Link Before You Share: Managing Privacy Policies through Blockchain

With the advent of numerous online content providers, utilities and applications, each with their own specific version of privacy policies and its associated overhead, it is becoming increasingly difficult for concerned users to manage and track the confidential information that they share with the providers. Users consent to providers to gather and share their Personally Identifiable Information (PII). We have developed a novel framework to automatically track details about how a users' PII data is stored, used and shared by the provider. We have integrated our Data Privacy ontology with the properties of blockchain, to develop an automated access control and audit mechanism that enforces users' data privacy policies when sharing their data across third parties. We have also validated this framework by implementing a working system LinkShare. In this paper, we describe our framework on detail along with the LinkShare system. Our approach can be adopted by Big Data users to automatically apply their privacy policy on data operations and track the flow of that data across various stakeholders.Comment: 10 pages, 6 figures, Published in: 4th International Workshop on Privacy and Security of Big Data (PSBD 2017) in conjunction with 2017 IEEE International Conference on Big Data (IEEE BigData 2017) December 14, 2017, Boston, MA, US

Keyword-Based Delegable Proofs of Storage

Cloud users (clients) with limited storage capacity at their end can outsource bulk data to the cloud storage server. A client can later access her data by downloading the required data files. However, a large fraction of the data files the client outsources to the server is often archival in nature that the client uses for backup purposes and accesses less frequently. An untrusted server can thus delete some of these archival data files in order to save some space (and allocate the same to other clients) without being detected by the client (data owner). Proofs of storage enable the client to audit her data files uploaded to the server in order to ensure the integrity of those files. In this work, we introduce one type of (selective) proofs of storage that we call keyword-based delegable proofs of storage, where the client wants to audit all her data files containing a specific keyword (e.g., "important"). Moreover, it satisfies the notion of public verifiability where the client can delegate the auditing task to a third-party auditor who audits the set of files corresponding to the keyword on behalf of the client. We formally define the security of a keyword-based delegable proof-of-storage protocol. We construct such a protocol based on an existing proof-of-storage scheme and analyze the security of our protocol. We argue that the techniques we use can be applied atop any existing publicly verifiable proof-of-storage scheme for static data. Finally, we discuss the efficiency of our construction.Comment: A preliminary version of this work has been published in International Conference on Information Security Practice and Experience (ISPEC 2018

Secure data storage and retrieval in cloud computing

Nowadays cloud computing has been widely recognised as one of the most inuential information technologies because of its unprecedented advantages. In spite of its widely recognised social and economic benefits, in cloud computing customers lose the direct control of their data and completely rely on the cloud to manage their data and computation, which raises significant security and privacy concerns and is one of the major barriers to the adoption of public cloud by many organisations and individuals. Therefore, it is desirable to apply practical security approaches to address the security risks for the wide adoption of cloud computing

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

An architecture for secure data management in medical research and aided diagnosis

