66 research outputs found
An In-Depth Analysis on Efficiency and Vulnerabilities on a Cloud-Based Searchable Symmetric Encryption Solution
Searchable Symmetric Encryption (SSE) has come to be as an integral cryptographic approach in a world where digital privacy is essential. The capacity to search through encrypted data whilst maintaining its integrity meets the most important demand for security and confidentiality in a society that is increasingly dependent on cloud-based services and data storage. SSE offers efficient processing of queries over encrypted datasets, allowing entities to comply with data privacy rules while preserving database usability. Our research goes into this need, concentrating on the development and thorough testing of an SSE system based on Curtmolaās architecture and employing Advanced Encryption Standard (AES) in Cypher Block Chaining (CBC) mode. A primary goal of the research is to conduct a thorough evaluation of the security and performance of the system. In order to assess search performance, a variety of database settings were extensively tested, and the system's security was tested by simulating intricate threat scenarios such as count attacks and leakage abuse. The efficiency of operation and cryptographic robustness of the SSE system are critically examined by these reviews
Forward and Backward Private Dynamic Searchable Symmetric Encryption for Conjunctive Queries
Recent research in Dynamic Searchable Symmetric Encryption (DSSE) focuses on efficient search over encrypted data while allowing updates. Unfortunately, as demonstrated by many attacks, updates can be a source of information leakage that can compromise DSSE privacy. To mitigate these attacks, forward and backward privacy of DSSE schemes have been introduced. A concerted effort of the research community has resulted in the publication of many DSSE schemes. To the best of our knowledge, however, there is no DSSE scheme supporting conjunctive queries, which achieves both
forward and backward privacy.
We give two DSSE schemes with forward and backward privacy, which support conjunctive queries, and they are suitable for different applications. In particular, we first introduce a new data structure termed the extended bitmap index. Then we describe our forward and backward private DSSE schemes, which support conjunctive queries. Our security analysis proves the claimed privacy characteristics, and experiments show that our schemes are practical. Compared to the state-of-the-art DSSE VBTree supporting conjunctive queries (but not backward privacy), our schemes offer search time that is a few orders of magnitude faster. Besides, our schemes claim better security (called Type-C backward privacy)
A Practical Framework for Storing and Searching Encrypted Data on Cloud Storage
Security has become a significant concern with the increased popularity of
cloud storage services. It comes with the vulnerability of being accessed by
third parties. Security is one of the major hurdles in the cloud server for the
user when the user data that reside in local storage is outsourced to the
cloud. It has given rise to security concerns involved in data confidentiality
even after the deletion of data from cloud storage. Though, it raises a serious
problem when the encrypted data needs to be shared with more people than the
data owner initially designated. However, searching on encrypted data is a
fundamental issue in cloud storage. The method of searching over encrypted data
represents a significant challenge in the cloud.
Searchable encryption allows a cloud server to conduct a search over
encrypted data on behalf of the data users without learning the underlying
plaintexts. While many academic SE schemes show provable security, they usually
expose some query information, making them less practical, weak in usability,
and challenging to deploy. Also, sharing encrypted data with other authorized
users must provide each document's secret key. However, this way has many
limitations due to the difficulty of key management and distribution.
We have designed the system using the existing cryptographic approaches,
ensuring the search on encrypted data over the cloud. The primary focus of our
proposed model is to ensure user privacy and security through a less
computationally intensive, user-friendly system with a trusted third party
entity. To demonstrate our proposed model, we have implemented a web
application called CryptoSearch as an overlay system on top of a well-known
cloud storage domain. It exhibits secure search on encrypted data with no
compromise to the user-friendliness and the scheme's functional performance in
real-world applications.Comment: 146 Pages, Master's Thesis, 6 Chapters, 96 Figures, 11 Table
Searchable Encryption for Cloud and Distributed Systems
The vast development in information and communication technologies has spawned many new computing and storage architectures in the last two decades. Famous for its powerful computation ability and massive storage capacity, cloud services, including storage and computing, replace personal computers and software systems in many industrial applications. Another famous and influential computing and storage architecture is the distributed system, which refers to an array of machines or components geographically dispersed but jointly contributes to a common task, bringing premium scalability, reliability, and efficiency. Recently, the distributed cloud concept has also been proposed to benefit both cloud and distributed computing. Despite the benefits of these new technologies, data security and privacy are among the main concerns that hinder the wide adoption of these attractive architectures since data and computation are not under the control of the end-users in such systems. The traditional security mechanisms, e.g., encryption, cannot fit these new architectures since they would disable the fast access and retrieval of remote storage servers. Thus, an urgent question turns to be how to enable refined and efficient data retrieval on encrypted data among numerous records (i.e., searchable encryption) in the cloud and distributed systems, which forms the topic of this thesis.
