Multiplicative Homomorphic Encryption Research Articles

Research on privacy information retrieval model based on hybrid homomorphic encryption

The computational complexity of privacy information retrieval protocols is often linearly related to database size. When the database size is large, the efficiency of privacy information retrieval protocols is relatively low. This paper designs an effective privacy information retrieval model based on hybrid fully homomorphic encryption. The assignment method is cleverly used to replace a large number of homomorphic encryption operations. At the same time, the multiplicative homomorphic encryption scheme is first used to deal with the large-scale serialization in the search, and then the fully homomorphic encryption scheme is used to deal with the remaining simple operations. The depth of operations supported by the fully homomorphic scheme no longer depends on the size of the database, but only needs to support the single homomorphic encryption scheme to decrypt the circuit depth. Based on this hybrid homomorphic encryption retrieval model, the efficiency of homomorphic privacy information retrieval model can be greatly improved.

Design and realization of a secure multiplicative homomorphic encryption scheme for cloud services

Design and realization of a secure multiplicative homomorphic encryption scheme for cloud services

LPCP: An efficient Privacy-Preserving Protocol for Polynomial Calculation Based on CRT

With the development of privacy-preserving techniques, the increasing demand for secure multiparty computation (MPC) of mobile devices has become a significant challenge. Unfortunately, it is inapplicable for mobile devices to implement the existing secure multiparty computation schemes that rely on costly computation and communication overhead. To solve this problem, we propose an efficient two-party computation protocol secure against semi-honest adversary based on the Chinese remainder theorem (CRT). Our protocol utilizes CRT-based encryption and re-encryption techniques to realize additional and multiplicative homomorphic encryption, which can be transformed into a two-party secure computation scheme. Then, we extend our two-party LPCP protocol into a multiparty LPCP protocol, which is much faster and more space saving than the previous works. For practical purpose, we describe a distance measurement application for mobile devices based on LPCP. In the end, we implement LPCP codes and compare the experimental results to the state-of-the-art two-party and multiparty computation protocols. The experimental result shows that the high computation and communication efficiency of LPCP makes it possible for low computing-power mobile devices to implement multiparty secure computation protocols in reality.

Provable Data Possession using Additive Homomorphic Encryption

Efficiency, public verification, and robustness are essential characteristics of data possession schemes. The efficiency of such kinds of Provable Data Possession (PDP) schemes is possible due to homomorphic encryption, which is used to verify the integrity of data. Most of the existing schemes use multiplicative homomorphic encryption. The multiplicative homomorphic encryption is unsuitable for the low configured devices, which are quite constrained in terms of computation and storage. In this work, we have provided the solution using additive homomorphic encryption techniques like Paillier, ElGamal and Elliptic Curve Cryptosystem (ECC). The proposed solution is based on ECC, which requires less time to execute setup, tag generation, proof generation and proof verification phases to provide public verifiability. The proposed solution is secured under a random Oracle model. Correctness analysis of the proposed algorithm is given at the end of the algorithm.

Development and Examination of Fog Computing-Based Encrypted Control System

This letter develops a fog computing-based encrypted control system in a practical industrial setting. The developed system conceals controller gains and signals over communication links using multiplicative homomorphic encryption to prevent eavesdropping attacks. Experimental validation confirms the feasibility of position servo control for the motor-driven stage with the developed system in terms of performance degradation, parameter variation, and processing time. The developed system inherits its stability regardless of whether plant parameters fluctuate or not even after the controller gains and signals are encrypted. Furthermore, although processing time becomes longer by increasing a key length of encryption, degradation of control performance is improved simultaneously.

Efficient confidentiality-preserving data analytics over symmetrically encrypted datasets

In the past decade, cloud computing has emerged as an economical and practical alternative to in-house datacenters. But due to security concerns, many enterprises are still averse to adopting third party clouds. To mitigate these concerns, several authors have proposed to use partially homomorphic encryption (PHE) to achieve practical levels of confidentiality while enabling computations in the cloud. However, these approaches are either not performant or not versatile enough. We present two novel PHE schemes, an additive and a multiplicative homomorphic encryption scheme, which, unlike previous schemes, are symmetric. We prove the security of our schemes and show they are more efficient than state-of-the-art asymmetric PHE schemes, without compromising the expressiveness of homomorphic operations they support. The main intuition behind our schemes is to trade strict ciphertext compactness for good "relative" compactness in practice, while in turn reaping improved performance. We build a prototype system called Symmetria that uses our proposed schemes and demonstrate its performance improvements over previous work. Symmetria achieves up to 7× average speedups on standard benchmarks compared to asymmetric PHE-based systems.

Research and analysis on sensitive data encryption method in accounting information processing system

In order to protect the confidentiality and integrity of sensitive data in accounting information processing system, it was necessary to study the sensitive data encryption method. The current encryption method was mainly used different technology to make encryption for the sensitivity of sensitive data, which caused a problem of poor security. In order to improve the security of encryption, a hybrid encryption method for sensitive data of accounting information processing system was proposed. Firstly, the sensitive data was preprocessed. Then, based on the elliptic curve encryption mechanism, the additive and multiplicative homomorphic encryption methods of sensitive data were constructed respectively. Experimental results showed that the cryptographic running time obtained by our proposed method was relatively small and the increase in decryption computation overhead was smaller than the traditional method which was good to improve encryption security.

Security Framework for Cloud Computing using Fragmentation and Homomorphic Encryption

An invention of cloud computing technology comes with numerous benefits for IT industries and others. The data store in the cloud can be easily shared among stakeholders irrespective of their location, i.e. data availability is very good. Nowadays organizations are switching to cloud platform for storing and sharing data in a decentralized manner. This is significantly reduces the economically burden to the organization. As the data are accessible through network, so major concern is to maintain the data confidentiality. Data breach in any form organization losses their trustworthy, and this affect the reputation of the organization. This is very important to maintain the privacy and security of data all the time. There are so many works has been proposed by many researchers to secure data in the cloud by using various encryption techniques. In this paper, we proposed a security mechanism to maintain confidentiality of data. This method is combination of multiplicative homomorphic encryption algorithms along with vertical fragmentation of data. We have tested our scheme based on crypto delays, communication delays, and query processing delays with an existing work. The results obtained show that our method out-perform the existing work. The results obtained show improvement with the proposed method.

Improved Data Integrity Proofs using Additive Homomorphic Encryption for Remote Storage

Background/Objectives: Remote data storage becomes the hype nowadays as various organizations provide free access of the application. Security and efficiency are the major concerns while using such kind of application. Hence solution related to data integrity verification needs to be focused to achieve reliability. Methods/Statistical Analysis: Despite of all the hype surrounding the storage and security solutions, clients are still hesitant to deploy their business in the cloud. As security is the major concerns which may become the hindrance as clients are more concern about data privacy and data protection. In proposed work we have provided solution of efficiency and security related to remote data storage using additive homomorphic encryption. Findings: Solution to this can be provided using some of the data integrity proofs techniques. The advent of an advanced model of the security to provide the solution should not negotiate with the required efficiency and reliability present in the current solutions. Additive homomorphic encryption has been proven to efficient compared to multiplicative homomorphic encryption. Additive homomorphic encryption is efficient compare to multiplicative homomorphic encryption which provides better efficiency. Applications/Improvements: Methodology given could be useful for remote file storage applications. Proposed algorithm has been implemented and tested. The results shows that it gives improvement over the existing solution in terms of tag generation and verification.