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 system’s 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 soluções baseadas em nuvem tornaram-se cada vez mais importantes na nossa sociedade. Tais soluções fornecem infraestruturas, computação e armazenamento como serviços, para alem do uso de logs volumosos de sistemas e aplicações para análise e monitoramento operacional em sistemas críticos. Atividades de auditoria, debugging de aplicações ou inspeção de eventos gerados por erros ou possíveis operações inesperadas - incluindo alertas por sistemas de detecção de intrusão - são situações comuns onde logs extensos devem ser analisados com facilidade. Frequentemente, parte dos logs gerados podem ser considerados confidenciais, exigindo uma solução que permite manter a confidencialidades dos dados durante procuras. Nesta dissertação, o principal objetivo é propor uma nova abordagem de armazenar logs críticos num armazenamento elástico e escalável baseado na cloud. A solução proposta suporta documentos JSON encriptados, fazendo uso de Searchable Encryption e métodos de criptografia homomórfica com provas de integridade e autenticação. O objetivo alcançado é um sistema de middleware unificado capaz de fornecer privacidade, integridade e autenticidade, mantendo registos auditáveis do lado do servidor e permitindo pesquisas pelo proprietário dos logs ou usuários autorizados. A solução proposta, Chameleon, visa fornecer recursos de consulta atuando em cima de dados cifrados - incluindo queries conjuntivas, de ordenação e booleanas - suportando pesquisas de campo e agregações aninhadas. As operações suportadas permitem à nossa solução suportar data analytics sobre documentos JSON cifrados, utilizando o Elasticsearch como armazenamento e motor de busca

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 one’s 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 readers’ 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 SSE’s 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

Practical yet Provably Secure: Complex Database Query Execution over Encrypted Data

Encrypted databases provide security for outsourced data. In this work novel encryption schemes supporting different database query types are presented enabling complex database queries over encrypted data. For specific constructions enabling exact keyword queries, range queries, database joins and substring queries over encrypted data we prove security in a formal framework, present a theoretical runtime analysis and provide an assessment of practical performance characteristics

An Efficient Queries Processing Model Based on Multi Broadcast Searchable Keywords Encryption (MBSKE)

Cloud computing is a technology which has enabled many organizations to outsource their data in an encrypted form to improve processing times. The public Internet was not initially designed to handle massive quantities of data flowing through millions of networks. So the rapid increase of broadcast users and the growth of the amount broadcasted information leads to slow sending quires and receiving encrypted data from the cloud. In order to solve this problem Next Generation Internet (NGI) is developed with high speed, while keeping the privacy of data. This research proposes a novel search algorithm called Multi-broadcast Searchable Keywords Encryption, which processes queries having a set of keywords. This set of keywords is sent from the users to the cloud server in an encrypted form, thus hiding all information about the user or the content of the queries from the cloud server. The proposed method uses caching algorithm and provide an improvement of 40% in terms of runtime and trapdoor. In addition, the method minimizes computational costs, complexity, and maximizes throughput, in the cloud environment, whilst maintaining privacy and confidentiality of both the user and the cloud. The cloud returns encrypted query results to the user, where data is decrypted using the users’ private keys

Secure equality testing protocols in the two-party setting

Protocols for securely testing the equality of two encrypted integers are common building blocks for a number of proposals in the literature that aim for privacy preservation. Being used repeatedly in many cryptographic protocols, designing efficient equality testing protocols is important in terms of computation and communication overhead. In this work, we consider a scenario with two parties where party A has two integers encrypted using an additively homomorphic scheme and party B has the decryption key. Party A would like to obtain an encrypted bit that shows whether the integers are equal or not but nothing more. We propose three secure equality testing protocols, which are more efficient in terms of communication, computation or both compared to the existing work. To support our claims, we present experimental results, which show that our protocols achieve up to 99% computation-wise improvement compared to the state-of-the-art protocols in a fair experimental set-up

