Order-preserving Encryption Scheme Research Articles

Frequency-Revealing Attacks against Frequency-Hiding Order-Preserving Encryption

Order-preserving encryption (OPE) allows efficient comparison operations over encrypted data and thus is popular in encrypted databases. However, most existing OPE schemes are vulnerable to inference attacks as they leak plaintext frequency. To this end, some frequency-hiding order-preserving encryption (FH-OPE) schemes are proposed and claim to prevent the leakage of frequency. FH-OPE schemes are considered an important step towards mitigating inference attacks. Unfortunately, there are still vulnerabilities in all existing FH-OPE schemes. In this work, we revisit the security of all existing FH-OPE schemes. We are the first to demonstrate that plaintext frequency hidden by them is recoverable. We present three ciphertext-only attacks named frequency-revealing attacks to recover plaintext frequency. We evaluate our attacks in three real-world datasets. They recover over 90% of plaintext frequency hidden by any existing FH-OPE scheme. With frequency revealed, we also show the potentiality to apply inference attacks on existing FH-OPE schemes. Our findings highlight the limitations of current FH-OPE schemes. Our attacks demonstrate that achieving frequency-hiding requires addressing the leakages of both non-uniform ciphertext distribution and insertion orders of ciphertexts, even though the leakage of insertion orders is always ignored in OPE.

PP-DDP: a privacy-preserving outsourcing framework for solving the double digest problem

BackgroundAs one of the fundamental problems in bioinformatics, the double digest problem (DDP) focuses on reordering genetic fragments in a proper sequence. Although many algorithms for dealing with the DDP problem were proposed during the past decades, it is believed that solving DDP is still very time-consuming work due to the strongly NP-completeness of DDP. However, none of these algorithms consider the privacy issue of the DDP data that contains critical business interests and is collected with days or even months of gel-electrophoresis experiments. Thus, the DDP data owners are reluctant to deploy the task of solving DDP over cloud.ResultsOur main motivation in this paper is to design a secure outsourcing computation framework for solving the DDP problem. We at first propose a privacy-preserving outsourcing framework for handling the DDP problem by using a cloud server; Then, to enable the cloud server to solve the DDP instances over ciphertexts, an order-preserving homomorphic index scheme (OPHI) is tailored from an order-preserving encryption scheme published at CCS 2012; And finally, our previous work on solving DDP problem, a quantum inspired genetic algorithm (QIGA), is merged into our outsourcing framework, with the supporting of the proposed OPHI scheme. Moreover, after the execution of QIGA at the cloud server side, the optimal solution, i.e. two mapping sequences, would be transferred publicly to the data owner. Security analysis shows that from these sequences, none can learn any information about the original DDP data. Performance analysis shows that the communication cost and the computational workload for both the client side and the server side are reasonable. In particular, our experiments show that PP-DDP can find optional solutions with a high success rate towards typical test DDP instances and random DDP instances, and PP-DDP takes less running time than DDmap, SK05 and GM12, while keeping the privacy of the original DDP data.ConclusionThe proposed outsourcing framework, PP-DDP, is secure and effective for solving the DDP problem.

An Order-Preserving Encryption Scheme Based on Weighted Random Interval Division for Ciphertext Comparison in Wearable Systems.

With the rapid development of wearable devices with various sensors, massive sensing data for health management have been generated. This causes a potential revolution in medical treatments, diagnosis, and prediction. However, due to the privacy risks of health data aggregation, data comparative analysis under privacy protection faces challenges. Order-preserving encryption is an effective scheme to achieve private data retrieval and comparison, but the existing order-preserving encryption algorithms are mainly aimed at either integer data or single characters. It is urgent to build a lightweight order-preserving encryption scheme that supports multiple types of data such as integer, floating number, and string. In view of the above problems, this paper proposes an order-preserving encryption scheme (WRID-OPES) based on weighted random interval division (WRID). WRID-OPES converts all kinds of data into hexadecimal number strings and calculates the frequency and weight of each hexadecimal number. The plaintext digital string is blocked and recombined, and each block is encrypted using WRID algorithm according to the weight of each hexadecimal digit. Our schemes can realize the order-preserving encryption of multiple types of data and achieve indistinguishability under ordered selection plaintext attack (IND-OCPA) security in static data sets. Security analysis and experiments show that our scheme can resist attacks using exhaustive methods and statistical methods and has linear encryption time and small ciphertext expansion rate.

