Dynamic multi-client searchable symmetric encryption with support for boolean queries

Searchable symmetric encryption (SSE) enables users to efficiently search ciphertext in the cloud and ensures the security of encrypted data. Recent works show that forward security is an important property in dynamic SSE. Many forward secure searchable symmetric encryption (FSSE) schemes supporting single-keyword search have been proposed. Only a few SSE schemes can satisfy the forward security and support conjunctive keyword search at the same time, which are realized by adopting inefficient or complicated cryptography tools. Very recently, Hu proposed a novel construction to achieve conjunctive-keyword search, that is, using inner-product encryption (IPE) to design a conjunctive-keyword FSSE scheme. However, IPE scheme is a conceptually complex and low efficient scheme. In this paper, we use a more efficient cryptographic tool, asymmetric scalar-product-preserving encryption (ASPE), to design an efficient and secure conjunctive-keyword FSSE scheme. To improve practicality, we design our scheme to support multi-user setting. Our scheme achieves sub-linear efficiency, and can easily be used in any single-keyword FSSE scheme to obtain a conjunctive-keyword FSSE scheme supporting multi-user. Compared with the current conjunctive-keyword FSSE scheme, our scheme has a better update and search efficiency.

Searchable symmetric encryption (SSE) has been proposed that enables the clients to outsource their private encrypted data onto the cloud server and later the data can be searched with limited information leakage. However, existing surveys have not covered most recent advances on SSE technique. To fill the gap, we make a survey on state-of-the-art representative SSE schemes in cloud environment. We mainly focus on dynamic SSE schemes with forward and backward privacy, two vital security elements to maintain query privacy during data update operations. Specifically, we discuss about SSE protocols based on query expressiveness, including single keyword search, conjunctive keyword search, range search, disjunctive keyword search and verifiable search. Finally, through comparison on query expressiveness, security and efficiency, we demonstrate the strengths and weaknesses of the existing SSE protocols.

Outsourcing encrypted data to the cloud demands efficient and confidentiality-preserving search techniques, yet existing Searchable Symmetric Encryption (SSE) schemes suffer from severe access and search pattern leakage, and the problem is more intractable in multi-data-owner scenarios where cross-dataset privacy-preserving search remains unsolved. This paper proposes PSSE-MDO (Privacy-Preserving SSE with Pattern Obfuscation for Multiple Data Owners), the first SSE scheme that achieves robust access and search pattern hiding for multi-data-owner settings with constant client-side overhead. Our core innovation is a cryptographic protocol enabling users to issue a single constant-sized search token (trapdoor) for searching across all data owners' encrypted indexes. The scheme integrates Inner-Product Predicate Encryption (IPE) and Somewhat Homomorphic Encryption (SHE) to probabilistically obfuscate search results for each query. A key experimental result shows that the client-side cost approximately 120 ms for search token generation—remains constant regardless of the number of data owners, in contrast to existing pattern-hiding schemes with linearly scaling costs. This validates PSSE-MDO's practicality for real-world large-scale collaborative cloud systems, marking a significant step toward practical privacy-preserving search in federated cloud environments.

Based on Sun et al. ’s multi-client symmetric searchable encryption (SSE) scheme (at ESORICS 2016), and combining Zhao’s identity-concealed authenticated encryption (CCS 2016), a new SSE scheme with multi-data-owner functionalities is proposed. By setting two key generation centers, our scheme first implements multi-data-owner SSE. In particular, compared with Sun et al. ’s scheme, the new scheme not only meets the same security requirements stated by them, but also further strengthens the securities of the same category relevant scheme by providing identity-concealment, authentication of data user to server and confidentiality of search token. The identity-concealment aims to provide privacy protection (Forward ID-Privacy) for data users by hiding their identity information, while the authentication is to resist the camouflage attack by applying certificate-based mechanism to our scheme. In particular, the confidentiality of the search token provides replay-attack-resistant by encrypting the plaintext search token generated by data user. While in other works, the adversary can employ the previously generated plaintext search tokens to force the server to perform the same search queries. Furthermore, by efficiency analysis, our scheme reaches almost the same level of efficiency as Sun et al. ’s scheme.