Searchable encryption technologies can be divided into Searchable Symmetric Encryption (SSE) and Public-key Encryption with Keyword Search (PEKS). The intrinsical symmetric key hinders data sharing since it is problematic and insecure to reveal oneās key to others. However, SSE outperforms PEKS due to its premium efficiency and is thus is prefered in a number of keyword search applications. Then multi-user SSE with rigorous and fine access control undoubtedly renders a satisfactory solution of both efficiency and security, which is the first problem worthy of our much attention. Second, functions and versatility play an essential role in a cloud storage application but it is still tricky to realize keyword search and deduplication in the cloud simultaneously. Large-scale data usually renders significant data redundancy and saving cloud storage resources turns to be inevitable. Existing schemes only facilitate data retrieval due to keywords but rarely consider other demands like deduplication. To be noted, trivially and hastily affiliating a separate deduplication scheme to the searchable encryption leads to disordered system architecture and security threats. Therefore, attention should be paid to versatile solutions supporting both keyword search and deduplication in the cloud. The third problem to be addressed is implementing multi-reader access for PEKS. As we know, PEKS was born to support multi-writers but enabling multi-readers in PEKS is challenging. Repeatedly encrypting the same keyword with different readersā keys is not an elegant solution. In addition to keyword privacy, user anonymity coming with a multi-reader setting should also be formulated and preserved. Last but not least, existing schemes targeting centralized storage have not taken full advantage of distributed computation, which is considerable efficiency and fast response. Specifically, all testing tasks between searchable ciphertexts and trapdoor/token are fully undertaken by the only centralized cloud server, resulting in a busy system and slow response. With the help of distributed techniques, we may now look forward to a new turnaround, i.e., multiple servers jointly work to perform the testing with better efficiency and scalability. Then the intractable multi-writer/multi-reader mode supporting multi-keyword queries may also come true as a by-product.
This thesis investigates searchable encryption technologies in cloud storage and distributed systems and spares effort to address the problems mentioned above. Our first work can be classified into SSE. We formulate the Multi-user Verifiable Searchable Symmetric Encryption (MVSSE) and propose a concrete scheme for multi-user access. It not only offers multi-user access and verifiability but also supports extension on updates as well as a non-single keyword index. Moreover, revocable access control is obtained that the search authority is validated each time a query is launched, different from existing mechanisms that once the search authority is granted, users can search forever. We give simulation-based proof, demonstrating our proposal possesses Universally Composable (UC)-security. Second, we come up with a redundancy elimination solution on top of searchable encryption. Following the keyword comparison approach of SSE, we formulate a hybrid primitive called Message-Locked Searchable Encryption (MLSE) derived in the way of SSEās keyword search supporting keyword search and deduplication and present a concrete construction that enables multi-keyword query and negative keyword query as well as deduplication at a considerable small cost, i.e., the tokens are used for both search and deduplication. And it can further support Proof of Storage (PoS), testifying the content integrity in cloud storage. The semantic security is proved in Random Oracle Model using the game-based methodology. Third, as the branch of PEKS, the Broadcast Authenticated Encryption with Keyword Search (BAEKS) is proposed to bridge the gap of multi-reader access for PEKS, followed by a scheme. It not only resists Keyword Guessing Attacks (KGA) but also fills in the blank of anonymity. The scheme is proved secure under Decisional Bilinear Diffie-Hellman (DBDH) assumption in the Random Oracle Model.
For distributed systems, we present a Searchable Encryption based on Efficient Privacy-preserving Outsourced calculation framework with Multiple keys (SE-EPOM) enjoying desirable features, which can be classified into PEKS. Instead of merely deploying a single server, multiple servers are employed to execute the test algorithm in our scheme jointly. The refined search, i.e., multi-keyword query, data confidentiality, and search pattern hiding, are realized. Besides, the multi-writer/multi-reader mode comes true. It is shown that under the distributed circumstance, much efficiency can be substantially achieved by our construction. With simulation-based proof, the security of our scheme is elaborated.