MDOPE: Efficient multi-dimensional data order preserving encryption scheme

Nowadays, tremendous information technology industries resort to cloud servers to store data with an outsourcing approach to extend their storage and computation power. This, however, also leads to privacy and security issues of unprotected data against curious cloud servers. The most common solution currently is to encrypt the data before uploading it. The problem is that encrypted data is out of control and users also cannot transfer the searching job to cloud serves anymore. Specifically, the order preserving encryption (OPE) provides an efficient solution to the order of plaintexts. Existing OPE schemes focus on single-dimensional data, and fail to effectively process multi-dimensional data. In this paper, we propose a multi-dimensional data order preserving encryption scheme MDOPE allowing fine-grained multi-dimensional range queries. Our scheme constructs query indexes for each dimension of the data based on the order preserving encryption network. In particular, the proposed scheme ensures that no external entity, including the cloud server, can obtain additional information other than the order of ciphertexts during the whole query process.

An Efficient Update Algorithm for Mutable Order-Preserving Encryption

Order-preserving encryption (OPE) produces ciphertexts that preserve the numerical order of plaintexts. Many researchers have focused on designing ideally-secure OPE schemes. This security notion, known as IND-OCPA, has been shown to be achievable by the mutability of ciphertexts and interaction between a database server and a client. This implies that the ciphertexts stored on the server can be updated. Unfortunately, existing update algorithms of mutable OPE schemes are designed to generate ciphertexts uniformly regardless of the distribution of the plaintexts. This leads to inefficiency that requires frequent ciphertext updates for a certain input data pattern (e.g., sequential data). In this paper, we propose a more efficient ciphertext update algorithm that is suitable for mutable OPE schemes. This algorithm makes it possible to reduce the number of updates by considering the input pattern of encrypted data without loss of security. Our experimental results show that, when applied to existing mutable OPE schemes, our update algorithm delivers significantly improved performance on a variety of datasets.

Practical Frequency-Hiding Order-Preserving Encryption with Improved Update

Order-preserving encryption (OPE) that preserves the numerical ordering of plaintexts is one of the promising solutions of cloud security. In 2013, an ideally secure OPE, which reveals no additional information except for the order of underlying plaintexts, was proposed, along with the notion (mutable encryption) that ciphertexts can be changed. Unfortunately, even the ideally secure OPE can be vulnerable by inferring the underlying frequency of repeated plaintexts. To solve this problem, in 2015, Kerschbaum designed a frequency-hiding OPE (FH-OPE) scheme based on the notion of a randomized order under the strengthened security model. Later, Maffei et al. has shown that Kerschbaum’s model is imprecise, which means no such OPE scheme can exist. Moreover, they provided a new FH-OPE scheme under the corrected security model. However, their scheme requires the order information of all the encrypted plaintexts as an input; therefore, it causes relatively high overhead during encryption. In this work, we propose a more efficient FH-OPE based on Maffei et al.’ s security model and also present an improved update algorithm suitable for duplicate plaintexts.

Frequency-hiding order-preserving encryption with small client storage

The range query on encrypted databases is usually implemented using the order-preserving encryption (OPE) technique which preserves the order of plaintexts. Since the frequency leakage of plaintexts makes OPE vulnerable to frequency-analyzing attacks, some frequency-hiding order-preserving encryption (FH-OPE) schemes are proposed. However, existing FH-OPE schemes require either the large client storage of size O ( n ) or O (log n ) rounds of interactions for each query, where n is the total number of plaintexts. To this end, we propose a FH-OPE scheme that achieves the small client storage without additional client-server interactions. In detail, our scheme achieves O ( N ) client storage and 1 interaction per query, where N is the number of distinct plaintexts and N ≤ n . Especially, our scheme has a remarkable performance when N ≪ n . Moreover, we design a new coding tree for producing the order-preserving encoding which indicates the order of each ciphertext in the database. The coding strategy of our coding tree ensures that encodings update in the low frequency when inserting new ciphertexts. Experimental results show that the single round interaction and low-frequency encoding updates make our scheme more efficient than previous FH-OPE schemes.

