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Cryptography for Big Data security

Published in:
Chapter 10 in Big Data: Storage, Sharing, and Security, 2016, pp. 214-87.

Summary

This chapter focuses on state-of-the-art provably secure cryptographic techniques for protecting big data applications. We do not focus on more established, and commonly available cryptographic solutions. The goal is to inform practitioners of new techniques to consider as they develop new big data solutions rather than to summarize the current best practice for securing data.
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Summary

This chapter focuses on state-of-the-art provably secure cryptographic techniques for protecting big data applications. We do not focus on more established, and commonly available cryptographic solutions. The goal is to inform practitioners of new techniques to consider as they develop new big data solutions rather than to summarize the current...

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HEtest: a homomorphic encryption testing framework

Published in:
3rd Workshop on Encrypted Computing and Applied Homomorphic Cryptography (WAHC 2015), 30 January 2015.

Summary

In this work, we present a generic open-source software framework that can evaluate the correctness and performance of homomorphic encryption software. Our framework, called HEtest, automates the entire process of a test: generation of data for testing (such as circuits and inputs), execution of a test, comparison of performance to an insecure baseline, statistical analysis of the test results, and production of a LaTeX report. To illustrate the capability of our framework, we present a case study of our analysis of the open-source HElib homomorphic encryption software. We stress though that HEtest is written in a modular fashion, so it can easily be adapted to test any homomorphic encryption software.
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Summary

In this work, we present a generic open-source software framework that can evaluate the correctness and performance of homomorphic encryption software. Our framework, called HEtest, automates the entire process of a test: generation of data for testing (such as circuits and inputs), execution of a test, comparison of performance to...

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Automated assessment of secure search systems

Summary

This work presents the results of a three-year project that assessed nine different privacy-preserving data search systems. We detail the design of a software assessment framework that focuses on low system footprint, repeatability, and reusability. A unique achievement of this project was the automation and integration of the entire test process, from the production and execution of tests to the generation of human-readable evaluation reports. We synthesize our experiences into a set of simple mantras that we recommend following in the design of any assessment framework.
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Summary

This work presents the results of a three-year project that assessed nine different privacy-preserving data search systems. We detail the design of a software assessment framework that focuses on low system footprint, repeatability, and reusability. A unique achievement of this project was the automation and integration of the entire test...

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A survey of cryptographic approaches to securing big-data analytics in the cloud

Published in:
HPEC 2014: IEEE Conf. on High Performance Extreme Computing, 9-11 September 2014.

Summary

The growing demand for cloud computing motivates the need to study the security of data received, stored, processed, and transmitted by a cloud. In this paper, we present a framework for such a study. We introduce a cloud computing model that captures a rich class of big-data use-cases and allows reasoning about relevant threats and security goals. We then survey three cryptographic techniques - homomorphic encryption, verifiable computation, and multi-party computation - that can be used to achieve these goals. We describe the cryptographic techniques in the context of our cloud model and highlight the differences in performance cost associated with each.
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Summary

The growing demand for cloud computing motivates the need to study the security of data received, stored, processed, and transmitted by a cloud. In this paper, we present a framework for such a study. We introduce a cloud computing model that captures a rich class of big-data use-cases and allows...

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A survey of cryptographic approaches to securing big-data analytics in the cloud

Published in:
HPEC 2014: IEEE Conf. on High Performance Extreme Computing, 9-11 September 2014.

Summary

The growing demand for cloud computing motivates the need to study the security of data received, stored, processed, and transmitted by a cloud. In this paper, we present a framework for such a study. We introduce a cloud computing model that captures a rich class of big-data use-cases and allows reasoning about relevant threats and security goals. We then survey three cryptographic techniques - homomorphic encryption, verifiable computation, and multi-party computation - that can be used to achieve these goals. We describe the cryptographic techniques in the context of our cloud model and highlight the differences in performance cost associated with each.
READ LESS

Summary

The growing demand for cloud computing motivates the need to study the security of data received, stored, processed, and transmitted by a cloud. In this paper, we present a framework for such a study. We introduce a cloud computing model that captures a rich class of big-data use-cases and allows...

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