Integer-based fully homomorphic encryption

The concept of fully homomorphic encryption has been considered the holy grail of cryptography since the discovery of secure public key cryptography in the 1970s. Fully homomorphic encryption allows arbitrary computation on encrypted data to be performed securely. Craig Gentry\u27s new method of bootstrapping introduced in 2009 provides a technique for constructing fully homomorphic cryptosystems. In this paper we explore one such bootstrappable system based on simple integer arithmetic in a manner that someone without a high level of experience in homomorphic encryption can readily understand. Further, we present an implementation of the system as well as a lattice- based attack. We present performance results of our implementation under various parameter choices and the resistance of the system to the lattice-based attack under those parameters. Unfortunately, while the system is very interesting from a theoretical point of view, the results show that it is still not feasible for use

Enhanced fully homomorphic encryption scheme using modified key generation for cloud environment

Fully homomorphic encryption (FHE) is a special class of encryption that allows performing unlimited mathematical operations on encrypted data without decrypting it. There are symmetric and asymmetric FHE schemes. The symmetric schemes suffer from the semantically security property and need more performance improvements. While asymmetric schemes are semantically secure however, they pose two implicit problems. The first problem is related to the size of key and ciphertext and the second problem is the efficiency of the schemes. This study aims to reduce the execution time of the symmetric FHE scheme by enhancing the key generation algorithm using the Pick-Test method. As such, the Binary Learning with Error lattice is used to solve the key and ciphertext size problems of the asymmetric FHE scheme. The combination of enhanced symmetric and asymmetric algorithms is used to construct a multi-party protocol that allows many users to access and manipulate the data in the cloud environment. The Pick-Test method of the Sym-Key algorithm calculates the matrix inverse and determinant in one instance requires only n-1 extra multiplication for the calculation of determinant which takes 0(N3) as a total cost, while the Random method in the standard scheme takes 0(N3) to find matrix inverse and 0(N!) to calculate the determinant which results in 0(N4) as a total cost. Furthermore, the implementation results show that the proposed key generation algorithm based on the pick-test method could be used as an alternative to improve the performance of the standard FHE scheme. The secret key in the Binary-LWE FHE scheme is selected from {0,1}n to obtain a minimal key and ciphertext size, while the public key is based on learning with error problem. As a result, the secret key, public key and tensored ciphertext is enhanced from logq , 0(n2log2q) and ((n+1)n2log2q)2log q to n, (n+1)2log q and (n+1)2log q respectively. The Binary-LWE FHE scheme is a secured but noise-based scheme. Hence, the modulus switching technique is used as a noise management technique to scale down the noise from e and c to e/B and c/B respectively thus, the total cost for noise management is enhanced from 0(n3log2q) to 0(n2log q) . The Multi-party protocol is constructed to support the cloud computing on Sym-Key FHE scheme. The asymmetric Binary-LWE FHE scheme is used as a small part of the protocol to verify the access of users to any resource. Hence, the protocol combines both symmetric and asymmetric FHE schemes which have the advantages of efficiency and security. FHE is a new approach with a bright future in cloud computing

Survey of Homomorphic schemes

Homomorphic encryption is increasingly becoming popular among researchers due to its future promises.Homomorphic encryption is a solution that allows a third party to process data in encrypted form. The decryption keys need not be shared.This paper summarizes the concept of homomorphic encryption and the work has been done in this field

A Hybrid Multi-user Cloud Access Control based Block Chain Framework for Privacy Preserving Distributed Databases

Most of the traditional medical applications are insecure and difficult to compute the data integrity with variable hash size. Traditional medical data security systems are insecure and it depend on static parameters for data security. Also, distributed based cloud storage systems are independent of integrity computational and data security due to unstructured data and computational memory. As the size of the data and its dimensions are increasing in the public and private cloud servers, it is difficult to provide the machine learning based privacy preserving in cloud computing environment. Block-chain technology plays a vital role for large cloud databases. Most of the conventional block-chain frameworks are based on the existing integrity and confidentiality models. Also, these models are based on the data size and file format. In this model, a novel integrity verification and encryption framework is designed and implemented in cloud environment.  In order to overcome these problems in the cloud computing environment, a hybrid integrity and security-based block-chain framework is designed and implemented on the large distributed databases. In this framework,a novel decision tree classifier is used along with non-linear mathematical hash algorithm and advanced attribute-based encryption models are used to improve the privacy of multiple users on the large cloud datasets. Experimental results proved that the proposed advanced privacy preserving based block-chain technology has better efficiency than the traditional block-chain based privacy preserving systems on large distributed databases

