182 research outputs found

    Efficient Method Based on Blockchain Ensuring Data Integrity Auditing with Deduplication in Cloud

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    With the rapid development of cloud storage, more and more cloud clients can store and access their data anytime, from anywhere and using any device. Data deduplication may be considered an excellent choice to ensure data storage efficiency. Although cloud technology offers many advantages for storage service, it also introduces security challenges, especially with regards to data integrity, which is one of the most critical elements in any system. A data owner should thus enable data integrity auditing mechanisms. Much research has recently been undertaken to deal with these issues. In this paper, we propose a novel blockchain-based method, which can preserve cloud data integrity checking with data deduplication. In our method, a mediator performs data deduplication on the client side, which permits a reduction in the amount of outsourced data and a decrease in the computation time and the bandwidth used between the enterprise and the cloud service provider. This method supports private and public auditability. Our method also ensures the confidentiality of a client's data against auditors during the auditing process

    A comprehensive meta-analysis of cryptographic security mechanisms for cloud computing

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    The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The concept of cloud computing offers measurable computational or information resources as a service over the Internet. The major motivation behind the cloud setup is economic benefits, because it assures the reduction in expenditure for operational and infrastructural purposes. To transform it into a reality there are some impediments and hurdles which are required to be tackled, most profound of which are security, privacy and reliability issues. As the user data is revealed to the cloud, it departs the protection-sphere of the data owner. However, this brings partly new security and privacy concerns. This work focuses on these issues related to various cloud services and deployment models by spotlighting their major challenges. While the classical cryptography is an ancient discipline, modern cryptography, which has been mostly developed in the last few decades, is the subject of study which needs to be implemented so as to ensure strong security and privacy mechanisms in today’s real-world scenarios. The technological solutions, short and long term research goals of the cloud security will be described and addressed using various classical cryptographic mechanisms as well as modern ones. This work explores the new directions in cloud computing security, while highlighting the correct selection of these fundamental technologies from cryptographic point of view

    Blockchain & Multi-Agent System: A New Promising Approach for Cloud Data Integrity Auditing with Deduplication

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    Recently, data storage represents one of the most important services in Cloud Computing. The cloud provider should ensure two major requirements which are data integrity and storage efficiency. Blockchain data structure and the efficient data deduplication represent possible solutions to address these exigencies. Several approaches have been proposed, some of them implement deduplication in Cloud server side, which involves a lot of computation to eliminate the redundant data and it becomes more and more complex. Therefore, this paper proposed an efficient, reliable and secure approach, in which the authors propose a Multi-Agent System in order to manipulate deduplication technique that permits to reduce data volumes thereby reduce storage overhead. On the other side, the loss of physical control over data introduces security challenges such as data loss, data tampering and data modification. To solve similar problems, the authors also propose Blockchain as a database for storing metadata of client files. This database serves as logging database that ensures data integrity auditing function

    Secure Cloud Storage with Client-Side Encryption Using a Trusted Execution Environment

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    With the evolution of computer systems, the amount of sensitive data to be stored as well as the number of threats on these data grow up, making the data confidentiality increasingly important to computer users. Currently, with devices always connected to the Internet, the use of cloud data storage services has become practical and common, allowing quick access to such data wherever the user is. Such practicality brings with it a concern, precisely the confidentiality of the data which is delivered to third parties for storage. In the home environment, disk encryption tools have gained special attention from users, being used on personal computers and also having native options in some smartphone operating systems. The present work uses the data sealing, feature provided by the Intel Software Guard Extensions (Intel SGX) technology, for file encryption. A virtual file system is created in which applications can store their data, keeping the security guarantees provided by the Intel SGX technology, before send the data to a storage provider. This way, even if the storage provider is compromised, the data are safe. To validate the proposal, the Cryptomator software, which is a free client-side encryption tool for cloud files, was integrated with an Intel SGX application (enclave) for data sealing. The results demonstrate that the solution is feasible, in terms of performance and security, and can be expanded and refined for practical use and integration with cloud synchronization services

    Ranked Keyword Search and Secure Data Sharing In Cloud Environment

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    The cloud computing innovation appeared amid the21st century; outsourcing data to cloud benefit for capacity turns into a helpful yet proficient pattern, which benefits in saving endeavors on data support and administration. In this work, we concentrate the issue of secure de-duplication on cloud data, likewise guaranteeing integrity. In particular, going for accomplishing both data integrity and de-duplication in cloud, we propose a framework, specifically cloud. Cloud presents an auditing element with support of the cloud, which creates hash esteem before transferring and audit the integrity of data having been put away in cloud. Contrasted and past work, the calculation by client in D-Cloud is extraordinarily lessened amid the document transferring and auditing stages. Cloud is planned understanding the way that clients dependably need to encode their data being transferred, and empowers integrity auditing and secure de-duplication on scrambled data. The primary danger for this cloud data stockpiling is data security as far as keeps up data integrity and data deduplication on cloud. Taking care of both issue normal time is the troublesome assignment. SecCloud and SecCloud+ are two new cloud auditing frameworks which help in keeping up cloud data integrity with productive data deduplication, In SecCloud framework, client can ready to create data labels before putting away data on cloud which encourages amid performing audit to check integrity of data, opposite side SecCloud+ framework give encryption of data before transferring it, which empowers integrity check and secure deduplication of encoded data