Searchable Symmetric Encryption (SSE) is a mechanism that facilitates search over encrypted data that is outsourced to an untrusted Server. SSE schemes offer practicality at the expense of some information leakage.The last two years, the first dynamic SSE (DSSE) schemes, i.e. schemes that support updates, that are both forward and backward private, were introduced. Two lines of design have been proposed. The first one contains the schemes that use an oblivious data structure, i.e. the Client hides the memory access pattern from the Server. This level of security comes at the expense of significant communication overheads as the oblivious memory access requires several communication roundtrips or the use of expensive primitives that limits the potential of practicality. The second line of design contains solutions that avoid oblivious data structures.In this paper, we introduce a new DSSE solution that offers both forward and the highest level of backward privacy. Our scheme is the first one that follows the first line of design and achieves this level of security with a constant and small number of communication roundtrips. We evaluate the scheme's performance and we show that it is practical.

The cloud-assisted intelligent systems have attracted extensive attention due to their powerful data analysis and computation capabilities. However, how to handle encrypted data remains a challenging problem in intelligent systems. A promising solution is searchable symmetric encryption (SSE), which enables a client to privately outsource their data to the cloud while preserving keyword search functionality. In practice, dynamic SSE is more practical and supports efficient data addition and deletion. Unfortunately, data update will leak some additional information which can be exploited to break data privacy. To address this issue, forward and backward secure SSE schemes are proposed to reduce the leakage of data update. That is, forward security guarantees that the newly updated documents cannot reveal the previously searched keywords, while backward security guarantees that the server cannot recover the deleted documents. However, the existing forward and backward secure SSE schemes mainly consider curious-but-honest server. How to verify the soundness and completeness of search results is still a challenge. In this paper, we propose a noninteractive verifiable dynamic SSE scheme with forward and backward security from two universal accumulators. Specifically, the server in our scheme only needs one roundtrip to return the nondeleted search results to the client, which saves the communication overhead dramatically. Besides, our scheme can achieve public verification that anyone can verify the search results but not only the client who has the private key. Finally, we give a formal security analysis and compare the proposed scheme with other related work, the results show that our scheme can achieve the desired security properties with practical efficiency.

Searchable symmetric encryption (SSE) is an important technique for cloud computing. SSE allows encrypted critical data stored on an untrusted cloud server to be searched using keywords, returning correct data, but the keywords and data content are unknown by the server. However, an SSE database is not practical because the data is generally frequently modified even when stored on a remote server, since the server cannot update the encrypted data without decryption. Dynamic searchable symmetric encryption (DSSE) is designed to support this requirement. DSSE allows adding or deleting encrypted data on the server without decryption. Many DSSE systems have been proposed, based on link-list structures or blind storage (a new primitive). Each has advantages and drawbacks regarding function, extensibility, and efficiency. For a real system, the most important aspect is the tradeoff between performance and security. Therefore, we implemented several DSSE systems to compare their efficiency and security, and identify the various disadvantages with a view to developing an improved system.