Confidential Information-Sharing for Automated Sustainability Benchmarks

The pressure on enterprises to manage and improve their environmental sustainability is steadily increasing. Despite the growing awareness in the IS community and business practice, current IS solutions remain in an initial state. Sustainability benchmarking is seen as a novel and effective tool in this context. However, sustainability benchmarking faces two major obstacles: First, the heterogeneity of the data requires significant pre-processing, and, second, the sensitivity of the data causes enterprises to reluctantly share this data. Our contribution is twofold: After analyzing the data input problem and identifying appropriate and available solutions, we present a secure sustainability benchmarking service (SBS) to overcome the information-sharing problem. Our service uses homomorphic encryption to protect the data during processing and differential privacy to protect against leakages from the reports. Finally, we evaluate in detail a prototypical implementation of this secure sustainability benchmarking service and illustrate its applicability in industry

Quantum-Safe Protocols and Application in Data Security of Medical Records

The use of traditional cryptography based on symmetric keys has been replaced with the revolutionary idea discovered by Diffie and Hellman in 1976 that fundamentally changed communication systems by ensuring a secure transmission of information over an insecure channel. Nowadays public key cryptography is frequently used for authentication in e-commerce, digital signatures and encrypted communication. Most of the public key cryptosystems used in practice are based on integer factorization (the famous RSA cryptosystem proposed by Rivest, Shamir and Adlemann), respectively on the discrete logarithm (in finite curves or elliptic curves). However these systems suffer from two potential drawbacks like efficiency because they must use large keys to maintain security and of course security breach with the advent of the quantum computer as a result of Peter Shor\u27s discovery in 1999 of the polynomial algorithm for solving problems such factorization of integers and discrete logarithm

Circuit Privacy for FHEW/TFHE-Style Fully Homomorphic Encryption in Practice

A fully homomorphic encryption (FHE) scheme allows a client to encrypt and delegate its data to a server that performs computation on the encrypted data that the client can then decrypt. While FHE gives confidentiality to clients\u27 data, it does not protect the server\u27s input and computation. Nevertheless, FHE schemes are still helpful in building delegation protocols that reduce communication complexity, as FHE ciphertext\u27s size is independent of the size of the computation performed on them. We can further extend FHE by a property called circuit privacy, which guarantees that the result of computing on ciphertexts reveals no information on the computed function and the inputs of the server. Thereby, circuit private FHE gives rise to round optimal and communication efficient secure two-party computation protocols. Unfortunately, despite significant efforts and much work put into the efficiency and practical implementations of FHE schemes, very little has been done to provide useful and practical FHE supporting circuit privacy. In this work, we address this gap and design the first randomized bootstrapping algorithm whose single invocation sanitizes a ciphertext and, consequently, serves as a tool to provide circuit privacy. We give an extensive analysis, propose parameters, and provide a C++ implementation of our scheme. Our bootstrapping can sanitize a ciphertext to achieve circuit privacy at an 80-bit statistical security level in 1.4 seconds. In addition, we can perform non-sanitized bootstrapping in around 0.14 seconds on a laptop without additional public keys. Crucially, we do not need to increase the parameters significantly to perform computation before or after the sanitization takes place. For comparison\u27s sake, we revisit the Ducas-Stehl\\u27e washing machine method. In particular, we give a tight analysis, estimate efficiency, review old and provide new parameters

