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This paper introduces a variant of the McEliece cryptosystem and employs the $(C_{1}, C_{1} + C_{2})$ -construction to generate a new code from two arbitrary linear codes. We propose an efficient hard-decision decoding algorithm for linear codes derived from the $(C_{1}, C_{1} + C_{2})$ -construction and integrate them into the McEliece framework. The security of the cryptosystem varies based on the specific codes used in the $(C_{1}, C_{1} + C_{2})$ -construction. Our proposed variant achieves a good level of security with approximately the same key size compared to one of the classic McEliece candidates of the National Institute of Standards and Technology (NIST) standardization process. Specifically, we demonstrate a 25% key size reduction for our proposed parameters compared to one of the 256-bit secured classic McEliece parameters.

For the feature selection problem, we propose an efficient privacy-preserving algorithm. Let D, F, and C be data, feature, and class sets, respectively, where the feature value x (F i) and the class label x (C) are given for each x ∈ D and F i ∈ F . For a triple (D , F , C) , the feature selection problem is to find a consistent and minimal subset F ′ ⊆ F , where 'consistent' means that, for any x , y ∈ D , x (C) = y (C) if x (F i) = y (F i) for F i ∈ F ′ , and 'minimal' means that any proper subset of F ′ is no longer consistent. On distributed datasets, we consider feature selection as a privacy-preserving problem: assume that semi-honest parties A and B have their own personal D A and D B . The goal is to solve the feature selection problem for D A ∪ D B without sacrificing their privacy. In this paper, we propose a secure and efficient algorithm based on fully homomorphic encryption, and we implement our algorithm to show its effectiveness for various practical data. The proposed algorithm is the first one that can directly simulate the CWC (Combination of Weakest Components) algorithm on ciphertext, which is one of the best performers for the feature selection problem on the plaintext. [ABSTRACT FROM AUTHOR]

In e-health systems, patients encrypt their personal health data for privacy purposes and upload them to the cloud. There exists a need for sharing patient health data with doctors for healing purposes in one's own preferred order. To achieve this fine-gained access control to delegation paths, some researchers have designed a new proxy re-encryption (PRE) scheme called autonomous path proxy re-encryption (AP-PRE), where the delegator can control the whole delegation path in a multi-hop delegation process. In this paper, we introduce a certificateless autonomous path proxy re-encryption (CLAP-PRE) using multilinear maps, which holds both the properties (i.e., certificateless, autonomous path) of certificateless encryption and autonomous path proxy re-encryption. In the proposed scheme, (a) each user has two public keys (user's identity and traditional public key) with corresponding private keys, and (b) each ciphertext is first re-encrypted from a public key encryption (PKE) scheme to an identity-based encryption (IBE) scheme and then transformed in the IBE scheme. Our scheme is an IND-CPA secure CLAP-PRE scheme under the k-multilinear decisional Diffie–Hellman (k-MDDH) assumption in the random oracle model. [ABSTRACT FROM AUTHOR]

For the feature selection problem, we propose an efficient privacy-preserving algorithm. Let D, F, and C be data, feature, and class sets, respectively, where the feature value x(Fi) and the class label x(C) are given for each x∈D and Fi∈F. For a triple (D,F,C), the feature selection problem is to find a consistent and minimal subset F′⊆F, where ‘consistent’ means that, for any x,y∈D, x(C)=y(C) if x(Fi)=y(Fi) for Fi∈F′, and ‘minimal’ means that any proper subset of F′ is no longer consistent. On distributed datasets, we consider feature selection as a privacy-preserving problem: assume that semi-honest parties A and B have their own personal DA and DB. The goal is to solve the feature selection problem for DA∪DB without sacrificing their privacy. In this paper, we propose a secure and efficient algorithm based on fully homomorphic encryption, and we implement our algorithm to show its effectiveness for various practical data. The proposed algorithm is the first one that can directly simulate the CWC (Combination of Weakest Components) algorithm on ciphertext, which is one of the best performers for the feature selection problem on the plaintext.

In e-health systems, patients encrypt their personal health data for privacy purposes and upload them to the cloud. There exists a need for sharing patient health data with doctors for healing purposes in one’s own preferred order. To achieve this fine-gained access control to delegation paths, some researchers have designed a new proxy re-encryption (PRE) scheme called autonomous path proxy re-encryption (AP-PRE), where the delegator can control the whole delegation path in a multi-hop delegation process. In this paper, we introduce a certificateless autonomous path proxy re-encryption (CLAP-PRE) using multilinear maps, which holds both the properties (i.e., certificateless, autonomous path) of certificateless encryption and autonomous path proxy re-encryption. In the proposed scheme, (a) each user has two public keys (user’s identity and traditional public key) with corresponding private keys, and (b) each ciphertext is first re-encrypted from a public key encryption (PKE) scheme to an identity-based encryption (IBE) scheme and then transformed in the IBE scheme. Our scheme is an IND-CPA secure CLAP-PRE scheme under the k-multilinear decisional Diffie–Hellman (k-MDDH) assumption in the random oracle model.

As many services have been subcontracted to the cloud, data in such services (i.e., management applications, signal processing, and so on) are stored on cloud in encrypted form for protecting user private information. In many emerging data and signal processing applications, approximate k-nearest neighbor (ANN) query is a prerequisite component for massive high-dimensional data (such as time series, biometric, signal, multimedia data, and so on). Unfortunately, existing secure ANN (SANN) methods encounter the limitation of dimensionality. To further resolve ANN query over high-dimensionally encrypted data, in this paper, we propose an effective SANN model in Euclidean space. In overview, a secure greedy partition method is carefully designed by applying locality sensitive hashing coding and an optimized linear order. Based on that, a novel partition-based SANN (SANNP) and a multi-division version mSANNP resolve SANN query by sequentially scanning a candidate set, which is produced by matching a cloak query with a map index. Our proposed solutions guarantee security and accuracy simultaneously, and reduce communication cost significantly. Meanwhile, the greedy partition method is proved to be indistinguishable secure under chosen-plaintext attack, which is the foundation of security for the proposed solutions. Through extensive experimental studies on four data sets, the proposed mechanisms outperform the state-of-the-art approaches and provide effective and tradeoff between result accuracy and communication cost.

Secure cloud storage has important applications in our big data-driven society, and to achieve secure cloud storage, we need to enforce strong access control mechanism. Proxy re-encryption (PRE) has been shown to be an effective tool of constructing cryptographically enforced access control schemes. In a traditional PRE scheme, a semi-trusted proxy can convert all ciphertexts for a delegator to ciphertexts for a delegatee once the proxy obtains the relevant re-encryption key from the delegator. In many practical applications, however, a fine-grained delegation of decryption abilities may be demanded, and thus, the notion of conditional PRE (C-PRE) is introduced, which allows only the ciphertexts satisfying a concrete condition to be converted by the proxy. In this paper, we introduce a special kind of C-PRE, sender-specified PRE (SS-PRE), which enables the delegator to delegate the decryption right of the ciphertexts from a specified sender to his/her delegatee. We give a formal definition of SS-PRE and its security model. We also provide the concrete constructions of an IND-CPA secure SS-PRE scheme and an IND-CCA secure SS-PRE scheme with the properties of unidirectionality and single-use and prove the security of both schemes in the standard model. The detailed analysis shows that our new IND-CCA secure SS-PRE scheme achieves a higher efficiency in computation cost and ciphertext size than the conventional C-PRE schemes.