An Efficient Quantum Somewhat Homomorphic Symmetric Searchable Encryption

Sun, Xiaoqiang; Wang, Ting; Sun, Zhiwei; Wang, Ping; Yu, Jianping; Xie, Weixin

doi:10.1007/s10773-017-3275-0

Cited by 16 publications

(7 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this case, one just needs to construct a homomorphic search circuit (or evaluation circuit) with homomorphic circuits for gates from G and adjust the key update algorithm accordingly. %randomly generate a 14-bit evaluation key, the 1st row is y1, the 2nd row is d1 38 evalKeyBits = randi([0,1], [2,7]); 39 disp('the random evaluation key:');disp(evalKeyBits); 40 encState = kron(kron(Z^encKeyBits(2,1) * X^encKeyBits(1,1),Z^encKeyBits(2,2) * ... X^encKeyBits(1,2)),Z^encKeyBits (2, curKeyBits(1,1) = xor(lastStepKeyBits(1,1),c); 133 curKeyBits(2,1) = mod(lastStepKeyBits(1,1) * (mod(c + evalKeyBits(1,7) + 1,2)) + ... lastStepKeyBits(2,1) + evalKeyBits(2,7) + evalKeyBits(1,7) , 2);…”

Section: Resultsmentioning

confidence: 99%

“…= eye(2);%defined the related unitary transform = sym([1/2^(1/2),1/2^(1/2);1/2^(1/2),-1/2^(1/2)]); = sym([0,1;1,0]);Z = sym([1,0;0,-1]);S = sym([1,0;0,1i]); 4 S_adjoint = transpose(conj(S)); 5 CNOT = sym([1,0,0,0;0,1,0,0;0,0,0,1;0,0,1,0;]);6 %CNOT with 3 qubits involved,the 3rd qubit act as target,the 1st qubit act as control 7 CNOT_13 = sym(blkdiag(eye(4),X,X)); ,j -4) = sym(1); 17 end 18 %the 4th qubit act as control,the 1st qubit act as target 19 CNOT_41 = sym(zeros(16,16)); 20 for j = 1 : 2 : 15 21 CNOT_41(j,j) = sym(1); ([1/2;1/2;1/2;1/2]);%set the input state 30 oracleQubit = sym([1/sqrt(2);-1/sqrt(2)]); 31 plainState = kron(dataQubits,oracleQubit); 32 %randomly generate a 4-bit encryption key, the 1st row is x0,the 2nd is z0 33 encKeyBits_forDataQubits = randi([0,1],[2,2]); 34 %the encrytion key for oracle qubit is 0,0 or unencrypted 35 encKeyBits = [encKeyBits_forDataQubits,[0;0]]; 36 disp('the random encryption key:');disp(encKeyBits); 37…”

mentioning

confidence: 99%

See 1 more Smart Citation

Quantum Search on Encrypted Data Based on Quantum Homomorphic Encryption

Zhou

Cui

et al. 2020

Sci Rep

View full text Add to dashboard Cite

We propose a blind quantum search protocol based on quantum homomorphic encryption, in which a client Alice with limited quantum ability can give her encrypted data to a powerful but untrusted quantum server and let the server search for her without decryption. By outsourcing the interactive key update process to a trusted key center, Alice only needs to encrypt her original data and decrypt the ciphered search result in linear time, and perfectly conceals the underlying plaintext from the search server as well. Besides, we also present a compact and secure quantum homomorphic evaluation protocol for Clifford circuits, where all possible keys are updated in parallel by the evaluator, and another server who would not contact the evaluator then searches out the true decryption key. In contrast with the CL scheme proposed by Broadbent, such protocol does not need any help from classical homomorphic encryption to achieve compactness.Please note: Abbreviations should be introduced at the first mention in the main text -no abbreviations lists. Suggested structure of main text (not enforced) is provided below. arXiv:1711.10066v2 [quant-ph] 25 Nov 2018 1. Randomly generate a four-bit encryption key ek = (x 0 , z 0 ) for |ψ . 6/15 15/15

