Fourier-based Function Secret Sharing with General Access Structure

Function secret sharing (FSS) scheme is a mechanism that calculates a function f(x) for x in {0,1}^n which is shared among p parties, by using distributed functions f_i:{0,1}^n -> G, where G is an Abelian group, while the function f:{0,1}^n -> G is kept secret to the parties. Ohsawa et al. in 2017 observed that any function f can be described as a linear combination of the basis functions by regarding the function space as a vector space of dimension 2^n and gave new FSS schemes based on the Fourier basis. All existing FSS schemes are of (p,p)-threshold type. That is, to compute f(x), we have to collect f_i(x) for all the distributed functions. In this paper, as in the secret sharing schemes, we consider FSS schemes with any general access structure. To do this, we observe that Fourier-based FSS schemes by Ohsawa et al. are compatible with linear secret sharing scheme. By incorporating the techniques of linear secret sharing with any general access structure into the Fourier-based FSS schemes, we show Fourier-based FSS schemes with any general access structure.Comment: 12 page

Confidential Boosting with Random Linear Classifiers for Outsourced User-generated Data

User-generated data is crucial to predictive modeling in many applications. With a web/mobile/wearable interface, a data owner can continuously record data generated by distributed users and build various predictive models from the data to improve their operations, services, and revenue. Due to the large size and evolving nature of users data, data owners may rely on public cloud service providers (Cloud) for storage and computation scalability. Exposing sensitive user-generated data and advanced analytic models to Cloud raises privacy concerns. We present a confidential learning framework, SecureBoost, for data owners that want to learn predictive models from aggregated user-generated data but offload the storage and computational burden to Cloud without having to worry about protecting the sensitive data. SecureBoost allows users to submit encrypted or randomly masked data to designated Cloud directly. Our framework utilizes random linear classifiers (RLCs) as the base classifiers in the boosting framework to dramatically simplify the design of the proposed confidential boosting protocols, yet still preserve the model quality. A Cryptographic Service Provider (CSP) is used to assist the Cloud's processing, reducing the complexity of the protocol constructions. We present two constructions of SecureBoost: HE+GC and SecSh+GC, using combinations of homomorphic encryption, garbled circuits, and random masking to achieve both security and efficiency. For a boosted model, Cloud learns only the RLCs and the CSP learns only the weights of the RLCs. Finally, the data owner collects the two parts to get the complete model. We conduct extensive experiments to understand the quality of the RLC-based boosting and the cost distribution of the constructions. Our results show that SecureBoost can efficiently learn high-quality boosting models from protected user-generated data

Efficient UC Commitment Extension with Homomorphism for Free (and Applications)

Homomorphic universally composable (UC) commitments allow for the sender to reveal the result of additions and multiplications of values contained in commitments without revealing the values themselves while assuring the receiver of the correctness of such computation on committed values. In this work, we construct essentially optimal additively homomorphic UC commitments from any (not necessarily UC or homomorphic) extractable commitment. We obtain amortized linear computational complexity in the length of the input messages and rate 1. Next, we show how to extend our scheme to also obtain multiplicative homomorphism at the cost of asymptotic optimality but retaining low concrete complexity for practical parameters. While the previously best constructions use UC oblivious transfer as the main building block, our constructions only require extractable commitments and PRGs, achieving better concrete efficiency and offering new insights into the sufficient conditions for obtaining homomorphic UC commitments. Moreover, our techniques yield public coin protocols, which are compatible with the Fiat-Shamir heuristic. These results come at the cost of realizing a restricted version of the homomorphic commitment functionality where the sender is allowed to perform any number of commitments and operations on committed messages but is only allowed to perform a single batch opening of a number of commitments. Although this functionality seems restrictive, we show that it can be used as a building block for more efficient instantiations of recent protocols for secure multiparty computation and zero knowledge non-interactive arguments of knowledge

Ideal Tightly Couple (t,m,n) Secret Sharing

As a fundamental cryptographic tool, (t,n)-threshold secret sharing ((t,n)-SS) divides a secret among n shareholders and requires at least t, (t<=n), of them to reconstruct the secret. Ideal (t,n)-SSs are most desirable in security and efficiency among basic (t,n)-SSs. However, an adversary, even without any valid share, may mount Illegal Participant (IP) attack or t/2-Private Channel Cracking (t/2-PCC) attack to obtain the secret in most (t,n)-SSs.To secure ideal (t,n)-SSs against the 2 attacks, 1) the paper introduces the notion of Ideal Tightly cOupled (t,m,n) Secret Sharing (or (t,m,n)-ITOSS ) to thwart IP attack without Verifiable SS; (t,m,n)-ITOSS binds all m, (m>=t), participants into a tightly coupled group and requires all participants to be legal shareholders before recovering the secret. 2) As an example, the paper presents a polynomial-based (t,m,n)-ITOSS scheme, in which the proposed k-round Random Number Selection (RNS) guarantees that adversaries have to crack at least symmetrical private channels among participants before obtaining the secret. Therefore, k-round RNS enhances the robustness of (t,m,n)-ITOSS against t/2-PCC attack to the utmost. 3) The paper finally presents a generalized method of converting an ideal (t,n)-SS into a (t,m,n)-ITOSS, which helps an ideal (t,n)-SS substantially improve the robustness against the above 2 attacks

