Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/128390
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dc.contributor.authorSun, R.en
dc.contributor.authorXue, M.en
dc.date.issued2020en
dc.identifier.citationProceedings of the 24th Evaluation and Assessment in Software Engineering (EASE 2020), 2020 / pp.270-275en
dc.identifier.isbn9781450377317en
dc.identifier.urihttp://hdl.handle.net/2440/128390-
dc.description.abstractOnline Automated Privacy Policy Generators (APPGs) are tools used by app developers to quickly create app privacy policies which are required by privacy regulations to be incorporated to each mobile app. The creation of these tools brings convenience to app developers; however, the quality of these tools puts developers and stakeholders at legal risk. In this paper, we conduct an empirical study to assess the quality of online APPGs. We analyze the completeness of privacy policies, determine what categories and items should be covered in a complete privacy policy, and conduct APPG assessment with boilerplate apps. The results of assessment show that due to the lack of static or dynamic analysis of app’s behavior, developers may encounter two types of issues caused by APPGs. First, the generated policies could be incomplete because they do not cover all the essential items required by a privacy policy. Second, some generated privacy policies contain unnecessary personal information collection or arbitrary commitments inconsistent with user input. Ultimately, the defects of APPGs may potentially lead to serious legal issues.We hope that the results and insights developed in this paper can motivate the healthy and ethical development of APPGs towards generating a more complete, accurate, and robust privacy policy.en
dc.description.statementofresponsibilityRuoxi Sun, Minhui Xueen
dc.language.isoenen
dc.publisherAssociation for Computing Machineryen
dc.rights© 2020 Association for Computing Machinery.en
dc.source.urihttps://dl.acm.org/doi/proceedings/10.1145/3383219en
dc.subjectAutomated privacy policy generator; Privacy policy completeness analysis; Quality assessmenten
dc.titleQuality assessment of online automated privacy policy generators: An empirical studyen
dc.typeConference paperen
dc.identifier.rmid1000023796en
dc.contributor.conferenceEvaluation and Assessment in Software Engineering (EASE) (15 Apr 2020 - 17 Apr 2020 : Trondheim, Norway)en
dc.identifier.doi10.1145/3383219.3383247en
dc.publisher.placeNew Yorken
dc.identifier.pubid539540-
pubs.library.collectionComputer Science publicationsen
pubs.library.teamDS03en
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
dc.identifier.orcidSun, R. [0000-0001-5404-8550]en
dc.identifier.orcidXue, M. [0000-0001-5411-5039]en
Appears in Collections:Computer Science publications

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