{"title":"DPL: GDPR执行的语言","authors":"Farzane Karami, D. Basin, E. Johnsen","doi":"10.1109/CSF54842.2022.9919687","DOIUrl":null,"url":null,"abstract":"The General Data Protection Regulation (GDPR) regulates the handling of personal data, including that personal data may be collected and stored only with the data subject's consent, that data is used only for the explicit purposes for which it is collected, and that is deleted after the purposes are served. We propose a programming language called DPL (Data Protection Language) with constructs for enforcing these central GDPR requirements and provide the language's runtime operational semantics. DPL is designed so that GDPR violations cannot occur: potential violations instead result in runtime errors. Moreover, DPL provides constructs to perform privacy-relevant checks, which enable programmers to avoid these errors. Finally, we formalize DPL in Maude, yielding an environment for program simulation, and verify our claims that DPL programs cannot result in privacy violations.","PeriodicalId":412553,"journal":{"name":"2022 IEEE 35th Computer Security Foundations Symposium (CSF)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"DPL: A Language for GDPR Enforcement\",\"authors\":\"Farzane Karami, D. Basin, E. Johnsen\",\"doi\":\"10.1109/CSF54842.2022.9919687\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The General Data Protection Regulation (GDPR) regulates the handling of personal data, including that personal data may be collected and stored only with the data subject's consent, that data is used only for the explicit purposes for which it is collected, and that is deleted after the purposes are served. We propose a programming language called DPL (Data Protection Language) with constructs for enforcing these central GDPR requirements and provide the language's runtime operational semantics. DPL is designed so that GDPR violations cannot occur: potential violations instead result in runtime errors. Moreover, DPL provides constructs to perform privacy-relevant checks, which enable programmers to avoid these errors. Finally, we formalize DPL in Maude, yielding an environment for program simulation, and verify our claims that DPL programs cannot result in privacy violations.\",\"PeriodicalId\":412553,\"journal\":{\"name\":\"2022 IEEE 35th Computer Security Foundations Symposium (CSF)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 35th Computer Security Foundations Symposium (CSF)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSF54842.2022.9919687\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 35th Computer Security Foundations Symposium (CSF)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSF54842.2022.9919687","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The General Data Protection Regulation (GDPR) regulates the handling of personal data, including that personal data may be collected and stored only with the data subject's consent, that data is used only for the explicit purposes for which it is collected, and that is deleted after the purposes are served. We propose a programming language called DPL (Data Protection Language) with constructs for enforcing these central GDPR requirements and provide the language's runtime operational semantics. DPL is designed so that GDPR violations cannot occur: potential violations instead result in runtime errors. Moreover, DPL provides constructs to perform privacy-relevant checks, which enable programmers to avoid these errors. Finally, we formalize DPL in Maude, yielding an environment for program simulation, and verify our claims that DPL programs cannot result in privacy violations.