ViCLOUD: Measuring Vagueness in Cloud Service Privacy Policies and Terms of Services
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Anantaa Kotal, Karuna Pande Joshi, and Anupam Joshi, ViCLOUD: Measuring Vagueness in Cloud Service Privacy Policies and Terms of Services, IEEE International Conference on Cloud Computing (CLOUD), 2020
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© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Cloud Legal documents, like Privacy Policies and Terms of Services (ToS), include key terms and rules that enable consumers to continuously monitor the performance of the cloud services used in their organization. To ensure high consumer confidence in the cloud service, it is necessary that these documents are clear and comprehensible to the average consumer. However, in practice, service providers often use legalese and ambiguous language in cloud legal documents resulting in consumers consenting or rejecting the terms without understanding the details. A measure capturing ambiguity in the texts of cloud service documents will enable consumers to decide if they understand what they are agreeing to, and deciding whether that service will meet their organizational requirements. It will also allow them to compare the service policies across various vendors. We have developed a novel model, ViCLOUD, that defines a scoring method based on linguistic cues to measure ambiguity in cloud legal documents and compare them to other peer websites. In this paper, we describe the ViCLOUD model in detail along with the validation results when applying it to 112 privacy policies and 108 Terms of Service documents of 115 cloud service vendors. The score distribution gives us a landscape of current trends in cloud services and a scale of comparison for new documentation. Our model will be very useful to organizations in making judicious decisions when selecting their cloud service.