the compliance of APP privacy policies. It also provides new ideas and methods for the scientific supervision of government departments and the self-inspection of APP operators.

Key words Mobile Health APP      Privacy Policy      Machine Learning      Compliance Evaluation      
Published: 25 November 2021
ZTFLH:  TP391,G250  

Cite this article:

Zhao Yang, Yan Zhouzhou, Shen Qiqi, Li Zhonghang. Evaluating the Compliance of Mobile Health APP Privacy Policy with Machine Learning . Data Analysis and Knowledge Discovery, 0, (): 1-.

URL: 2021.0897     OR

[1] Wang Hanxue,Cui Wenjuan,Zhou Yuanchun,Du Yi. Identifying Pathogens of Foodborne Diseases with Machine Learning[J]. 数据分析与知识发现, 2021, 5(9): 54-62.
[2] Chen Donghua,Zhao Hongmei,Shang Xiaopu,Zhang Runtong. Optimizing Large Hospital Operating Rooms with Data Analytics[J]. 数据分析与知识发现, 2021, 5(9): 115-128.
[3] Che Hongxin,Wang Tong,Wang Wei. Comparing Prediction Models for Prostate Cancer[J]. 数据分析与知识发现, 2021, 5(9): 107-114.
[4] Su Qiang, Hou Xiaoli, Zou Ni. Predicting Surgical Infections Based on Machine Learning[J]. 数据分析与知识发现, 2021, 5(8): 65-75.
[5] Cao Rui,Liao Bin,Li Min,Sun Ruina. Predicting Prices and Analyzing Features of Online Short-Term Rentals Based on XGBoost[J]. 数据分析与知识发现, 2021, 5(6): 51-65.
[6] Zhong Jiawa,Liu Wei,Wang Sili,Yang Heng. Review of Methods and Applications of Text Sentiment Analysis[J]. 数据分析与知识发现, 2021, 5(6): 1-13.
[7] Xiang Zhuoyuan,Liu Zhicong,Wu Yu. Adaptive Recommendation Model Based on User Behaviors[J]. 数据分析与知识发现, 2021, 5(4): 103-114.
[8] Chai Guorong,Wang Bin,Sha Yongzhong. Public Health Risk Forecasting with Multiple Machine Learning Methods Combined:Case Study of Influenza Forecasting in Lanzhou, China[J]. 数据分析与知识发现, 2021, 5(1): 90-98.
[9] Chen Dong,Wang Jiandong,Li Huiying,Cai Sihang,Huang Qianqian,Yi Chengqi,Cao Pan. Forecasting Poultry Turnovers with Machine Learning and Multiple Factors[J]. 数据分析与知识发现, 2020, 4(7): 18-27.
[10] Liang Ye,Li Xiaoyuan,Xu Hang,Hu Yiran. CLOpin: A Cross-Lingual Knowledge Graph Framework for Public Opinion Analysis and Early Warning[J]. 数据分析与知识发现, 2020, 4(6): 1-14.
[11] Yang Heng,Wang Sili,Zhu Zhongming,Liu Wei,Wang Nan. Recommending Domain Knowledge Based on Parallel Collaborative Filtering Algorithm[J]. 数据分析与知识发现, 2020, 4(6): 15-21.
[12] Wang Shuyi,Liu Sai,Ma Zheng. Microblog Image Privacy Classification with Deep Transfer Learning[J]. 数据分析与知识发现, 2020, 4(10): 80-92.
[13] Ruojia Wang,Lu Zhang,Jimin Wang. Automatic Triage of Online Doctor Services Based on Machine Learning[J]. 数据分析与知识发现, 2019, 3(9): 88-97.
[14] Gang Li,Huayang Zhou,Jin Mao,Sijing Chen. Classifying Social Media Users with Machine Learning[J]. 数据分析与知识发现, 2019, 3(8): 1-9.
[15] Jiahui Hu,An Fang,Wanqing Zhao,Chenliu Yang,Huiling Ren. Annotating Chinese E-Medical Record for Knowledge Discovery[J]. 数据分析与知识发现, 2019, 3(7): 123-132.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938