Efficient Zero-Knowledge Authenticated Data Structures
- Esha Ghosh | Brown University
With the advent of cloud storage and computing, adopting cloud services to reduce operational, maintenance and storage costs, is becoming increasingly common — both for individuals and corporations. However, the fact that the data owner is not in physical possession of the data anymore raises important challenges in terms of integrity of data. Moreover, this is more than just a theoretical risk, since third party service providers are typically allowed to access the remotely stored data. Such risks raise obvious privacy issues. Along with such important security and privacy concerns, efficiency is also a major factor in such settings, as the main motivations for adopting cloud computing – namely scalability and computation offloading – are defeated otherwise. In this talk I will discuss our work on efficient privacy-preserving protocols addressing the above challenges for a large class of data queries. I will first describe our proposed model and then discuss protocols for set queries, order queries for lists and range queries.
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Melissa Chase
Principal Researcher
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Series: Microsoft Research Talks
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Decoding the Human Brain – A Neurosurgeon’s Experience
- Dr. Pascal O. Zinn
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Challenges in Evolving a Successful Database Product (SQL Server) to a Cloud Service (SQL Azure)
- Hanuma Kodavalla,
- Phil Bernstein
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Improving text prediction accuracy using neurophysiology
- Sophia Mehdizadeh
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Tongue-Gesture Recognition in Head-Mounted Displays
- Tan Gemicioglu
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DIABLo: a Deep Individual-Agnostic Binaural Localizer
- Shoken Kaneko
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Audio-based Toxic Language Detection
- Midia Yousefi
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From SqueezeNet to SqueezeBERT: Developing Efficient Deep Neural Networks
- Forrest Iandola,
- Sujeeth Bharadwaj
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Hope Speech and Help Speech: Surfacing Positivity Amidst Hate
- Ashique Khudabukhsh
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Towards Mainstream Brain-Computer Interfaces (BCIs)
- Brendan Allison
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Learning Structured Models for Safe Robot Control
- Subramanian Ramamoorthy
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