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About 1,953 papers for “Functional encryption”

Functional Encryption

Romain Gay · 2023

Abstract Functional encryption gives users fine-grained access to the encrypted data and permits the computation of specific functions on the protected plaintexts. Namely, data is encrypted using a public key, while restricted keys that correspond to particular functions are generated. This prevents the computer from computing anything other than the function specified by the restricted decrypting key. Functional encryption can handle more sophisticated data sharing involving an untrusted cloud. Finally, functional encryption is to become an increasingly valuable tool in the context of growing concern for privacy and the ubiquitous use of data.

Cited by 0Open access

Controlled Functional Encryption

Muhammad Naveed, Shashank Agrawal, Manoj Prabhakaran et al. · 2014

Motivated by privacy and usability requirements in various scenarios where existing cryptographic tools (like secure multi-party computation and functional encryption) are not adequate, we introduce a new cryptographic tool called Controlled Functional Encryption (C-FE). As in functional encryption, C-FE allows a user (client) to learn only certain functions of encrypted data, using keys obtained from an authority. However, we allow (and require) the client to send a fresh key request to the authority every time it wants to evaluate a function on a ciphertext. We obtain efficient solutions by carefully combining CCA2 secure public-key encryption (or rerandomizable RCCA secure public-key encryption, depending on the nature of security desired) with Yao's garbled circuit. Our main contributions in this work include developing and for- mally defining the notion of C-FE; designing theoretical and practical constructions of C-FE schemes achieving these definitions for specific and general classes of functions; and evaluating the performance of our constructions on various application scenarios.

Cited by 60

Hierarchical Functional Encryption

Zvika Brakerski, Nishanth Chandran, Vipul Goyal et al. · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · 2017

Functional encryption provides fine-grained access control for encrypted data, allowing each user to learn only specific functions of the encrypted data. We study the notion of hierarchical functional encryption, which augments functional encryption with delegation capabilities, offering significantly more expressive access control. We present a generic transformation that converts any general-purpose public-key functional encryption scheme into a hierarchical one without relying on any additional assumptions. This significantly refines our understanding of the power of functional encryption, showing that the existence of functional encryption is equivalent to that of its hierarchical generalization. Instantiating our transformation with the existing functional encryption schemes yields a variety of hierarchical schemes offering various trade-offs between their delegation capabilities (i.e., the depth and width of their hierarchical structures) and underlying assumptions. When starting with a scheme secure against an unbounded number of collusions, we can support arbitrary hierarchical structures. In addition, even when starting with schemes that are secure against a bounded number of collusions (which are known to exist under rather minimal assumptions such as the existence of public-key encryption and shallow pseudorandom generators), we can support hierarchical structures of bounded depth and width.

Cited by 9Open access

Functional Encryption Without Obfuscation

Sanjam Garg, Craig Gentry, Shai Halevi et al. · 2014

Previously known functional encryption (FE) schemes for general circuits relied on indistinguishability obfuscation, which in turn either relies on an exponential number of assumptions (basically, one per circuit), or a polynomial set of assumptions, but with an exponential loss in the security reduction. Additionally most of these schemes are proved in the weaker selective security model, where the adversary is forced to specify its target before seeing the public parameters. For these constructions, full security can be obtained but at the cost of an exponential loss in the security reduction. In this work, we overcome the above limitations and realize an adaptively secure functional encryption scheme without using indistinguishability obfuscation. Specifically the security of our scheme relies only on the polynomial hardness of simple assumptions on composite order multilinear maps. Though we do not currently have secure instantiations for these assumptions, we expect that multilinear maps supporting these assumptions will discovered in the future. Alternatively, follow up results may yield constructions which can be securely instantiated. As a separate technical contribution of independent interest, we show how to add to existing graded encoding schemes a new extension function, that can be thought of as dynamically introducing new encoding levels.

Cited by 0

Advances in Functional Encryption

Hoeteck Wee · HAL (Le Centre pour la Communication Scientifique Directe) · 2016

Functional encryption is a novel paradigm for public-key encryption that enables both fine-grained access control and selective computation on encrypted data, as is necessary to protect big, complex data in the cloud. In this thesis, I provide a brief introduction to functional encryption, and an overview of my contributions to the area.

