مشخصات مقاله:
عنوان فارسی مقاله:
اشتراک مشارکت داده های خصوصی مشروط هوشمند
عنوان انگلیسی مقاله:
Intelligent conditional collaborative private data sharing
مناسب برای رشته های دانشگاهی زیر:
مهندسی فناوری اطلاعات – مهندسی کامپیوتر
مناسب برای گرایش های دانشگاهی زیر:
شبکه های کامپیوتری – هوش مصنوعی
وضعیت مقاله انگلیسی و ترجمه:
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فهرست مطالب:
Outline
Highlights
Abstract
۱٫ Introduction
۲٫ Models and preliminaries
۳٫ Proposed approach
۴٫ Use case example
۵٫ Performance evaluation
۶٫ Conclusion
Acknowledgments
References
قسمتی از مقاله انگلیسی:
Abstract
With the advent of distributed systems, secure and privacy-preserving data sharing between different entities (individuals or organizations) becomes a challenging issue. There are several real-world scenarios in which different entities are willing to share their private data only under certain circumstances, such as sharing the system logs when there is indications of cyber attack in order to provide cyber threat intelligence. Therefore, over the past few years, several researchers proposed solutions for collaborative data sharing, mostly based on existing cryptographic algorithms. However, the existing approaches are not appropriate for conditional data sharing, i.e., sharing the data if and only if a pre-defined condition is satisfied due to the occurrence of an event. Moreover, in case the existing solutions are used in conditional data sharing scenarios, the shared secret will be revealed to all parties and re-keying process is necessary. In this work, in order to address the aforementioned challenges, we propose, a “conditional collaborative private data sharing” protocol based on Identity-Based Encryption and Threshold Secret Sharing schemes. In our proposed approach, the condition based on which the encrypted data will be revealed to the collaborating parties (or a central entity) could be of two types: (i) threshold, or (ii) pre-defined policy. Supported by thorough analytical and experimental analysis, we show the effectiveness and performance of our proposal.
1 Introduction
New generation networking paradigms, such as Cloud, have made data sharing between individuals or organizations easier and simpler than ever before. However, preserving confidentiality and privacy of the shared data (which could be privacy sensitive) is an important and challenging issue in such networks. This issue becomes more significant with regards to distributed systems, in which different systems might have their own access control policies for the shared data. Therefore, providing an intelligent private data sharing method that allows the involved parties to decide when, to whom, and to what extent they should share their private data is important [9, 13].