Homomorphic Encryption (HE) is a powerful cryptographic primitive to address privacy and security issues in outsourcing computation on sensitive data to an untrusted computation environment. Comparing to secure Multi-...
详细信息
ISBN:
(纸本)9781450356930
Homomorphic Encryption (HE) is a powerful cryptographic primitive to address privacy and security issues in outsourcing computation on sensitive data to an untrusted computation environment. Comparing to secure Multi-Party Computation (MPC), HE has advantages in supporting non-interactive operations and saving on communication costs. However, it has not come up with an optimal solution for modern learning frameworks, partially due to a lack of efficient matrix computation mechanisms. In this work, we present a practical solution to encrypt a matrix homomorphically and perform arithmetic operations on encrypted matrices. Our solution includes a novel matrix encoding method and an efficient evaluation strategy for basic matrix operations such as addition, multiplication, and transposition. We also explain how to encrypt more than one matrix in a single ciphertext, yielding better amortized performance. Our solution is generic in the sense that it can be applied to most of the existing HE schemes. It also achieves reasonable performance for practical use;for example, our implementation takes 9.21 seconds to multiply two encrypted square matrices of order 64 and 2.56 seconds to transpose a square matrix of order 64. Our secure matrix computation mechanism has a wide applicability to our new framework E2DM, which stands for encrypted data and encrypted model. To the best of our knowledge, this is the first work that supports secure evaluation of the prediction phase based on both encrypted data and encrypted model, whereas previous work only supported applying a plain model to encrypted data. As a benchmark, we report an experimental result to classify handwritten images using convolutional neural networks (CNN). Our implementation on the MNIST dataset takes 28.59 seconds to compute ten likelihoods of 64 input images simultaneously, yielding an amortized rate of 0.45 seconds per image.
In 2009, Craig Gentry introduced the first "fully" homomorphic encryption scheme allowing arbitrary circuits to be evaluated on encrypted data [17]. Homomorphic encryption is a very powerful cryptographic pr...
详细信息
ISBN:
(纸本)9781450356930
In 2009, Craig Gentry introduced the first "fully" homomorphic encryption scheme allowing arbitrary circuits to be evaluated on encrypted data [17]. Homomorphic encryption is a very powerful cryptographic primitive, though it has often been viewed by practitioners as too inefficient for practical applications. However, the performance of these encryption schemes has come a long way from that of Gentry's original work: there are now several well-maintained libraries implementing homomorphic encryption schemes and protocols demonstrating impressive performance results, alongside an ongoing standardization effort by the community. In this tutorial we survey the existing homomorphic encryption landscape, providing both a general overview of the state of the art, as well as a deeper dive into several of the existing libraries. We aim to provide a thorough introduction to homomorphic encryption accessible by the broader computer security community. Several of the presenters are core developers of well-known publicly available homomorphic encryption libraries, and organizers of the homomorphic encryption standardization effort *** [2]. This tutorial is targeted at application developers, security researchers, privacy engineers, graduate students, and anyone else interested in learning the basics of modern homomorphic encryption. The tutorial is divided into two parts: Part I is accessible by everyone comfortable with basic college-level math;Part II will cover more advanced topics, including descriptions of some of the different homomorphic encryption schemes and libraries, concrete example applications and code samples, and a deeper discussion on implementation challenges. Part II requires the audience to be familiar with modern C++.
The proceedings contain 40 papers. The topics discussed include: DBMask: fine-grained access control on encrypted relational databases;differentially-private mining of moderately-frequent high-confidence association r...
ISBN:
(纸本)9781450331913
The proceedings contain 40 papers. The topics discussed include: DBMask: fine-grained access control on encrypted relational databases;differentially-private mining of moderately-frequent high-confidence association rules;StaDynA: addressing the problem of dynamic code updates in the security analysis of android applications;CoinParty: secure multi-party mixing of bitcoins;how your phone camera can be used to stealthily spy on you: transplantation attacks against android camera service;Pleco and Plectron two provably secure password hashing algorithms;one thing leads to another: credential based privilege escalation;epidemic behavior of negative users in online social sites;rapid screening of transformed data leaks with efficient algorithms and parallel computing;ABSS: an attribute-based sanitizable signature for integrity of outsourced database with public cloud;and privacy-preserving scanning of big content for sensitive data exposure with MapReduce.
The proceedings contain 129 papers. The topics discussed include: influence factors on the quality of user experience in OS reliability: a qualitative experimental study;finally Johnny can encrypt. but does this make ...
ISBN:
(纸本)9781450364485
The proceedings contain 129 papers. The topics discussed include: influence factors on the quality of user experience in OS reliability: a qualitative experimental study;finally Johnny can encrypt. but does this make him feel more secure?;an efficient cryptography-based access control using inner-product proxy re-encryption scheme;non-interactive key exchange from identity-based encryption;the other side of the coin: a framework for detecting and analyzing web-based cryptocurrency mining campaigns;a pyramidal-based model to compute the impact of cyber security events;together: towards automatic investigation of Android malware cyber-infrastructures;attack graph-based assessment of exploitability risks in automotive on-board networks;comparison of data flow error detection techniques in embedded systems: an empirical study;distributed and cooperative firewall/controller in cloud environments;an investigation of a deep learning based malware detection system;towards the automatic generation of low-interaction web application HoneyPots;assessing internet-wide cyber situational awareness of critical sectors;spreading alerts quietly: new insights from theory and practice;what are security patterns? a formal model for security and design of software;and a NLP-based solution to prevent from privacy leaks in social network posts.
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