A fast single server private information retrieval protocol with low communication cost

Existing single server Private Information Retrieval (PIR) protocols are far from practical. To be practical, a single server PIR protocol has to be both communicationally and computationally efficient. In this paper, we present a single server PIR protocol that has low communication cost and is much faster than existing protocols. A major building block of the PIR protocol in this paper is a tree-based compression scheme, which we call folding/unfolding. This compression scheme enables us to lower the communication complexity to O(loglogn). The other major building block is the BGV fully homomorphic encryption scheme. We show how we design the protocol to exploit the internal parallelism of the BGV scheme. This significantly reduces the server side computational overhead and makes our protocol much faster than the existing protocols. Our protocol can be further accelerated by utilising hardware parallelism. We have built a prototype of the protocol. We report on the performance of our protocol based on the prototype and compare it with the current most efficient protocols

On the IND-CCA1 Security of FHE Schemes

Fully homomorphic encryption (FHE) is a powerful tool in cryptography that allows one to perform arbitrary computations on encrypted material without having to decrypt it first. There are numerous FHE schemes, all of which are expanded from somewhat homomorphic encryption (SHE) schemes, and some of which are considered viable in practice. However, while these FHE schemes are semantically (IND-CPA) secure, the question of their IND-CCA1 security is much less studied, and we therefore provide an overview of the IND-CCA1 security of all acknowledged FHE schemes in this paper. To give this overview, we grouped the SHE schemes into broad categories based on their similarities and underlying hardness problems. For each category, we show that the SHE schemes are susceptible to either known adaptive key recovery attacks, a natural extension of known attacks, or our proposed attacks. Finally, we discuss the known techniques to achieve IND-CCA1-secure FHE and SHE schemes. We concluded that none of the proposed schemes were IND-CCA1-secure and that the known general constructions all had their shortcomings.publishedVersio

A HYBRIDIZED ENCRYPTION SCHEME BASED ON ELLIPTIC CURVE CRYPTOGRAPHY FOR SECURING DATA IN SMART HEALTHCARE

Recent developments in smart healthcare have brought us a great deal of convenience. Connecting common objects to the Internet is made possible by the Internet of Things (IoT). These connected gadgets have sensors and actuators for data collection and transfer. However, if users' private health information is compromised or exposed, it will seriously harm their privacy and may endanger their lives. In order to encrypt data and establish perfectly alright access control for such sensitive information, attribute-based encryption (ABE) has typically been used. Traditional ABE, however, has a high processing overhead. As a result, an effective security system algorithm based on ABE and Fully Homomorphic Encryption (FHE) is developed to protect health-related data. ABE is a workable option for one-to-many communication and perfectly alright access management of encrypting data in a cloud environment. Without needing to decode the encrypted data, cloud servers can use the FHE algorithm to take valid actions on it. Because of its potential to provide excellent security with a tiny key size, elliptic curve cryptography (ECC) algorithm is also used. As a result, when compared to related existing methods in the literature, the suggested hybridized algorithm (ABE-FHE-ECC) has reduced computation and storage overheads. A comprehensive safety evidence clearly shows that the suggested method is protected by the Decisional Bilinear Diffie-Hellman postulate. The experimental results demonstrate that this system is more effective for devices with limited resources than the conventional ABE when the system’s performance is assessed by utilizing standard model

Privacy-preserving outsourced calculation toolkit in the cloud

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Reusable garbled circuits and succinct functional encryption

Garbled circuits, introduced by Yao in the mid 80s, allow computing a function f on an input x without leaking anything about f or x besides f(x). Garbled circuits found numerous applications, but every known construction suffers from one limitation: it offers no security if used on multiple inputs x. In this paper, we construct for the first time reusable garbled circuits. The key building block is a new succinct single-key functional encryption scheme. Functional encryption is an ambitious primitive: given an encryption Enc(x) of a value x, and a secret key sk_f for a function f, anyone can compute f(x) without learning any other information about x. We construct, for the first time, a succinct functional encryption scheme for {\em any} polynomial-time function f where succinctness means that the ciphertext size does not grow with the size of the circuit for f, but only with its depth. The security of our construction is based on the intractability of the Learning with Errors (LWE) problem and holds as long as an adversary has access to a single key sk_f (or even an a priori bounded number of keys for different functions). Building on our succinct single-key functional encryption scheme, we show several new applications in addition to reusable garbled circuits, such as a paradigm for general function obfuscation which we call token-based obfuscation, homomorphic encryption for a class of Turing machines where the evaluation runs in input-specific time rather than worst-case time, and a scheme for delegating computation which is publicly verifiable and maintains the privacy of the computation.Natural Sciences and Engineering Research Council of Canada (NSERC Discovery Grant)United States. Defense Advanced Research Projects Agency (DARPA award FA8750-11-2-0225)United States. Defense Advanced Research Projects Agency (DARPA award N66001-10-2-4089)National Science Foundation (U.S.) (NSF award CNS-1053143)National Science Foundation (U.S.) (NSF award IIS-1065219)Google (Firm

Survey on Fully Homomorphic Encryption, Theory, and Applications

Data privacy concerns are increasing significantly in the context of Internet of Things, cloud services, edge computing, artificial intelligence applications, and other applications enabled by next generation networks. Homomorphic Encryption addresses privacy challenges by enabling multiple operations to be performed on encrypted messages without decryption. This paper comprehensively addresses homomorphic encryption from both theoretical and practical perspectives. The paper delves into the mathematical foundations required to understand fully homomorphic encryption (FHE). It consequently covers design fundamentals and security properties of FHE and describes the main FHE schemes based on various mathematical problems. On a more practical level, the paper presents a view on privacy-preserving Machine Learning using homomorphic encryption, then surveys FHE at length from an engineering angle, covering the potential application of FHE in fog computing, and cloud computing services. It also provides a comprehensive analysis of existing state-of-the-art FHE libraries and tools, implemented in software and hardware, and the performance thereof