Random Perturbation Order Preserving Distribution Encryption

Cloud computing services have to gain fast awareness by many organizations because of their cost-effectiveness, but they are faced with many security issues in protecting client business data in the current technological generation. Order-preserving encryption (OPE) is a very important technique for databases, and cloud storage encryption executes range queries efficiently, but regrettably, limited systems have stood to accomplish confirmable security. However, these schemes leak the distribution of repeated plaintext values. This paper presents a random perturbation distribution scheme (RPDS), which is secure and does not leak the distribution of repeated plaintext values. Our technology is based on Popa’s mutable order preserving encoding (mOPE) and storage-aware order-preserving encoding (stOPE). We supported RPDS with an insertion algorithm in which we added a random bit value to handle a repeated plaintext value that stops the server from recognizing repeated values, and we developed a proof to show the correctness of its syntax. This paper suggests that the arbitrary collision probability and proof show that collisions can only occur with a lower probability in the RPDS. This paper presents proof of the safety of the RPDS and its applicability, usability, and functionalities. Finally, we compared the RPDS with existing OPE schemes and provided an experimental result for the practicality of the RPDS.

Order-Revealing Encryption Scheme with Comparison Token for Cloud Computing

Order-preserving encryption (OPE) is a basic paradigm for the outsourced database where the order of plaintexts is kept in ciphertexts. OPE enables efficient order comparison execution while providing privacy protection. Unfortunately, almost all the previous OPE schemes either require numerous rounds of interactions or reveal more information about the encrypted database (e.g., the most significant bit). Order-revealing encryption (ORE) as a generalization is an encryption scheme where the order of plaintexts can be evaluated by running a comparison algorithm. Therefore, it is desirable to design an efficient ORE scheme which addresses above efficiency and security issues. In this paper, we propose a noninteractive ORE scheme from prefix encoding and Bloom filter techniques. The proposed scheme is an encryption scheme where a cloud service provider cannot evaluate the order of plaintexts until a comparison token is provided. The security analysis illustrates that our scheme achieves ideal security with frequency hiding. Furthermore, we illustrate a secure range query scheme through designing an encrypted tree structure named PORE tree from the above ORE scheme. The PORE tree reveals the order between different nodes and leaves encrypted data items in the same node incomparable even after query execution. Finally, the experimental evaluation shows the high efficiency of the proposed ORE scheme and range query scheme.

EncodeORE: Reducing Leakage and Preserving Practicality in Order-Revealing Encryption

Order-preserving encryption (OPE) is a cryptographic primitive that preserves the order of plaintexts. In the past few years, many OPE schemes were proposed to solve the problem of executing range queries in encrypted databases. However, OPE leaks some certain information (for example, the order of ciphertext), so it is vulnerable to many attacks. Subsequently, order-revealing encryption (ORE) was proposed by Boneh <i>et al.</i> (Eurocrypt 2015) as a generalization of order-preserving encryption. It breaks through the limitation of the numeric order of OPE plaintext. It implements ciphertext comparison for any specific form of plaintext through a publicly computable comparison function. In this article, we aim to design a new ORE scheme which reduces the leakages and preserves the practicality in terms of ciphertext length and encryption time. We first propose the hybrid model named <i>HybridORE</i>. Then, we propose an improved scheme named <i>EncodeORE</i> which achieves acceptable security and appropriate ciphertext length. They both explore the encode strategy of encoding plaintext into different parts and apply suitable ORE algorithms to each part according to its security characteristics to reduce leakages. Compared with the typical CLWW scheme (FSE 2016) and Lewi-Wu (CCS 2016) in large domain, they have fewer leakages. The experiment shows that the proposed <i>EncodeORE</i> is very practical.

Securing top-k query processing in two-tiered sensor networks

ABSTRACT Integrity and privacy are two important secure matrices in cyber security. Due to the limited resources and computing capability of the sensor nodes, it is challenging to simultaneously satisfy these two matrices for top-k querying in two-tiered sensor networks. To solve this problem, this paper proposes a weight-bind-based secure top-k query processing scheme (WBB-TQ), which utilises both the order-preserving symmetric encryption scheme (OPES) and the pairwise-key encryption technique to ensure data privacy in top-k querying. Since OPES can keep the size orders of the sensed data items unchanged before and after they are encrypted, the upper-layer storage nodes in the network can process top-k queries without knowing the exact values of the sensed data items. To guarantee the completeness of query results, we propose a novel method to establish chaining relationship among all the data items generated by each sensor node. By checking whether the relationship holds on not, Sink can find out whether adversaries drop and/or tamper with part or all of the qualified top-k data items in the query results. Theoretical analyses show that WBB-TQ can preserve data integrity and privacy of the top-k query results. Extensive simulation results further demonstrate that, WBB-TQ incurs very low computational and communication cost in securing top-k querying.

