scholarly journals Forward and Backward-Secure Range-Searchable Symmetric Encryption

2021 ◽  
Vol 2022 (1) ◽  
pp. 28-48
Author(s):  
Jiafan Wang ◽  
Sherman S. M. Chow
Keyword(s):  
Homomorphic Encryption ◽  
Inverted Index ◽  
Range Queries ◽  
Symmetric Encryption ◽  
Forward Security ◽  
Injection Attacks ◽  
Searchable Symmetric Encryption ◽  
Encrypted Database ◽  
Definition Of ◽  
Client Side

Abstract Dynamic searchable symmetric encryption (DSSE) allows a client to query or update an outsourced encrypted database. Range queries are commonly needed. Previous range-searchable schemes either do not support updates natively (SIGMOD’16) or use file indexes of many long bit-vectors for distinct keywords, which only support toggling updates via homomorphically flipping the presence bit. (ESORICS’18). We propose a generic upgrade of any (inverted-index) DSSE to support range queries (a.k.a. range DSSE), without homomorphic encryption, and a specific instantiation with a new trade-off reducing client-side storage. Our schemes achieve forward security, an important property that mitigates file injection attacks. Moreover, we identify a variant of injection attacks against the first somewhat dynamic scheme (ESORICS’18). We also extend the definition of backward security to range DSSE and show that our schemes are compatible with a generic upgrade of backward security (CCS’17). We comprehensively analyze the computation and communication overheads, including implementation details of client-side index-related operations omitted by prior schemes. We show high empirical efficiency for million-scale databases over a million-scale keyword space.

An Encryption Methodology for Enabling the Use of Data Warehouses on the Cloud

2021 ◽  
pp. 528-559
Author(s):  
Claudivan Cruz Lopes ◽  
Valéria Cesário-Times ◽  
Stan Matwin ◽  
Cristina Dutra de Aguiar Ciferri ◽  
Ricardo Rodrigues Ciferri
Keyword(s):  
Data Warehouse ◽  
Homomorphic Encryption ◽  
Distributed Database ◽  
Pareto Optimal ◽  
Symmetric Encryption ◽  
Data Confidentiality ◽  
Cloud Data ◽  
Use Of Data ◽  
Star Schema ◽  
Definition Of

A cloud data warehouse (cloud DW) is a subject-oriented, integrated, time-variant, voluminous, nonvolatile and multidimensional distributed database that is hosted in a cloud. A solution to ensure data confidentiality for a cloud DW is cryptography. In this article, the authors propose an encryption methodology for a cloud DW stored according to the star schema, considering both the data confidentiality maintenance of the DW and the capability of processing analytical queries directly over the encrypted DW. The proposed encryption methodology comprises an encryption strategy for DW called MV-HO (MultiValued and HOmomorphic) for the definition of how the different types of DW's attributes must be encrypted. The proposed MV-HO encryption strategy was compared with encryption strategies based on symmetric encryption, order preserving symmetric encryption and homomorphic encryption. Results indicated that MV-HO is the best solution found, as MV-HO is pareto-optimal with respect to other strategies investigated.

scholarly journals A Dynamic Searchable Symmetric Encryption Scheme for Multiuser with Forward and Backward Security

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xi Zhang ◽  
Ye Su ◽  
Jing Qin
Keyword(s):  
Random Model ◽  
Symmetric Encryption ◽  
Encrypted Data ◽  
Privacy Concerns ◽  
Search Results ◽  
Injection Attacks ◽  
Pseudorandom Functions ◽  
Searchable Symmetric Encryption ◽  
Security Guarantees ◽  
Forward And Backward Security

Dynamic Searchable Symmetric Encryption for Multiuser (M-DSSE) is an advanced form of symmetric encryption. It extends the traditional symmetric encryption to support the operations of adding and deleting the encrypted data and allow an authenticated group of data users to retrieve their respective desired encrypted data in the dynamic database. However, M-DSSE would suffer from the privacy concerns regarding forward and backward security. The former allows an attacker to identify the keywords contained in the added data by lunching file-injection attacks, while the latter allows to utilize the search results and the deleted data to learn the content. To our knowledge, these privacy concerns for M-DSSE have not been fully considered in the existing literatures. Taking account of this fact, we focus on the dynamic searchable symmetric encryption for multiuser meeting the needs of forward and backward security. In order to propose a concrete scheme, the primitives of Pseudorandom Functions (PRF) and the Homomorphic Message Authenticator (HMAC) are employed to construct the inverted index and update the search token. The proposed scheme is proven secure in the random model. And the performance analysis shows that the proposed scheme achieves the enhanced security guarantees at the reasonable price of efficiency.

