Searchable Encryption with Secure and Efficient Updates

Outsourcing medical data and their search services to a third party cloud have been a popular trend for many medical practices, because using healthcare cloud services can help cut down the cost of Electronic Health Records (EHR) systems in terms of front-end ownership cost and IT maintenance burdens. Healthcare cloud applications need searchable encryption with the following two capabilities for protecting data privacy and access privacy: (1) the healthcare providers need to share the encrypted data with authorized users and enable querying over encrypted data, and (2) they also need to keep the query keywords and associated search operations private such that healthcare data hosting service providers cannot gain access to unauthorized content or trace and infer sensitive data stored in the healthcare cloud. This survey paper describes the notion of searchable encryption (SE) in the context of healthcare applications and characterize the SE use cases into four scenarios in healthcare. Then we provide a comprehensive overview of the four representative SE techniques: searchable symmetric encryption (SSE), public key encryption with keyword search (PEKS), attribute-based encryption with keyword search (ABKS), and proxy re-encryption with keyword search (PRES) according to different EHR retrieving scenarios and requirements. We categorize and compare the different SE schemes in terms of their security, efficiency, and functionality. The survey is designed to benefit both experienced researchers in the computer science (CS) field and non-specialists who are domain scientists or healthcare professionals with limited CS and information security background. Thus, we are in favor of technological overview of the state of art searchable encryption models and the underlying key techniques, instead of detailed proofs and constructions of the respective SE algorithms. We describe how the existing SE schemes relate to and differ from one another, and point out the connections between the SE techniques and the security and privacy requirements of healthcare applications and the open research problems.

Searchable encryption is a significant cryptographic primitive to ensure storage security and data privacy in cloud computing environment. It allows a client to store a collection of encrypted documents on server, and latterly, according to specific search criteria, perform keyword-based searches and retrieve the documents, meanwhile ensuring that it reveals minimal information to the server. Early research on searchable encryption schemes mainly focused on the efficiency, the security and the query expressiveness, and nowadays, the studies have been paying attention to searchable encryption that supports dataset update dynamically. In this paper, we propose a new dynamic symmetric searchable encryption scheme. In the aspect of efficiency, the complexity of search algorithm is O(1), while file addition and deletion are O(mn) and O(N) respectively (here m means the number of keywords in a document; N means the number of document-keyword pairs and n means the size of keywords dictionary), which indicates the overall efficiency is superior to the existing schemes; in terms of security, this scheme can resist selective keyword attack, and compared with former ones, it achieves less information leakage.

Cloud computing offers the possibility of providing suitable access within a network for a set of resources. Many users use different services for outsourcing their data within the cloud, saving and mitigating the local storage and other resources involved. One of the biggest concerns is represented by storing sensitive data on remote servers, which can be found to be extremely challenging within different situations related to privacy. Searchable Encryption (SE) represents a particular case of Fully Homomorphic Encryption (FHE) and at the same time represents a method composed from a set of algorithms meant to offer protection for users’ sensitive data, while it preserves the searching functionality on the server-side. There are two main types of SE: Searchable Symmetric Encryption (SSE), where the ciphertexts and trapdoors for searching are performed using private key holders, and Public Key Searchable Encryption (PKSE), in which a specific number of users have the public key based on which are capable of outputting ciphertexts and giving the possibility of producing the trapdoors by using the private key from the holder. In this article, we propose a searchable encryption system that uses biometric authentication. Additionally, biometric data are used in the trapdoor generation process, such that an unauthorized user cannot submit search queries. The proposed system contains three components: classic user authentication (based on username, password, and a message with a code using short message service (SMS), biometric authentication, and the searchable encryption scheme. The first two components can be seen as two-factor authentication (2FA), and the second component represents the initialization step of the searchable encryption scheme. In the end, we show and demonstrate that the proposed scheme can be implemented with success for medium to complex network infrastructures. We have granted special attention to the trapdoor function, which generates a value that can be used to perform the search process and search function that is based on the trapdoor pair for searching within the index structure. We provide the correctness and security proof of the operations, which gives us the guarantee that the cloud servers return the correct documents. Additionally, we discuss measuring the performance of the authentication scheme in terms of performance indicators, introducing two indicators for measuring purposes—namely, cloud average number of non-legitim the user actions for cloud purposes (CANNL) and cloud average number of legitim user actionsCANLU.

Processing queries on encrypted data protects sensitive data stored in cloud databases. CryptDB has introduced the approach of adjustable encryption for such processing. A database column is adjusted to the necessary level of encryption, e.g. order-preserving, for the set of executed queries, but never reversed. This has the drawback that long running cloud databases will eventually transform into only order-preserving encrypted databases. In this paper we propose searchable encryption as an alternative in order to reduce this encryption degradation. It maintains security while only marginally impacting performance when applied only to infrequently used queries for searching. We present a budget-based encryption selection algorithm as part of query planning for making the appropriate choice between searchable and deterministic or order-preserving encryption. We evaluate our algorithm on a long-tail distributed TPC-C benchmark on an experimental implementation of encrypted queries in an in-memory database. In one choice of parameters our algorithm incurs only a \(1.5\%\) performance penalty, but one of 15 columns is not decrypted to order-preserving or deterministic encryption. Our selection algorithm is configurable, such that higher security gains are possible at the cost of performance.