Research on order-preserving encryption scheme based on CryptDB

With the rapid development of cloud computing technology, cloud database, as an important part of cloud computing services, has gradually become necessary for daily work of enterprises or individuals. However, entrusting data to third-party managing can lead to security issues such as data leakage, and users cannot guarantee data security. To this end, this paper is based on the CryptDB, an open source database encryption proxy system designed by MIT, in this thesis we propose an improvement scheme for the shortcomings of the original CryptDB system. Specific contents including: By studying the CryptDB system, we find that the system is lack of scalability for different databases and does not involve the management of system keys. For the inefficiency of the mutable Order-Preserving Encryption (mOPE) in CryptDB system, we propose an improved additive Order-Revealing Encryption (aORE) scheme by combining the Practical Order-Revealing Encryption (P-ORE) and mOPE. The scheme is based on pseudorandom function and double encryption. Compared with mOPE, it can improve the execution efficiency of the Order-Preserving scheme at the expense of security.

Order-preserving encryption using approximate common divisors

Order-preservation is a highly desirable property for encrypted databases as it allows range queries over ciphertexts. Order-preserving encryption (OPE) is used in the encrypted database systems CryptDB and Cipherbase. The former has been adopted by several commercial organisations and the latter was developed as an extension of Microsoftâs SQLServer. We present two novel, but simple, randomised OPE schemes based on the general approximate common divisor problem (GACDP) and decisional polynomial approximate common divisor problem (DPolyACDP) respectively. These appear to be the first OPE schemes to be based on a computational hardness primitive, rather than a security game. Our GACDP based scheme is very efficient, requiring only O(1) arithmetic operations for encryption and decryption. Our DPolyACDP based scheme is similarly efficient. We show that these schemes have near optimal information leakage. We demonstrate how our OPE schemes can be integrated into a secure distributed computing system which computes over encrypted data. We report on an extensive evaluation of our GACDP-based algorithms in such a scenario, a MapReduce computation over encrypted data. The results clearly demonstrate extremely favourable execution times in comparison with existing OPE schemes.

Privacy-preserving range query over multi-source electronic health records in public clouds

Range query is an important data search technique in cloud-based electronic healthcare (eHealth) systems. It enables authorized doctors to retrieve target electronic health records (EHRs) that are generated and outsourced by patients from the cloud server. In reality, patients always encrypt their EHRs before outsourcing, making the range query impossible. In this paper, we identify three threats in real cloud-based eHealth systems, i.e., privacy leakage, frequency analysis, and identical data inference. To capture the security properties that resist these threats, we define a security notion of indistinguishability under multi-source ordered chosen plaintext attack (IND-MSOCPA). Then, we propose a multi-source order-preserving encryption (MSOPE) scheme for cloud-based eHealth systems to enable range queries over encrypted EHRs from multiple patients. Security analysis proves that the MSOPE scheme is IND-MSOCPA secure. We also conduct comprehensive performance evaluations, which demonstrate the high efficiency of the MSOPE scheme.

Periodical key change for cloud mutable security protocol

Securing cloud databases is a challenge in the cloud computing paradigm. Several research studies have been conducted to improve the security level in cloud computing. Many security schemes do not preserve mathematical or logical operations over encrypted data. Order Preserving Encryption schemes (OPEs) preserve the ordering (logical) operations over encrypted data. However, many OPE schemes leak information. Mutable Order Preserving Encoding (MOPE) algorithm achieves ideal security when it uses Randomized Encryption (RND) rather than Deterministic Encryption (DET) Scheme. RND and DET can be implemented with any standard cipher such as AES. This research proposes to use DET for MOPE and achieves the same security level when it uses RND. This paper proposes to change the encryption key on a certain time or a certain number of transactions. MOPE keeps its search tree balanced on each transaction applied by the system to maintain the performance. To enhance the security level without degrading the performance, this paper is utilizing the time consumed by rebalancing part of the tree in MOPE algorithm. This paper finds an optimal window to change the encryption key with an acceptable loss of performance.