In this article, we tackle for the first time the problem of dynamic memory-efficient Searchable Symmetric Encryption (SSE). In the term “memory-efficient” SSE, we encompass both the goals of local SSE, and page-efficient SSE. The centerpiece of our approach is a novel connection between those two goals. We introduce a map, called the Generic Local Transform, which takes as input a page-efficient SSE scheme with certain special features, and outputs an SSE scheme with strong locality properties. We obtain several results. (1) First, for page-efficient SSE with page size p, we build a dynamic scheme with storage efficiency \(\mathcal {O}({1})\) and page efficiency \(\widetilde{\mathcal {O}}\left( {\textrm{log}\, \textrm{log}\, (N/p)}\right) \), called \(\textsf{LayeredSSE}\). The main technical innovation behind \(\textsf{LayeredSSE}\) is a novel weighted extension of the two-choice allocation process, of independent interest. (2) Second, we introduce the Generic Local Transform, and combine it with \(\textsf{LayeredSSE}\) to build a dynamic SSE scheme with storage efficiency \(\mathcal {O}({1})\), locality \(\mathcal {O}({1})\), and read efficiency \(\widetilde{\mathcal {O}}\left( {\textrm{log}\,\textrm{log}\, N}\right) \), under the condition that the longest list is of size \(\mathcal {O}({N^{1-1/\textrm{log}\, \textrm{log}\, \lambda }})\). This matches, in every respect, the purely static construction of Asharov et al. presented at STOC 2016: dynamism comes at no extra cost. (3) Finally, by applying the Generic Local Transform to a variant of the Tethys scheme by Bossuat et al. from Crypto 2021, we build an unconditional static SSE with storage efficiency \(\mathcal {O}({1})\), locality \(\mathcal {O}({1})\), and read efficiency \(\mathcal {O}({\textrm{log}^\varepsilon N})\), for an arbitrarily small constant \(\varepsilon > 0\). To our knowledge, this is the construction that comes closest to the lower bound presented by Cash and Tessaro at Eurocrypt 2014.

As cloud computing becomes prevalent, more and more data owners are likely to outsource their data to a cloud server. However, to ensure privacy, the data should be encrypted before outsourcing. Symmetric searchable encryption allows users to retrieve keyword over encrypted data without decrypting the data. Many existing schemes that are based on symmetric searchable encryption only support single keyword search, conjunctive keywords search, multiple keywords search, or single phrase search. However, some schemes, i.e., static schemes, only search one phrase in a query request. In this paper, we propose a multi-phrase ranked search over encrypted cloud data, which also supports dynamic update operations, such as adding or deleting files. We used an inverted index to record the locations of keywords and to judge whether the phrase appears. This index can search for keywords efficiently. In order to rank the results and protect the privacy of relevance score, the relevance score evaluation model is used in searching process on client-side. Also, the special construction of the index makes the scheme dynamic. The data owner can update the cloud data at very little cost. Security analyses and extensive experiments were conducted to demonstrate the safety and efficiency of the proposed scheme.

With the wide spread of Cloud service, users are outsourcing their data to the third party servers. When we delegate our data to the cloud servers, there is such a potential risk that the data stored in the servers is stolen. If the data are stored in the encrypted form, the damage caused by data theft is low because the data will not leak to other parties. However, a new problem arises, that is, users are not able to operate encrypted data, which loses the merit of cloud computing. To solve such a problem, searchable symmetric encryption(SSE) is proposed. SSE is a cryptographic protocol that can execute keyword search over encrypted documents without decrypting them. Secure Indexes is one of realizations of SSE that provides constant time keyword search per document with the help of pseudo-random function and Bloom filters. However, Secure Indexes dose not support addition and deletion of documents. Tekin and Sahin proposed an improved Secure Indexes scheme that supports addition and deletion by employing Bloom filter and counting Bloom filter. The drawback of their scheme is that these operations are implemented in user side, which is not desired in the cloud computing since the aim of cloud computing is to delegate as many operations as possible. This paper proposes new SSE scheme. The proposed scheme also employ counting Bloom filter, but provide more fine-grained operations compared to the scheme by Tekin and Sahin in the sense that the proposed scheme provides not only search documents but add and delete the elements of document. Moreover, these operations are executed in the server side. The performance of the proposed SSE is comparable to the existing scheme which provides constant time for search, add and delete per document. We also implemented this SSE scheme, and verified that the scheme performed well not only theoretically but also in practice.