show abstract

Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

Quantum Search on Encrypted Data Based on Quantum Homomorphic Encryption

Zhou

Cui

et al. 2020

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Addition and multiplication can be performed on the re-encrypted ciphertext, and each user involved can decrypted the computed result using their own private key, which is corresponding to the public key used for the first level encryption. Quantum cryptography was introduced in the SHE scheme to obtain unconditional security and efficient query on ciphertext in [76], and the proposed scheme belongs to symmetric encryption. Multiuser training machine learning model on encrypted data is also studied in recent years.…”

Section: Homomorphic Encryptionmentioning

confidence: 99%

Data Security and Privacy Protection for Cloud Storage: A Survey

2020

View full text Add to dashboard Cite

The new development trends including Internet of Things (IoT), smart city, enterprises digital transformation and world's digital economy are at the top of the tide. The continuous growth of data storage pressure drives the rapid development of the entire storage market on account of massive data generated. By providing data storage and management, cloud storage system becomes an indispensable part of the new era. Currently, the governments, enterprises and individual users are actively migrating their data to the cloud. Such a huge amount of data can create magnanimous wealth. However, this increases the possible risk, for instance, unauthorized access, data leakage, sensitive information disclosure and privacy disclosure. Although there are some studies on data security and privacy protection, there is still a lack of systematic surveys on the subject in cloud storage system. In this paper, we make a comprehensive review of the literatures on data security and privacy issues, data encryption technology, and applicable countermeasures in cloud storage system. Specifically, we first make an overview of cloud storage, including definition, classification, architecture and applications. Secondly, we give a detailed analysis on challenges and requirements of data security and privacy protection in cloud storage system. Thirdly, data encryption technologies and protection methods are summarized. Finally, we discuss several open research topics of data security for cloud storage.

show abstract

“…Bösch et al distinguish SEs based on the number of allowable client access in [20] as follows: Most of the oriented SSEs are classified into S/S, which is a suitable architecture for outsourcing data. However, some of recent researches aim to expand SSE to be a multi-user model by employing a proxy server and homomorphic encryptions [21][22][23]. Further details about SSEs are described in Section 2.4.…”

Section: Related Searchable Techniquesmentioning

confidence: 99%

Advanced Searchable Encryption: An Adaptively Secure Keyword Search for Matrix-type Storages

Kodera

Kuribayashi

Kusaka

et al. 2019

IJNC

View full text Add to dashboard Cite

IoT technologies and cloud storages have been developed remarkably, and many types of data including private information have been gradually outsourced. For such a situation, new convenient functionalities such as arithmetic and a keyword search over ciphertexts are required to allow users to obtain information without leaking queried results, contents of ciphertext, and so on. Especially, searchable encryptions have been paid much attention to realize a keyword search on an encrypted domain. In addition, an architecture of searchable symmetric encryption (SSE) is a suitable and efficient solution for data outsourcing. In this paper, we focus on an SSE scheme which employs a secure index for searching a keyword. In conventional studies, it has been widely considered that the scheme searches whether a queried keyword is contained in encrypted documents or not. On the other hand, we additionally take into account the location of the queried keyword in the documents by targeting a matrix-type data format. The method enables an administrator to search personal information listed per line or column in CSV-like format data.

show abstract

An Efficient Quantum Somewhat Homomorphic Symmetric Searchable Encryption

Cited by 16 publications

References 22 publications

Quantum Search on Encrypted Data Based on Quantum Homomorphic Encryption

Quantum Search on Encrypted Data Based on Quantum Homomorphic Encryption

Data Security and Privacy Protection for Cloud Storage: A Survey

Advanced Searchable Encryption: An Adaptively Secure Keyword Search for Matrix-type Storages

Contact Info

Product

Resources

About