All constructions proposed in this thesis are formally proven according to their corresponding security definitions and requirements. In addition, for each cryptographic primitive designed in this thesis, concrete schemes are initiated to demonstrate the availability and practicality of our proposal
Searchable Encryption for Conjunctive Queries with Extended Forward and Backward Privacy
Recent developments in the field of Dynamic Searchable Symmetric Encryption (DSSE) with forward and backward privacy have attracted much attention from both research and industrial communities. However, most forward and backward private DSSE schemes support single keyword queries only, which impedes its prevalence in practice. Until recently, Patranabis et al. (NDSS 2021) introduced a forward and backward private DSSE for conjunctive queries (named ODXT) based on the Oblivious Cross-Tags (OXT) framework. Unfortunately, its security is not comprehensive for conjunctive queries, and it deploys ālazy deletionā, which incurs more communication cost. Besides, it cannot delete a file in certain circumstances. To address these problems, we introduce two forward and backward private DSSE schemes with conjunctive queries (named SDSSE-CQ and SDSSE-CQ-S). To analysis their security, we present two new levels of backward privacy (named Type-O and Type-O, where Type-O is more secure than Type-O), which describe the leakages of conjunctive queries with OXT framework more accurately. Finally, the security and experimental evaluation demonstrate that our proposed schemes achieve better security with comparable computation and communication increase in comparison with ODXT
Chameleon: A Secure Cloud-Enabled and Queryable System with Elastic Properties
There are two dominant themes that have become increasingly more important in our
technological society. First, the recurrent use of cloud-based solutions which provide
infrastructures, computation platforms and storage as services. Secondly, the use of applicational
large logs for analytics and operational monitoring in critical systems. Moreover,
auditing activities, debugging of applications and inspection of events generated by errors
or potential unexpected operations - including those generated as alerts by intrusion
detection systems - are common situations where extensive logs must be analyzed, and
easy access is required. More often than not, a part of the generated logs can be deemed
as sensitive, requiring a privacy-enhancing and queryable solution.
In this dissertation, our main goal is to propose a novel approach of storing encrypted
critical data in an elastic and scalable cloud-based storage, focusing on handling JSONbased
ciphered documents. To this end, we make use of Searchable and Homomorphic
Encryption methods to allow operations on the ciphered documents. Additionally, our
solution allows for the user to be near oblivious to our systemās internals, providing
transparency while in use. The achieved end goal is a unified middleware system capable
of providing improved system usability, privacy, and rich querying over the data. This
previously mentioned objective is addressed while maintaining server-side auditable logs,
allowing for searchable capabilities by the log owner or authorized users, with integrity
and authenticity proofs.
Our proposed solution, named Chameleon, provides rich querying facilities on ciphered
data - including conjunctive keyword, ordering correlation and boolean queries
- while supporting field searching and nested aggregations. The aforementioned operations
allow our solution to provide data analytics upon ciphered JSON documents, using
Elasticsearch as our storage and search engine.O uso recorrente de soluƧƵes baseadas em nuvem tornaram-se cada vez mais importantes
na nossa sociedade. Tais soluƧƵes fornecem infraestruturas, computaĆ§Ć£o e armazenamento
como serviƧos, para alem do uso de logs volumosos de sistemas e aplicaƧƵes para
anĆ”lise e monitoramento operacional em sistemas crĆticos. Atividades de auditoria, debugging
de aplicaƧƵes ou inspeĆ§Ć£o de eventos gerados por erros ou possĆveis operaƧƵes
inesperadas - incluindo alertas por sistemas de detecĆ§Ć£o de intrusĆ£o - sĆ£o situaƧƵes comuns
onde logs extensos devem ser analisados com facilidade. Frequentemente, parte dos
logs gerados podem ser considerados confidenciais, exigindo uma soluĆ§Ć£o que permite
manter a confidencialidades dos dados durante procuras.
Nesta dissertaĆ§Ć£o, o principal objetivo Ć© propor uma nova abordagem de armazenar
logs crĆticos num armazenamento elĆ”stico e escalĆ”vel baseado na cloud. A soluĆ§Ć£o proposta
suporta documentos JSON encriptados, fazendo uso de Searchable Encryption e
mĆ©todos de criptografia homomĆ³rfica com provas de integridade e autenticaĆ§Ć£o. O objetivo
alcanƧado Ʃ um sistema de middleware unificado capaz de fornecer privacidade,
integridade e autenticidade, mantendo registos auditƔveis do lado do servidor e permitindo
pesquisas pelo proprietĆ”rio dos logs ou usuĆ”rios autorizados. A soluĆ§Ć£o proposta,
Chameleon, visa fornecer recursos de consulta atuando em cima de dados cifrados - incluindo
queries conjuntivas, de ordenaĆ§Ć£o e booleanas - suportando pesquisas de campo
e agregaƧƵes aninhadas. As operaƧƵes suportadas permitem Ć nossa soluĆ§Ć£o suportar data
analytics sobre documentos JSON cifrados, utilizando o Elasticsearch como armazenamento
e motor de busca
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