Abstract The National Institute of Standards and Technology (NIST) has been working on standardization of post-quantum cryptography and is approaching the end of round-3 evaluation of algorithms. Key reuse security evaluation is an important part of algorithm evaluation. In order to evaluate the key reuse security of candidate IND-CPA PKEs, at Eurocrypt’19, B$\breve{\text{a}}$etu et al. proposed a classical key recovery under plaintext checking attack (KR-PCA) which can recover the reused secret keys by querying an oracle thousands of times. However, the method does not work for cryptosystems which shorten ciphertexts by rounding off the low bits, such as round-3 finalists Kyber and Saber. Subsequently, Dumittan and Vaudenay (ACNS’20) and Qin et al. (ASIACRYPT’21) came up with new effective methods, which require carefully constructed queries. In this paper, we propose an automatic method to recover the reused secret keys of IND-CPA PKEs in Kyber and Saber. Instead of constructing queries carefully, our method uses automated search combined with an optimized bruteforce. The effect and cost of the method depend on the specific parameters. In particular, we can recover the secret keys after thousands of queries in all parameter sets, which is comparable with the current best result.

The Boolean functions satisfying secure properties on the restricted sets of inputs are studied recently due to their importance in the framework of the FLIP stream cipher. However, finding Boolean functions with optimal cryptographic properties is an open research problem in the cryptographic community. This paper presents an Improved Genetic Algorithm (IGA) with the directed changes that keep the weightwise balancedness of Boolean functions. A cross-protection strategy is proposed to ensure that the offspring has the same weightwise balancedness characteristics of the parents while implementing crossover. Then, a large number of weightwise (almost) perfectly balanced (W(A)PB) functions with a good nonlinearity profile are obtained based on IGA. Finally, we make comparisons between our constructions and relevant works. The comparisons show that IGA has a significant advantage for reaching the W(A)PB functions with high weightwise nonlinearity. Moreover, it is the first time to obtain the 8-variable WPB functions with the weightwise nonlinearity of 28 in the restricted sets of inputs with Hamming weight of 4, and list the statistical indicators of the weightwise nonlinearity for W(A)PB functions for input size n = 9, 10.

With the deepening of research, how to construct a fully homomorphic signcryption scheme based on standard assumptions is a problem that we need to solve. For this question, recently, Jin et al. proposed a leveled fully homomorphic signcryption scheme from standard lattices. However, when verifying, it is supposed to unsigncrypt first as they utilize sign‐then‐encrypt method. This leads to users being unable to verify the authenticity of the data first, which resulting in the waste of resources. This raises another question of how to construct an fully homomorphic signcryption (FHSC) scheme with public verifiability. To solve this problem, we propose a leveled fully homomorphic signcryption scheme that can be publicly verified and show its completeness, IND‐CPA security, and strong unforgeability.

This letter addresses some security issues of an identity-based provable data possession protocol with compressed cloud storage (published in IEEE TIFS, doi:10.1109/TIFS.2022. 3159152). Some serious flaws are identified and an attack to the protocol is designed. This attack is able to recover the ephemeral secret keys from two encrypted blocks with high probability to reveal the original plaintext file completely. Moreover, an adversary can impersonate a data owner to outsource any file to the cloud in a malicious way. The main ingredients of the attack is some classical number theoretic results.

With the vigorous development and gradual maturity of machine learning (ML) technologies, the AI-assisted disease diagnosis and prediction ($\mathcal {AADP}$) system has been extensively studied and can be expected to be intensively deployed in the real world. However, as the scale of ML data increases exponentially, the training and application of ML models impose a great burden on resource-constrained terminals. Designing cloud/edge server-aided$\mathcal {AADP}$protocols is becoming a popular topic. Whereas, the sensitivity of ML data, the intellectual property of ML models, and the uncontrollability of servers bring great security challenges to this promising computing paradigm. In this article, we initialize a new four-party framework for the$\mathcal {AADP}$system which consists of users, third-party test institution, AI doctor, and cloud/edge server. With this framework, we design two high-efficiency and secure outsourcing$\mathcal {AADP}$protocols under two different security models. By comprehensively employing secure hash functions, Householder transformations, and random permutations, we realize the following design objectives: 1) user’s actual identification is invisible to the other parties; 2) user’s feature vector is blinded to the AI doctor and the server; 3) the ML model of the AI doctor is confidential to the server; 4) AI doctor can obtain decent computational savings compared with achieving the diagnosis task by itself; and 5) AI doctor can verify the server’s misbehaviors with a nonnegligible probability under the security model with a fully malicious server. We argue these claims with rigid theoretical proofs and corroborate them with extensive experimental analysis.

Abstract There is an increasing trend for data owners to outsource their data to an untrusted cloud provider. Besides providing the storage for the data, the service provider could allow the data owner or authorized clients to search over the data. To guarantee the data secure, the owner must encrypt his or her data before sending to the cloud. However, traditional encryption does not allow searching without decrypting the data. Searchable symmetric encryption is one approach that allows users to search over the encrypted data. For data applications, various different functional search have been proposed, such as wildcard search, similarity keyword search and fuzzy keyword search. Moreover, dynamic addition and removal of files should be supported in practice. However, to our knowledge, there does not exist a searchable symmetric encryption scheme that can support many properties such as more than three functions in all the aforementioned operations. In this paper, we propose an efficient multi‐functional searchable symmetric encryption scheme that can support wildcard search, similarity search (including hamming distance and edit distance), fuzzy keyword search and disjunctive keyword search simultaneously. In the new scheme, the trapdoor changes with various search requests and it enumerates all possibilities of the keyword of the trapdoor. Moreover, we use an array instead of a matrix to reduce the storage, and the scheme can be constructed efficiently in terms of both computational and space complexity. Our scheme is based on the Bloom filter, and it is secure against non‐adaptive chosen keyword attack. With the dynamic technique for the inverted index, our scheme can support dynamic operation such as addition and removal of data files, which can also be secure against adaptive chosen keyword attack. Copyright © 2015 John Wiley & Sons, Ltd.