Description
Performing non- aggregate range queries on cloud stored data, while achieving both privacy and efficiency is a challenging problem. With the PINED-RQ family of techniques, we propose constructing a differentially private index to an outsourced encrypted dataset. Efficiency is enabled by using a cleartext index structure to perform range queries. Security relies on both differential privacy (of the index) and semantic security (of the encrypted dataset). Our initial solution, PINED-RQ, develops algorithms for building and updating the differentially private index. Our recent proposals extend PINED-RQ with a parallel architecture for coping with high-rate incoming data. Compared to state-of-the-art secure index based range query processing approaches, PINED-RQ executes queries in the order of at least one magnitude faster. Moreover its parallel extensions increase its throughput by at least one order of magnitude. The security of the PINED-RQ solutions is proved and their efficiency is assessed by extensive experimental validations. In this talk, I will introduce the PINED-RQ family of techniques by presenting the initial PINED-RQ proposal and overviewing then its parallel extensions.
Infos pratiques
Prochains exposés
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CHERIoT RTOS: An OS for Fine-Grained Memory-Safe Compartments on Low-Cost Embedded Devices
Orateur : Hugo Lefeuvre - The University of British Columbia
Embedded systems do not benefit from strong memory protection, because they are designed to minimize cost. At the same time, there is increasing pressure to connect embedded devices to the internet, where their vulnerable nature makes them routinely subject to compromise. This fundamental tension leads to the current status-quo where exploitable devices put individuals and critical infrastructure[…]-
SoSysec
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Compartmentalization
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Operating system and virtualization
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Hardware/software co-design
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Hardware architecture
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