Conference
Data Leakage Mitigation of User-Defined Functions on Secure Personal Data Management Systems
| العنوان: | Data Leakage Mitigation of User-Defined Functions on Secure Personal Data Management Systems |
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| المؤلفون: | Carpentier, Robin, Sandu Popa, Iulian, Anciaux, Nicolas |
| المساهمون: | Personal Trusted cloud (PETRUS), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Données et algorithmes pour une ville intelligente et durable - DAVID (DAVID), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ANR-22-PECY-0002,iPoP,interdisciplinary Project on Privacy(2022) |
| المصدر: | SSDBM 2022 - 34th International Conference on Scientific and Statistical Database Management ; https://inria.hal.science/hal-03692175 ; SSDBM 2022 - 34th International Conference on Scientific and Statistical Database Management, Jul 2022, Copenhagen, Denmark. ⟨10.1145/3538712.3538741⟩ ; https://ssdbm.org/2022/ |
| بيانات النشر: | CCSD |
| سنة النشر: | 2022 |
| المجموعة: | Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQ |
| مصطلحات موضوعية: | Personal Data Management Systems, User-defined functions, Untrusted Code, Information leakage, Trusted Execution Environment, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR] |
| جغرافية الموضوع: | Copenhagen, Denmark |
| الوصف: | International audience ; Personal Data Management Systems (PDMSs) arrive at a rapid pace providing individuals with appropriate tools to collect, manage and share their personal data. At the same time, the emergence of Trusted Execution Environments (TEEs) opens new perspectives in solving the critical and conflicting challenge of securing users' data while enabling a rich ecosystem of data-driven applications. In this paper, we propose a PDMS architecture leveraging TEEs as a basis for security. Unlike existing solutions, our architecture allows for data processing extensiveness through the integration of any userdefined functions, albeit untrusted by the data owner. In this context, we focus on aggregate computations of large sets of database objects and provide a first study to mitigate the very large potential data leakage. We introduce the necessary security building blocks and show that an upper bound on data leakage can be guaranteed to the PDMS user. We then propose practical evaluation strategies ensuring that the potential data leakage remains minimal with a reasonable performance overhead. Finally, we validate our proposal with an Intel SGX-based PDMS implementation on real data sets. |
| نوع الوثيقة: | conference object |
| اللغة: | English |
| DOI: | 10.1145/3538712.3538741 |
| الاتاحة: | https://inria.hal.science/hal-03692175 https://inria.hal.science/hal-03692175v1/document https://inria.hal.science/hal-03692175v1/file/Data%20Leakage%20Mitigation%20of%20User-Defined%20Functions%20on%20Secure%20Personal%20Data%20Management%20Systems.pdf https://doi.org/10.1145/3538712.3538741 |
| Rights: | info:eu-repo/semantics/OpenAccess |
| رقم الانضمام: | edsbas.EFFA33DC |
| قاعدة البيانات: | BASE |
| DOI: | 10.1145/3538712.3538741 |
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