典型文献
Large-scale App privacy governance
文献摘要：
Recently,the problem of mobile applications(Apps)leaking users'private information has aroused wide concern.As the number of Apps continuously increases,effective large-scale App governance is a major challenge.Currently,the government mainly filters out Apps with potential privacy problems manually.Such approach is inefficient with limited searching scope.In this regard,we propose a quantitative method to filter out problematic Apps on a large scale.We introduce Privacy Level(P-Level)to measure an App's probability of leaking privacy.P-Level is calculated on the basis of Permission-based Privacy Value(P-Privacy)and Usage-based Privacy Value(U-Privacy).The former considers App permission setting,whereas the latter considers App usage.We first illustrate the privacy value model and computation results of both values based on real-world dataset.Subsequently,we introduce the P-Level computing model.We also define the P-Level computed on our dataset as the PL stan-dard.We analyze the distribution of average usage and number of Apps under the levels given in the PL standard,which may provoke insights into the large-scale App governance.Through P-Privacy,U-Privacy,and P-Level,potentially problematic Apps can be filtered out efficiently,thereby making up for the shortcoming of being manual.
文献关键词：
中图分类号：
作者姓名：
Zitong LI;Zhuoya FAN;Junxu LIU;Leixia WANG;Xiaofeng MENG
作者机构：
School of Information,Renmin University of China,Beijing 100872,China
文献出处：
引用格式：
[1]Zitong LI;Zhuoya FAN;Junxu LIU;Leixia WANG;Xiaofeng MENG-.Large-scale App privacy governance)[J].工程管理前沿（英文版）,2022(04):640-652
A类：
Permission
B类：
Large,scale,privacy,governance,Recently,mobile,applications,Apps,leaking,users,private,information,has,aroused,wide,concern,number,continuously,increases,effective,large,major,challenge,Currently,government,mainly,filters,out,problems,manually,Such,approach,inefficient,limited,searching,scope,In,this,regard,we,propose,quantitative,method,problematic,We,introduce,Privacy,Level,measure,probability,calculated,basis,Value,Usage,former,considers,permission,setting,whereas,latter,usage,first,illustrate,model,computation,results,both,values,real,world,dataset,Subsequently,computing,also,define,computed,our,PL,analyze,distribution,average,under,levels,given,standard,which,may,provoke,insights,into,Through,potentially,can,filtered,efficiently,thereby,making,up,shortcoming,being
AB值：
0.536508
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