Semi-Order Preserving Encryption Technique for Numeric Database

Order preserving encryption techniques are treated as some of the most efficient encryption schemes for securing numeric data in a database. Such schemes are popular because they resolve performance degradation issues, which are significant problems in database encryption. However, in some applications, the order itself is sensitive information, and should be hidden. Conventional order preserving encryption techniques published so far, did not consider this issue. Therefore, in this study, we consider three techniques that protect the order information and also show good performance. The three methods hide the data order such that comparison operators can be handled efficiently and performance degradation can be prevented. Our methods work on the top of an order preserving encryption scheme and enhance the security of data. Experimental results demonstrate the efficiency and effectiveness of the proposed three methods.

A secure, fast insert and efficient search order preserving encryption scheme for outsourced databases

Order preserving encryption (OPE) schemes have been studied to a great extent in the cryptography literature because of their potential application to database design. For the first time, a scheme ...

A secure, fast insert and efficient search order preserving encryption scheme for outsourced databases

Order preserving encryption (OPE) schemes have been studied to a great extent in the cryptography literature because of their potential application to database design. For the first time, a scheme called mutable order preserving encoding (mOPE) is introduced to achieve indistinguishability under ordered chosen plaintext attack (IND-OCPA) security. However, even mOPE scheme potentially leaks the distribution of repeated ciphertexts and is less efficient. In this paper, a new scheme is introduced called as a secure and cost efficient order preserving encryption (SCOPE), which is considerably more secure and efficient than mOPE scheme. A new form of strong security notion called as indistinguishability under ordered chosen repeated plaintext distribution attack (IND-OCRPDA) is proposed and we show that SCOPE scheme is IND-OCRPDA secure. Finally, the experimental results show that SCOPE achieves good performance in the context of an encrypted database and have a reasonable overhead which is 3.5× compared to plain data.

Collusion-Resistant Processing of SQL Range Predicates

Prior solutions for securely handling SQL range predicates in outsourced Cloud-resident databases have primarily focused on passive attacks in the Honest-but-Curious adversarial model, where the server is only permitted to observe the encrypted query processing. We consider here a significantly more powerful adversary, wherein the server can launch an active attack by clandestinely issuing specific range queries via collusion with a few compromised clients. The security requirement in this environment is that data values from a plaintext domain of size N should not be leaked to within an interval of size H. Unfortunately, all prior encryption schemes for range predicate evaluation are easily breached with only O(log _2psi ) range queries, where psi = N{/}H. To address this lacuna, we present SPLIT, a new encryption scheme where the adversary requires exponentially more—{mathbf{O}}(psi )—range queries to breach the interval constraint and can therefore be easily detected by standard auditing mechanisms. The novel aspect of SPLIT is that each value appearing in a range-sensitive column is first segmented into two parts. These segmented parts are then independently encrypted using a layered composition of a secure block cipher with the order-preserving encryption and prefix-preserving encryption schemes, and the resulting ciphertexts are stored in separate tables. At query processing time, range predicates are rewritten into an equivalent set of table-specific sub-range predicates, and the disjoint union of their results forms the query answer. A detailed evaluation of SPLIT on benchmark database queries indicates that its execution times are well within a factor of two of the corresponding plaintext times, testifying its efficiency in resisting active adversaries.

A Novel Secure Scheme for Supporting Complex SQL Queries over Encrypted Databases in Cloud Computing

With the advance of database-as-a-service (DaaS) and cloud computing, increasingly more data owners are motivated to outsource their data to cloud database for great convenience and economic savings. Many encryption schemes have been proposed to process SQL queries over encrypted data in the database. In order to obtain the desired data, the SQL queries contain some statements to describe the requirement, e.g., arithmetic and comparison operators (+, -, ×, &lt;, &gt;, and =). However, to support different operators (+, -, ×, &lt;, &gt;, and =) in SQL queries over encrypted data, multiple encryption schemes need to be combined and adjusted to work together. Moreover, repeated encryptions will reduce the efficiency of execution. This paper presents a practical and secure homomorphic order-preserving encryption (FHOPE) scheme, which allows cloud server to perform complex SQL queries that contain different operators (such as addition, multiplication, order comparison, and equality checks) over encrypted data without repeated encryption. These operators are data interoperable, so they can be combined to formulate complex SQL queries. We conduct security analysis and efficiency evaluation of the proposed scheme FHOPE. The experiment results show that, compared with the existing approaches, the FHOPE scheme incurs less overhead on computation and communication. It is suitable for large batch complex SQL queries over encrypted data in cloud environment.