Notes on Lattice-Based Cryptography

Asymmetrisk kryptering er avhengig av antakelsen om at noen beregningsproblemer er vanskelige å løse. I 1994 viste Peter Shor at de to mest brukte beregningsproblemene, nemlig det diskrete logaritmeproblemet og primtallsfaktorisering, ikke lenger er vanskelige å løse når man bruker en kvantedatamaskin. Siden den gang har forskere jobbet med å finne nye beregningsproblemer som er motstandsdyktige mot kvanteangrep for å erstatte disse to. Gitterbasert kryptografi er forskningsfeltet som bruker kryptografiske primitiver som involverer vanskelige problemer definert på gitter, for eksempel det korteste vektorproblemet og det nærmeste vektorproblemet. NTRU-kryptosystemet, publisert i 1998, var et av de første som ble introdusert på dette feltet. Problemet Learning With Error (LWE) ble introdusert i 2005 av Regev, og det regnes nå som et av de mest lovende beregningsproblemene som snart tas i bruk i stor skala. Å studere vanskelighetsgraden og å finne nye og raskere algoritmer som løser den, ble et ledende forskningstema innen kryptografi. Denne oppgaven inkluderer følgende bidrag til feltet: - En ikke-triviell reduksjon av Mersenne Low Hamming Combination Search Problem, det underliggende problemet med et NTRU-lignende kryptosystem, til Integer Linear Programming (ILP). Særlig finner vi en familie av svake nøkler. - En konkret sikkerhetsanalyse av Integer-RLWE, en vanskelig beregningsproblemvariant av LWE, introdusert av Gu Chunsheng. Vi formaliserer et meet-in-the-middle og et gitterbasert angrep for denne saken, og vi utnytter en svakhet ved parametervalget gitt av Gu, for å bygge et forbedret gitterbasert angrep. - En forbedring av Blum-Kalai-Wasserman-algoritmen for å løse LWE. Mer spesifikt, introduserer vi et nytt reduksjonstrinn og en ny gjetteprosedyre til algoritmen. Disse tillot oss å utvikle to implementeringer av algoritmen, som er i stand til å løse relativt store LWE-forekomster. Mens den første effektivt bare bruker RAM-minne og er fullt parallelliserbar, utnytter den andre en kombinasjon av RAM og disklagring for å overvinne minnebegrensningene gitt av RAM. - Vi fyller et tomrom i paringsbasert kryptografi. Dette ved å gi konkrete formler for å beregne hash-funksjon til G2, den andre gruppen i paringsdomenet, for Barreto-Lynn-Scott-familien av paringsvennlige elliptiske kurver.Public-key Cryptography relies on the assumption that some computational problems are hard to solve. In 1994, Peter Shor showed that the two most used computational problems, namely the Discrete Logarithm Problem and the Integer Factoring Problem, are not hard to solve anymore when using a quantum computer. Since then, researchers have worked on finding new computational problems that are resistant to quantum attacks to replace these two. Lattice-based Cryptography is the research field that employs cryptographic primitives involving hard problems defined on lattices, such as the Shortest Vector Problem and the Closest Vector Problem. The NTRU cryptosystem, published in 1998, was one of the first to be introduced in this field. The Learning With Error (LWE) problem was introduced in 2005 by Regev, and it is now considered one of the most promising computational problems to be employed on a large scale in the near future. Studying its hardness and finding new and faster algorithms that solve it became a leading research topic in Cryptology. This thesis includes the following contributions to the field: - A non-trivial reduction of the Mersenne Low Hamming Combination Search Problem, the underlying problem of an NTRU-like cryptosystem, to Integer Linear Programming (ILP). In particular, we find a family of weak keys. - A concrete security analysis of the Integer-RLWE, a hard computational problem variant of LWE introduced by Gu Chunsheng. We formalize a meet-in-the-middle attack and a lattice-based attack for this case, and we exploit a weakness of the parameters choice given by Gu to build an improved lattice-based attack. - An improvement of the Blum-Kalai-Wasserman algorithm to solve LWE. In particular, we introduce a new reduction step and a new guessing procedure to the algorithm. These allowed us to develop two implementations of the algorithm that are able to solve relatively large LWE instances. While the first one efficiently uses only RAM memory and is fully parallelizable, the second one exploits a combination of RAM and disk storage to overcome the memory limitations given by the RAM. - We fill a gap in Pairing-based Cryptography by providing concrete formulas to compute hash-maps to G2, the second group in the pairing domain, for the Barreto-Lynn-Scott family of pairing-friendly elliptic curves.Doktorgradsavhandlin