Although searchable encryption schemes allow secure search over the encrypted data, they mostly support conventional Boolean keyword search, without capturing any relevance of the search results. This leads to a large amount of post-processing overhead to find the most matching documents and causes an unnecessary communication cost between the servers and end-users. Such problems can be addressed efficiently using a ranked search system that retrieves the most relevant documents. However, existing state-of-the-art solutions in the context of Searchable Symmetric Encryption (SSE) suffer from either (a) security and privacy breaches due to the use of Order Preserving Encryption (OPE) or (b) non-practical solutions like using the two non-colluding servers. In this paper, we present a generic solution for multi-keyword ranked search over the encrypted cloud data. The proposed solution can be applied over different symmetric searchable encryption schemes. To demonstrate the practicality of our technique, in this paper we leverage the Oblivious Cross Tags (OXT) protocol of Cash et al. (2013) due to its scalability and remarkable flexibility to support different settings. Our proposed scheme supports the multi-keyword search on Boolean, ranked and limited range queries while keeping all of the OXT’s properties intact. The key contribution of this paper is that our scheme is resilience against all common attacks that take advantage of OPE leakage while only a single cloud server is used. Moreover, the results indicate that using the proposed solution the communication overhead decreases drastically when the number of matching results is large.

We point out the risks of protecting relational databases via Searchable Symmetric Encryption (SSE) schemes by proposing an inference attack exploiting the structural properties of relational databases. We also show that record-injection attacks mounted on relational databases have worse consequences than their file-injection counterparts on unstructured databases. Moreover, we discuss some techniques to reduce the effectiveness of inference attacks exploiting the access pattern leakage existing in SSE schemes.

With the development of cloud computing, data sharing has a new effective method, i.e., outsourced to cloud platform. In this case, since the outsourced data may contain privacy, they only allow to be accessed by the authorized users. Encrypting the data before outsourcing is a commonly used approach, where the data owners only need to send the corresponding encryption key to the authorized users. However, in such approach it is difficult to use the data since the encrypted data obsoletes comprehensive search functionalities of plaintext keyword search. In this paper, we leverage the secure k-nearest neighbor to propose a secure dynamic searchable symmetric encryption scheme. Our scheme can achieve two important security features, i.e., forward privacy and backward privacy which are very challenging in Dynamic Searchable Symmetric Encryption (DSSE) area. In addition, we evaluate the performance of our proposed scheme compared with other DSSE schemes. The comparison results demonstrate the efficiency of our proposed scheme in terms of the storage, search and update complexity.

From a view point of information security, researches on an encrypted search system have been done intensively. Such search systems are called searchable symmetric encryption (SSE). The main part of SSE is an encrypted index which affects security and efficiency. Until now many SSE schemes have been proposed, but most of them uses a random oracle to achieve both adaptive security and an optimal index size. The index size of adaptively secure SSE schemes without a random oracle can be much larger. In this paper, we propose a new SSE scheme which satisfies adaptive security in the standard model and has an optimal index size. Furthermore the index of our scheme consists of Bloom filters and simple arrays, that is, arrays of integers. Since Bloom filters are also implemented by an array of integers, the structure of the index is simple. Thus, unlike other SSE schemes with an optimal index size, the size does not depend on a security parameter.

Storage services allow data owners to store their huge amount of potentially sensitive data, such as audios, images, and videos, on remote cloud servers in encrypted form. To enable retrieval of encrypted files of interest, searchable symmetric encryption (SSE) schemes have been proposed. However, many schemes construct indexes based on keyword-file pairs and focus on boolean expressions of exact keyword matches. Moreover, most dynamic SSE schemes cannot achieve forward privacy and reveal unnecessary information when updating the encrypted databases. We tackle the challenge of supporting large-scale similarity search over encrypted feature-rich multimedia data, by considering the search criteria as a high-dimensional feature vector instead of a keyword. Our solutions are built on carefully-designed fuzzy Bloom filters which utilize locality sensitive hashing (LSH) to encode an index associating the file identifiers and feature vectors. Our schemes are proven to be secure against adaptively chosen query attack and forward private in the standard model . We have evaluated the performance of our scheme on real-world high-dimensional datasets, and achieved a search quality of 99 percent recall with only a few number of hash tables for LSH. This shows that our index is compact and searching is not only efficient but also accurate.