Cited by 0Open access

Multi-Input Functional Encryption

S. Dov, Gordon Jonathan, Katz Feng-hao et al. · 2015

Functional encryption (FE) is a powerful primitive enabling fine-grained access to encrypted data. In an FE scheme, secret keys (“tokens”) correspond to functions; a user in possession of a ciphertext ct = Enc(x) and a token TKf for the function f can compute f(x) but learn nothing else about x. An active area of research over the past few years has focused on the development of ever more expressive FE schemes. In this work we introduce the notion of multi-input functional encryption. Here, informally, a user in possession of a token TKf for an n-ary function f and multiple ciphertexts ct1 = Enc(x1),..., ctn = Enc(xn) can compute f(x1,..., xn) but nothing else about the {xi}. Besides introducing the notion, we explore the feasibility of multi-input FE in the public-key and symmetric-key settings, with

Cited by 0

D1.1 Homomorphic Encryption, Functional Encryption and Function Hiding

HARPOCRATES Consortium · Zenodo (CERN European Organization for Nuclear Research) · 2024

The HARPOCRATES project aims to develop solutions for private and secure data analysis and sharing. As such, this deliverable (D1.1 Homomorphic Encryption, Functional Encryption and Function Hiding) covers the cryptographic solutions developed to aid operating on encrypted data as if it was unencrypted. As such, this document covers the development of Functional Encryption (FE) as well as Homomorphic Encryption (HE) and Hybrid Homomorphic Encryption (HHE) solutions, which can be used for secure data analysis and improving the privacy of users as well as keeping proprietary models and protocols secure. Throughout this document, we cover the preliminaries of constructing both FE, HE and HHE based solutions and providethree FE constructions as well as an HHE construction for different usecases. The contents of this deliverable can be summarised as such:• In accordance to the Symmetric and Asymmetric Functional Encryption with Function Hiding task, we analyse the constructions of FE schemes and implement two FE constructions, Need for Speed and SPADE, which can be used for efficient data aggregation and data analysis without revealing the original data.• To protect proprietary software as well as provide privacy on how users analyse their data, we constructed a generic FE framework that can be appended to any messageprivate, multi-input FE scheme and transform it to a function hiding FE scheme. By doing this, an analyst can still use an FE to analyze encrypted data in privacy-preserving way but apart from keeping the data private we also hide the functions applied to the data – thus keeping the confidentiality and privacy of both the data and the utilized statistical functions.• Following the Efficient Homomorphic Encryption Schemes task, we analyse the advantages and limitations of HE and HHE schemes by evaluating the efficiency of HHE when compared to standard HE. Additionally, we analyse the security of these schemes and show their robustness against malicious adversaries.• We build upon HHE schemes and expand them to a new use case for Privacy-Preserving Machine Learning (PPML). This results in GuardML, a realistic solution that allows to run secure machine learning on encrypted data for a variety of users and devices

Cited by 0Open access

Framework for Investigating Functional Encryption

Singh, Gaurav (Gaurav J.) · DSpace@MIT (Massachusetts Institute of Technology) · 2016

Thesis: M. Eng. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.

Cited by 0Open access

Functional encryption for quadratic functions

Josef Sýkora · Digital Repository (National Repository of Grey Literature) · 2022

In this thesis we will be studying functional encryption for quadratic functions. We want to encrypt a message, in form of a vector, z to a plaintext ct and create a secret key skf for a quadratic function f, which will allow us to decrypt ct to f(z), while the ct and skf will not leak any information about z. We will introduce one concrete design. The aim of this thesis will be the preparation of necessary preliminaries, which will allow us to describe the design, and to verify correctness of the algorithms. We will describe Arithmetic Branching Programs. Such objects will help us represent function f. Furthermore, we will introduce Garbling and Partial Garbling schemes. Those will allow us to "randomize"a part of the algorithm. We will also specify an encryption algorithm for linear transformation and use it to describe the main encryption algorithm for quadratic functions. 1

Cited by 0

Selective Opening Secure Functional Encryption

Yuanyuan Ji, Haixia Xu, Peili Li · 2015

Functional encryption (FE) has more fine-grained control to encrypted data than traditional encryption schemes. The well-accepted security of FE is indistinguishability-based security (IND-FE) and simulation-based security (SIMFE), but the security is not sufficient. For example, if an adversary has the ability to access a vector of ciphertexts and can ask to open some information of the messages, such as coins used in the encryption or secret key in multikey setting, whether the privacy of the unopened messages is guaranteed. This is called selective opening attack (SOA).

Cited by 0Open access