Dynamic Searchable Symmetric Encryption with Forward and Backward Privacy: A Survey

Dynamic searchable symmetric encryption (DSSE) is helpful to users with limited storage. In DSSE, the users are able to perform search and update queries on the ciphertext which stored on the cloud server. However, DSSE may suffer from file-injection attacks and leak information after deletion. In order to solve these problems, DSSE schemes with forward security and/or backward security have been proposed. In this paper, we propose two efficient DSSE schemes. The first one supports forward security using binary tree as the basic data structure. The second one uses puncturable encryption to achieve both forward and backward privacy.

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.

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.

An efficient conjunctive keyword searchable encryption for cloud-based IoT systems

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.

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

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.

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.

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.

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.

Dynamic searchable symmetric encryption (DSSE) that enables a client to perform searches and updates on encrypted data has been intensively studied in cloud computing. Recently, forward privacy and backward privacy has engaged significant attention to protect DSSE from the leakage of updates. However, the research in this field almost focused on keyword-level updates. That is, the client needs to know the keywords of the documents in advance. In this paper, we proposed a document-level update scheme, DBP, which supports immediate deletion while guaranteeing forward privacy and backward privacy. Compared with existing forward and backward private DSSE schemes, our DBP scheme has the following merits: 1) Practicality. It achieves deletion based on document identifiers rather than document/keyword pairs; 2) Efficiency. It utilizes only lightweight primitives to realize backward privacy while supporting immediate deletion. Experimental evaluation on two real datasets demonstrates the practical efficiency of our scheme.

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.

Symmetric Searchable Encryption (SSE) schemes enable users to search over encrypted data hosted on an untrusted server. Recently, there has been a lot of interest in forward and backward private SSE. The notion of forward privacy guarantees that updates to the encrypted structure do not reveal their association to any query made in the past. Backward privacy, on the other hand, guarantees that queries do not reveal their association to deleted documents. But strong backward private schemes are known to be inefficient in terms of both communication and computation. One avenue for improvement is leveraging the power of trusted execution environments such as Intel SGX inside the untrusted server to improve some of these inefficiencies. In this work, we propose the first SGX-supported dynamic SSE constructions that are forward-private as well as backward-private. To the best of our knowledge, while there is some work on SGX-supported Oblivious RAM (ORAM) and static SSE, there is no work on SGX-supported dynamic SSE. We propose three constructions that cover all types of backward privacy in literature that are very efficient compared to the state of the art backward private schemes. Our communication complexity is always the number of current documents matching the query and we show that there is no need for 'total obliviousness' in constructions for the strongest notion of backward privacy.

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.