Searchable Encryption can search over encrypted data without accessing data or queries in plaintext. It preserves privacy while queries are performed over data on an untrusted server. To ensure the efficiency of search, most Searchable Encryption schemes reveal access patterns, i.e., a server learns which encrypted files are retrieved for each query. Unfortunately, by collecting access patterns, a file-injection attack can completely compromise the query privacy offered by Searchable Encryption. In this paper, we propose a novel pre-encryption obfuscation mechanism, referred to as Vaccine, which can effectively protect searchable encrypted data against a file-injection attack. Specifically, the main idea of Vaccine is to introduce a self file-injection attack, which obfuscates access patterns obtained by an attacker and prevents this attacker from inferring correct queries in plaintext. In addition, by harnessing natural language processing techniques, Vaccine can effectively remove self-injected files from search results, and therefore introduce minimal tradeoffs. Our experimental results on a real-world dataset show that Vaccine can reduce an adversary's guessing probability from 1 to $3.7\times 10^{-3}$ , which significantly promotes privacy protection. Furthermore, Vaccine introduces only 3.4% false negatives and no false positives in search results.

The continued development of cloud computing requires technologies that protect users’ privacy even from the cloud service providers themselves. Searchable encryption is one such kind of technology that allows users to perform keyword search queries directly over encrypted documents stored on a remote server. Multi-user searchable encryption enables a data owner to allow multiple users to search over her encrypted document collection. For many applications, it is important to limit what an adversarial service provider can infer about the encrypted documents, even if it colludes with some of the users. Clearly, it can learn the content of documents shared with this subset of “corrupted” users, however, it is important to ensure that this collusion does not reveal information about parts of the dataset that are only shared with the remaining “uncorrupted” users, e.g., via cross-user leakage. In this work, we propose three novel schemes for this setting that achieve different trade-offs between performance and leakage. Compared to previous constructions, our first two schemes are the first ones to achieve asymptotically optimal search time. Our third scheme achieves minimal user storage and forward privacy with respect to document sharing, but slightly slower search performance. We formally prove the security of our schemes under reasonable assumptions. Moreover, we implement and evaluate their performance both on a single machine and over WAN. Our experimental results are encouraging, e.g., the search computation time is in the order of a few milliseconds.

Searchable encryption (SE) enables data users to securely search encrypted data stored in untrusted cloud servers. However, most SE schemes allow for leakages of access and search patterns to maximize efficiency and functionality. Recent attacks have shown that adversaries can recover query keywords with prior knowledge of the database by exploiting these leakages. Unfortunately, the existing schemes that protect access and search patterns result in frequent communications and high computational costs. Furthermore, complex calculation processes also raise challenges for verifying search results. To address these concerns, we first design an efficient conjunctive SE scheme with search and access pattern privacy using private set intersection. In the proposed scheme, we utilize random numbers to obfuscate the values of polynomials and randomly divide the results into two parts, which simplifies the search process, improves search efficiency, and eliminates the need for time-consuming ciphertext multiplication operations. We also extend this scheme to support search result verifiability. Specifically, by embedding a random number as the root of the return polynomial, we achieve verifiability of search results. Furthermore, we prove the security of both schemes employing the simulation-based method. Finally, we implement the schemes in a real database and thorough performance analyses demonstrate their efficiency.

With the rapid growth of cloud storage technology, the demand for efficient and secure search of outsourced encrypted data has become increasingly critical. However, existing conjunctive keyword dynamic searchable encryption schemes often expose the Keyword Pair Result Pattern (KPRP) during index matching, compromising privacy. Additionally, frequent index updates require expensive group exponentiations, leading to high client-side overhead. To tackle these challenges, we propose LRP-HDSE, a lightweight dynamic conjunctive keyword searchable encryption scheme that hides KPRP while minimizing client computation costs. To enhance privacy, we introduce the Vector Hidden Subset Predicate Encryption (VH-SPE) mechanism, which enables the server to implicitly detect cross-tag in the membership matching index, effectively mitigating KPRP leakage. For improved efficiency, the scheme designs a lightweight membership matching index structure, LSet, based on low-cost multiset hash operations, reducing reliance on costly exponentiations and lowering client overhead. Our security analysis confirms that LRP-HDSE provides robust KPRP hiding along with forward and backward security in dynamic environments. Asymptotic analysis, along with experiment evaluations on two real-world datasets, show that our scheme offers superior client-side computational efficiency compared to existing approaches, making it both practical and effective.