Programa Oficial de Doutoramento en Tecnoloxías da Información e as Comunicacións. 5032V01[Resumo] O Regulamento Xeral de Proteccion de Datos (GDPR) implantouse o 25 de maio de 2018 e considerase o desenvolvemento mais importante na regulacion da privacidade de datos dos ultimos 20 anos. As multas fortes definense por violar esas regras e non e algo que os centros sanitarios poidan permitirse ignorar. O obxectivo principal desta tese e estudar e proponer unha capa segura/integracion para os curadores de datos sanitarios, onde: a conectividade entre sistemas illados (localizacions), a unificacion de rexistros nunha vision centrada no paciente e a comparticion de datos coa aprobacion do consentimento sexan as pedras angulares de a arquitectura controlar a sua identidade, os perfis de privacidade e as subvencions de acceso. Ten como obxectivo minimizar o medo a responsabilidade legal ao compartir os rexistros medicos mediante o uso da anonimizacion e facendo que os pacientes sexan responsables de protexer os seus propios rexistros medicos, pero preservando a calidade do tratamento do paciente. A nosa hipotese principal e: os conceptos Distributed Ledger e Self-Sovereign Identity son unha simbiose natural para resolver os retos do GDPR no contexto da saude? Requirense solucions para que os medicos e investigadores poidan manter os seus fluxos de traballo de colaboracion sen comprometer as regulacions. A arquitectura proposta logra eses obxectivos nun ambiente descentralizado adoptando perfis de privacidade de datos illados.[Resumen] El Reglamento General de Proteccion de Datos (GDPR) se implemento el 25 de mayo de 2018 y se considera el desarrollo mas importante en la regulacion de privacidad de datos en los ultimos 20 anos. Las fuertes multas estan definidas por violar esas reglas y no es algo que los centros de salud puedan darse el lujo de ignorar. El objetivo principal de esta tesis es estudiar y proponer una capa segura/de integración para curadores de datos de atencion medica, donde: la conectividad entre sistemas aislados (ubicaciones), la unificacion de registros en una vista centrada en el paciente y el intercambio de datos con la aprobacion del consentimiento son los pilares de la arquitectura propuesta. Esta propuesta otorga al titular de los datos un rol central, que le permite controlar su identidad, perfiles de privacidad y permisos de acceso. Su objetivo es minimizar el temor a la responsabilidad legal al compartir registros medicos utilizando el anonimato y haciendo que los pacientes sean responsables de proteger sus propios registros medicos, preservando al mismo tiempo la calidad del tratamiento del paciente. Nuestra hipotesis principal es: .son los conceptos de libro mayor distribuido e identidad autosuficiente una simbiosis natural para resolver los desafios del RGPD en el contexto de la atencion medica? Se requieren soluciones para que los medicos y los investigadores puedan mantener sus flujos de trabajo de colaboracion sin comprometer las regulaciones. La arquitectura propuesta logra esos objetivos en un entorno descentralizado mediante la adopcion de perfiles de privacidad de datos aislados.[Abstract] The General Data Protection Regulation (GDPR) was implemented on 25 May 2018 and is considered the most important development in data privacy regulation in the last 20 years. Heavy fines are defined for violating those rules and is not something that healthcare centers can afford to ignore. The main goal of this thesis is to study and propose a secure/integration layer for healthcare data curators, where: connectivity between isolated systems (locations), unification of records in a patientcentric view and data sharing with consent approval are the cornerstones of the proposed architecture. This proposal empowers the data subject with a central role, which allows to control their identity, privacy profiles and access grants. It aims to minimize the fear of legal liability when sharing medical records by using anonymisation and making patients responsible for securing their own medical records, yet preserving the patient’s quality of treatment. Our main hypothesis is: are the Distributed Ledger and Self-Sovereign Identity concepts a natural symbiosis to solve the GDPR challenges in the context of healthcare? Solutions are required so that clinicians and researchers can maintain their collaboration workflows without compromising regulations. The proposed architecture accomplishes those objectives in a decentralized environment by adopting isolated data privacy profiles

Split keyword fuzzy and synonym search over encrypted cloud data

A substitute solution for various organizations of data owners to store their data in the cloud using storage as a service(SaaS). The outsourced sensitive data is encrypted before uploading into the cloud to achieve data privacy. The encrypted data is search based on keywords and retrieve interested files by data user using a lot of traditional Search scheme. Existing search schemes supports exact keyword match or fuzzy keyword search, but synonym based multi-keyword search are not supported. In the real world scenario, cloud users may not know the exact keyword for searching and they might give synonym of the keyword as the input for search instead of exact or fuzzy keyword due to lack of appropriate knowledge of data. In this paper, we describe an efficient search approach for encrypted data called as Split Keyword Fuzzy and Synonym Search (SKFS). Multi-keyword ranked search with accurate keyword and Fuzzy search supports synonym queries are a major contribution of SKFS. The wildcard Technique is used to store the keywords securely within the index tree. Index tree helps to search faster, accurate and low storage cost. Extensive experimental results on real-time data sets shows, the proposed solution is effective and efficient for multi-keyword ranked search and synonym queries Fuzzy based search over encrypted cloud data. © 2017 Springer Science+Business Media, LL

Integrity Proofs for RDF Graphs

Representing open datasets with the RDF model is becoming increasingly popular. An important aspect of this data model is that it can utilize the methods of computing cryptographic hashes to verify the integrity of RDF graphs. In this paper, we first develop a number of metrics to compare the state-of-the-art integrity proof methods and then present two new approaches to generate an integrity proof of RDF datasets: (i) semantic-based and (ii) structure-based. The semantic-based approach leverages timestamps (or other inherent notions of ordering) as an indexing key to construct a sorted Merkle tree variation, where timestamps are semantically extractable from the dataset. The structure-based approach utilizes the redundant structure of large RDF datasets to compress the dataset statements prior to generating a variation of a Merkle tree. We provide a theoretical analysis and an experimental evaluation of our two proposed methods. Compared to the Merkle and sorted Merkle tree, the semantic-based approach achieves faster querying performance for large datasets. The structure-based approach is well suited when RDF datasets contain large amounts of semantic redundancies. We also evaluate our methods' resistance to adversarial threats