Revisiting Shared Data Protection Against Key Exposure

This paper puts a new light on secure data storage inside distributed systems. Specifically, it revisits computational secret sharing in a situation where the encryption key is exposed to an attacker. It comes with several contributions: First, it defines a security model for encryption schemes, where we ask for additional resilience against exposure of the encryption key. Precisely we ask for (1) indistinguishability of plaintexts under full ciphertext knowledge, (2) indistinguishability for an adversary who learns: the encryption key, plus all but one share of the ciphertext. (2) relaxes the "all-or-nothing" property to a more realistic setting, where the ciphertext is transformed into a number of shares, such that the adversary can't access one of them. (1) asks that, unless the user's key is disclosed, noone else than the user can retrieve information about the plaintext. Second, it introduces a new computationally secure encryption-then-sharing scheme, that protects the data in the previously defined attacker model. It consists in data encryption followed by a linear transformation of the ciphertext, then its fragmentation into shares, along with secret sharing of the randomness used for encryption. The computational overhead in addition to data encryption is reduced by half with respect to state of the art. Third, it provides for the first time cryptographic proofs in this context of key exposure. It emphasizes that the security of our scheme relies only on a simple cryptanalysis resilience assumption for blockciphers in public key mode: indistinguishability from random, of the sequence of diferentials of a random value. Fourth, it provides an alternative scheme relying on the more theoretical random permutation model. It consists in encrypting with sponge functions in duplex mode then, as before, secret-sharing the randomness

A Simplified Hierarchical Dynamic Quantum Secret Sharing Protocol with Added Features

Generalizing the notion of dynamic quantum secret sharing (DQSS), a simplified protocol for hierarchical dynamic quantum secret sharing (HDQSS) is proposed and it is shown that the protocol can be implemented using any existing protocol of quantum key distribution, quantum key agreement or secure direct quantum communication. The security of this proposed protocol against eavesdropping and collusion attacks is discussed with specific attention towards the issues related to the composability of the subprotocols that constitute the proposed protocol. The security and qubit efficiency of the proposed protocol is also compared with that of other existing protocols of DQSS. Further, it is shown that it is possible to design a semi-quantum protocol of HDQSS and in principle, the protocols of HDQSS can be implemented using any quantum state. It is also noted that the completely orthogonal-state-based realization of HDQSS protocol is possible and that HDQSS can be experimentally realized using a large number of alternative approaches.Comment: 9 pages, 1 figur

Highly-Efficient and Composable Password-Protected Secret Sharing (Or: How to Protect Your Bitcoin Wallet Online)

PPSS is a central primitive introduced by Bagherzandi et al [BJSL10] which allows a user to store a secret among n servers such that the user can later reconstruct the secret with the sole possession of a single password by contacting t+1 servers for t<n. At the same time, an attacker breaking into t of these servers - and controlling all communication channels - learns nothing about the secret (or the password). Thus, PPSS schemes are ideal for on-line storing of valuable secrets when retrieval solely relies on a memorizable password. We show the most efficient Password-Protected Secret Sharing (PPSS) to date (and its implied Threshold-PAKE scheme), which is optimal in round communication as in Jarecki et al [JKK14] but which improves computation and communication complexity over that scheme requiring a single per-server exponentiation for the client and a single exponentiation for the server. As with the schemes from [JKK14] and Camenisch et al [CLLN14], we do not require secure channels or PKI other than in the initialization stage. We prove the security of our PPSS scheme in the Universally Composable (UC) model. For this we present a UC definition of PPSS that relaxes the UC formalism of [CLLN14] in a way that enables more efficient PPSS schemes (by dispensing with the need to extract the user\u27s password in the simulation) and present a UC-based definition of Oblivious PRF (OPRF) that is more general than the (Verifiable) OPRF definition from [JKK14] and is also crucial for enabling our performance optimization

Computer-aided proofs for multiparty computation with active security

Secure multi-party computation (MPC) is a general cryptographic technique that allows distrusting parties to compute a function of their individual inputs, while only revealing the output of the function. It has found applications in areas such as auctioning, email filtering, and secure teleconference. Given its importance, it is crucial that the protocols are specified and implemented correctly. In the programming language community it has become good practice to use computer proof assistants to verify correctness proofs. In the field of cryptography, EasyCrypt is the state of the art proof assistant. It provides an embedded language for probabilistic programming, together with a specialized logic, embedded into an ambient general purpose higher-order logic. It allows us to conveniently express cryptographic properties. EasyCrypt has been used successfully on many applications, including public-key encryption, signatures, garbled circuits and differential privacy. Here we show for the first time that it can also be used to prove security of MPC against a malicious adversary. We formalize additive and replicated secret sharing schemes and apply them to Maurer's MPC protocol for secure addition and multiplication. Our method extends to general polynomial functions. We follow the insights from EasyCrypt that security proofs can be often be reduced to proofs about program equivalence, a topic that is well understood in the verification of programming languages. In particular, we show that in the passive case the non-interference-based definition is equivalent to a standard game-based security definition. For the active case we provide a new NI definition, which we call input independence