Searchable encryption (SE) is appearing as a prominent solution in the intersection of privacy protection and efficient retrieval of data outsourced to cloud computing storage. While it preserves privacy by encrypting data, yet supports search operation without data leakage. Due to its applicability, many research communities have proposed different SE schemes under various security definitions with numerous customary features (i.e. multi keyword search, ranked search). However, by reason of multi-keyword ranked search, SE discloses encrypted document list corresponding to multiple (secure) query keywords (or trapdoor). Such disclosure of statistical information helps an attacker to analyze and deduce the content of the data. To counter statistical information leakage in SE, we propose a scheme referred to as Countering Statistical Attack in Cloud based Searchable Encryption (CSA-CSE) that resorts to randomness in all components of an SE. CSA-CSE adopts inverted index that is built with a hash digest of a pair of keywords. Unlike existing schemes, ranking factors (i.e. relevance scores) rank the documents and then they no longer exist in the secure index (neither in order preserving encrypted form). Query keywords are also garbled with randomness in order to hide actual query/result statistics. Our security analysis and experiment on request for comments database ensure the security and efficiency of CSA-CSE.

Driven by the cloud-first initiative taken by various governments and companies, it has become a common practice to outsource spatial data to cloud servers for a wide range of applications such as location-based services and geographic information systems. Searchable encryption is a common practice for outsourcing spatial data which enables search over encrypted data by sacrificing the full security via leaking some information about the queries to the server. However, these inherent leakages could equip the server to learn beyond what is considered in the scheme, in the worst-case allowing it to reconstruct of the database. Recently, a novel form of database reconstruction attack against such kind of outsourced spatial data was introduced (Markatou and Tamassia, IACR ePrint 2020/284), which is performed using common leakages of searchable encryption schemes, i.e., access and search pattern leakages. An access pattern leakage is utilized to achieve an order reconstruction attack, whereas both access and search pattern leakages are exploited for the full database reconstruction attack. In this paper, we propose two novel schemes for outsourcing encrypted spatial data supporting dynamic range search. Our proposed schemes leverage R+tree to partition the dataset and binary secret sharing to support secure range search. They further provide backward and content privacy and do not leak the access pattern, therefore being resilient against the above mentioned database reconstruction attacks. The evaluations and results on the real-world dataset demonstrate the practicality of our schemes, due to (a) the minimal round-trip between the client and server, and (b) the low computation and storage overhead on the client side.

The cryptographic operations in existing searchable encryption protocols will consume a lot of energy of terminals if they are used in mobile computing environment. To address this issue, novel schemes of searchable encryption are required. In this paper, for reducing user's computational burden generated by the expensive cryptographic operations, an agent-based searchable encryption (ABSE) scheme with its security model is proposed in order that the searchable encryption can be used in mobile computing environment. A concrete implement of ABSE with its security proof is presented to help user search the related data with some keywords trapdoors in either cases that the agent is online or offline. Performance analysis is also provided to show this scheme is suitable to be used in mobile environments.

Cross-lingual multi-keyword rank search with semantic extension over encrypted data

SEPS: Efficient public-key based secure search over outsourced data

Most existing symmetric searchable encryption schemes aim at allowing a user to outsource her encrypted data to a cloud server and delegate the latter to search on her behalf. These schemes do not qualify as a secure and scalable solution for the multiparty setting, where users outsource their encrypted data to a cloud server and selectively authorize each other to search. Due to the possibility that the cloud server may collude with some malicious users, it is a challenge to have a secure and scalable multiparty searchable encryption (MPSE) scheme. This is shown by our analysis on the Popa-Zeldovich scheme, which says that an honest user may leak all her search patterns even if she shares only one of her documents with another malicious user. Based on our analysis, we present a new security model for MPSE by considering the worst case and average-case scenarios, which capture different server-user collusion possibilities. We then propose a MPSE scheme by employing the bilinear property of Type-3 pairings and prove its security based on the bilinear Diffie-Hellman variant and symmetric external Diffie-Hellman assumptions in the random oracle model.

Forward secure searchable encryption (FSSE) scheme allows one data user to search on encrypted databases while resisting the file injection attack. The data utilization can be further improved by extending the single-user scenario to the multi-user scenario. However, there are some issues needed to be considered when a data owner shares data with multiple data users. First, the public cloud server can not be completely trusted as it may be dishonest returning incorrect or incomplete results. Second, authorized users may trade their private keys for financial benefit. To our knowledge, state-of-the-art searchable encryption schemes only consider part of the following desirable features: the verifiability of results, the resistance to file injection attacks, the traceability and revocation of malicious users who abuse their private keys in the multi-user setting. Based on these motivations, we first propose enabling traceable and verifiable multi-user FSSE, which achieves the above functionalities. Besides, we carry out the security proof which demonstrates that our scheme can meet the requirements of security. We also assess the performance from theoretical analysis and experimental analysis, which shows that compared with other similar schemes, our scheme has richer functionalities with comparable efficiency.