An Encryption Methodology for Enabling the Use of Data Warehouses on the Cloud

2018 ◽  
Vol 14 (4) ◽  
pp. 38-66 ◽  
Author(s):  
Claudivan Cruz Lopes ◽  
Valéria Cesário-Times ◽  
Stan Matwin ◽  
Cristina Dutra de Aguiar Ciferri ◽  
Ricardo Rodrigues Ciferri
Keyword(s):  
Data Warehouse ◽  
Homomorphic Encryption ◽  
Distributed Database ◽  
Symmetric Encryption ◽  
Data Confidentiality ◽  
Cloud Data ◽  
Use Of Data ◽  
Star Schema ◽  
Different Types ◽  
Definition Of

A cloud data warehouse (cloud DW) is a subject-oriented, integrated, time-variant, voluminous, nonvolatile and multidimensional distributed database that is hosted in a cloud. A solution to ensure data confidentiality for a cloud DW is cryptography. In this article, the authors propose an encryption methodology for a cloud DW stored according to the star schema, considering both the data confidentiality maintenance of the DW and the capability of processing analytical queries directly over the encrypted DW. The proposed encryption methodology comprises an encryption strategy for DW called MV-HO (MultiValued and HOmomorphic) for the definition of how the different types of DW's attributes must be encrypted. The proposed MV-HO encryption strategy was compared with encryption strategies based on symmetric encryption, order preserving symmetric encryption and homomorphic encryption. Results indicated that MV-HO is the best solution found, as MV-HO is pareto-optimal with respect to other strategies investigated.

scholarly journals Efficient Searchable Symmetric Encryption Supporting Dynamic Multikeyword Ranked Search

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Yu Zhang ◽  
Yin Li ◽  
Yifan Wang
Keyword(s):  
Binary Tree ◽  
Search Time ◽  
Symmetric Encryption ◽  
Time Cost ◽  
Computational Costs ◽  
Related Space ◽  
Insertion And Deletion ◽  
Searchable Symmetric Encryption ◽  
Ranked Search ◽  
Binary Tree Structure

Searchable symmetric encryption that supports dynamic multikeyword ranked search (SSE-DMKRS) has been intensively studied during recent years. Such a scheme allows data users to dynamically update documents and retrieve the most wanted documents efficiently. Previous schemes suffer from high computational costs since the time and space complexities of these schemes are linear with the size of the dictionary generated from the dataset. In this paper, by utilizing a shallow neural network model called “Word2vec” together with a balanced binary tree structure, we propose a highly efficient SSE-DMKRS scheme. The “Word2vec” tool can effectively convert the documents and queries into a group of vectors whose dimensions are much smaller than the size of the dictionary. As a result, we can significantly reduce the related space and time cost. Moreover, with the use of the tree-based index, our scheme can achieve a sublinear search time and support dynamic operations like insertion and deletion. Both theoretical and experimental analyses demonstrate that the efficiency of our scheme surpasses any other schemes of the same kind, so that it has a wide application prospect in the real world.

scholarly journals Semantically Secure Symmetric Encryption with Error Correction for Distributed Storage

2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Juha Partala
Keyword(s):  
Error Correction ◽  
Network Coding ◽  
Linear Combination ◽  
Distributed Storage ◽  
Homomorphic Encryption ◽  
Error Correcting Codes ◽  
Symmetric Encryption ◽  
Goppa Codes ◽  
Linear Network ◽  
Linear Network Coding

A distributed storage system (DSS) is a fundamental building block in many distributed applications. It applies linear network coding to achieve an optimal tradeoff between storage and repair bandwidth when node failures occur. Additively homomorphic encryption is compatible with linear network coding. The homomorphic property ensures that a linear combination of ciphertext messages decrypts to the same linear combination of the corresponding plaintext messages. In this paper, we construct a linearly homomorphic symmetric encryption scheme that is designed for a DSS. Our proposal provides simultaneous encryption and error correction by applying linear error correcting codes. We show its IND-CPA security for a limited number of messages based on binary Goppa codes and the following assumption: when dividing a scrambled generator matrix G^ into two parts G1^ and G2^, it is infeasible to distinguish G2^ from random and to find a statistical connection between G1^ and G2^. Our infeasibility assumptions are closely related to those underlying the McEliece public key cryptosystem but are considerably weaker. We believe that the proposed problem has independent cryptographic interest.

PMHE:A Wearable Medical Sensor Assisted Framework For Health Care Based On Blockchain And Privacy Computing

2021 ◽  
Author(s):  
Jindong Zhao ◽  
Wenshuo Wang ◽  
Dan Wang ◽  
Chunxiao Mu
Keyword(s):  
Prediction Model ◽  
Homomorphic Encryption ◽  
Physiological Data ◽  
Disease Prediction ◽  
Smart Contracts ◽  
Cloud Platform ◽  
User Privacy ◽  
Fully Homomorphic Encryption ◽  
Client Side ◽  
Medical Cloud

Abstract Nowadays, smart medical cloud platforms have become a new direction in the industry. However, because the medical system involves personal physiological data, user privacy in data transmission and processing is also easy to leak in the smart medical cloud platform. This paper proposed a medical data privacy protection framework named PMHE based on blockchain and fully homomorphic encryption technology. The framework receives personal physiological data from wearable devices on the client side, and uses blockchain as data storage to ensure that the data cannot be tampered with or forged; Besides, it use fully homomorphic encryption method to design a disease prediction model, which was implemented using smart contracts. In PMHE, data is encoded and encrypted on the client side, and encrypted data is uploaded to the cloud platform via the public Internet, preventing privacy leakage caused by channel eavesdropping; Smart contracts run on the blockchain platform for disease prediction, and the operators participating in computing are encrypted user data too, so it avoids privacy and security issues caused by platform data leakage. The client-to-cloud interaction protocol is also designed to overcome the defect that fully homomorphic encryption only supports addition and multiplication by submitting tuples on the client side, to ensure that the prediction model can perform complex computing. In addition, the design of the smart contract is introduced in detail, and the performance of the system is analyzed. Finally, experiments are conducted to verify the operating effect of the system, ensuring that user privacy is not leaked without affecting the accuracy of the model, and realizing a smart medical cloud platform in which data can be used but cannot be borrowed.

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