Masking Fuzzy-Searchable Public Databases

We introduce and study the notion of keyless fuzzy search (KlFS) which allows to mask a publicly available database in such a way that any third party can retrieve content if and only if it possesses some data that is “close to” the encrypted data – no cryptographic keys are involved. We devise a formal security model that asks a scheme not to leak any information about the data and the queries except for some well-defined leakage function if attackers cannot guess the right query to make. In particular, our definition implies that recovering high entropy data protected with a KlFS scheme is costly. We propose two KlFS schemes: both use locality-sensitive hashes (LSH), cryptographic hashes and symmetric encryption as building blocks. The first scheme is generic and works for abstract plaintext domains. The second scheme is specifically suited for databases of images. To demonstrate the feasibility of our KlFS for images, we implemented and evaluated a prototype system that supports image search by object similarity on a masked database

Privacy-preserving efficient searchable encryption

Data storage and computation outsourcing to third-party managed data centers, in environments such as Cloud Computing, is increasingly being adopted by individuals, organizations, and governments. However, as cloud-based outsourcing models expand to society-critical data and services, the lack of effective and independent control over security and privacy conditions in such settings presents significant challenges. An interesting solution to these issues is to perform computations on encrypted data, directly in the outsourcing servers. Such an approach benefits from not requiring major data transfers and decryptions, increasing performance and scalability of operations. Searching operations, an important application case when cloud-backed repositories increase in number and size, are good examples where security, efficiency, and precision are relevant requisites. Yet existing proposals for searching encrypted data are still limited from multiple perspectives, including usability, query expressiveness, and client-side performance and scalability. This thesis focuses on the design and evaluation of mechanisms for searching encrypted data with improved efficiency, scalability, and usability. There are two particular concerns addressed in the thesis: on one hand, the thesis aims at supporting multiple media formats, especially text, images, and multimodal data (i.e. data with multiple media formats simultaneously); on the other hand the thesis addresses client-side overhead, and how it can be minimized in order to support client applications executing in both high-performance desktop devices and resource-constrained mobile devices. From the research performed to address these issues, three core contributions were developed and are presented in the thesis: (i) CloudCryptoSearch, a middleware system for storing and searching text documents with privacy guarantees, while supporting multiple modes of deployment (user device, local proxy, or computational cloud) and exploring different tradeoffs between security, usability, and performance; (ii) a novel framework for efficiently searching encrypted images based on IES-CBIR, an Image Encryption Scheme with Content-Based Image Retrieval properties that we also propose and evaluate; (iii) MIE, a Multimodal Indexable Encryption distributed middleware that allows storing, sharing, and searching encrypted multimodal data while minimizing client-side overhead and supporting both desktop and mobile devices

Multimedia

The nowadays ubiquitous and effortless digital data capture and processing capabilities offered by the majority of devices, lead to an unprecedented penetration of multimedia content in our everyday life. To make the most of this phenomenon, the rapidly increasing volume and usage of digitised content requires constant re-evaluation and adaptation of multimedia methodologies, in order to meet the relentless change of requirements from both the user and system perspectives. Advances in Multimedia provides readers with an overview of the ever-growing field of multimedia by bringing together various research studies and surveys from different subfields that point out such important aspects. Some of the main topics that this book deals with include: multimedia management in peer-to-peer structures & wireless networks, security characteristics in multimedia, semantic gap bridging for multimedia content and novel multimedia applications

Data Service Outsourcing and Privacy Protection in Mobile Internet

Mobile Internet data have the characteristics of large scale, variety of patterns, and complex association. On the one hand, it needs efficient data processing model to provide support for data services, and on the other hand, it needs certain computing resources to provide data security services. Due to the limited resources of mobile terminals, it is impossible to complete large-scale data computation and storage. However, outsourcing to third parties may cause some risks in user privacy protection. This monography focuses on key technologies of data service outsourcing and privacy protection, including the existing methods of data analysis and processing, the fine-grained data access control through effective user privacy protection mechanism, and the data sharing in the mobile Internet