    Secure data storage and retrieval in cloud computing

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    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

    Efficient, Dependable Storage of Human Genome Sequencing Data

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    A compreensão do genoma humano impacta várias áreas da vida. Os dados oriundos do genoma humano são enormes pois existem milhões de amostras a espera de serem sequenciadas e cada genoma humano sequenciado pode ocupar centenas de gigabytes de espaço de armazenamento. Os genomas humanos são críticos porque são extremamente valiosos para a investigação e porque podem fornecer informações delicadas sobre o estado de saúde dos indivíduos, identificar os seus dadores ou até mesmo revelar informações sobre os parentes destes. O tamanho e a criticidade destes genomas, para além da quantidade de dados produzidos por instituições médicas e de ciências da vida, exigem que os sistemas informáticos sejam escaláveis, ao mesmo tempo que sejam seguros, confiáveis, auditáveis e com custos acessíveis. As infraestruturas de armazenamento existentes são tão caras que não nos permitem ignorar a eficiência de custos no armazenamento de genomas humanos, assim como em geral estas não possuem o conhecimento e os mecanismos adequados para proteger a privacidade dos dadores de amostras biológicas. Esta tese propõe um sistema de armazenamento de genomas humanos eficiente, seguro e auditável para instituições médicas e de ciências da vida. Ele aprimora os ecossistemas de armazenamento tradicionais com técnicas de privacidade, redução do tamanho dos dados e auditabilidade a fim de permitir o uso eficiente e confiável de infraestruturas públicas de computação em nuvem para armazenar genomas humanos. As contribuições desta tese incluem (1) um estudo sobre a sensibilidade à privacidade dos genomas humanos; (2) um método para detetar sistematicamente as porções dos genomas que são sensíveis à privacidade; (3) algoritmos de redução do tamanho de dados, especializados para dados de genomas sequenciados; (4) um esquema de auditoria independente para armazenamento disperso e seguro de dados; e (5) um fluxo de armazenamento completo que obtém garantias razoáveis de proteção, segurança e confiabilidade a custos modestos (por exemplo, menos de 1/Genoma/Ano),integrandoosmecanismospropostosaconfigurac\co~esdearmazenamentoapropriadasTheunderstandingofhumangenomeimpactsseveralareasofhumanlife.Datafromhumangenomesismassivebecausetherearemillionsofsamplestobesequenced,andeachsequencedhumangenomemaysizehundredsofgigabytes.Humangenomesarecriticalbecausetheyareextremelyvaluabletoresearchandmayprovidehintsonindividuals’healthstatus,identifytheirdonors,orrevealinformationaboutdonors’relatives.Theirsizeandcriticality,plustheamountofdatabeingproducedbymedicalandlife−sciencesinstitutions,requiresystemstoscalewhilebeingsecure,dependable,auditable,andaffordable.Currentstorageinfrastructuresaretooexpensivetoignorecostefficiencyinstoringhumangenomes,andtheylacktheproperknowledgeandmechanismstoprotecttheprivacyofsampledonors.Thisthesisproposesanefficientstoragesystemforhumangenomesthatmedicalandlifesciencesinstitutionsmaytrustandafford.Itenhancestraditionalstorageecosystemswithprivacy−aware,data−reduction,andauditabilitytechniquestoenabletheefficient,dependableuseofmulti−tenantinfrastructurestostorehumangenomes.Contributionsfromthisthesisinclude(1)astudyontheprivacy−sensitivityofhumangenomes;(2)todetectgenomes’privacy−sensitiveportionssystematically;(3)specialiseddatareductionalgorithmsforsequencingdata;(4)anindependentauditabilityschemeforsecuredispersedstorage;and(5)acompletestoragepipelinethatobtainsreasonableprivacyprotection,security,anddependabilityguaranteesatmodestcosts(e.g.,lessthan1/Genoma/Ano), integrando os mecanismos propostos a configurações de armazenamento apropriadasThe understanding of human genome impacts several areas of human life. Data from human genomes is massive because there are millions of samples to be sequenced, and each sequenced human genome may size hundreds of gigabytes. Human genomes are critical because they are extremely valuable to research and may provide hints on individuals’ health status, identify their donors, or reveal information about donors’ relatives. Their size and criticality, plus the amount of data being produced by medical and life-sciences institutions, require systems to scale while being secure, dependable, auditable, and affordable. Current storage infrastructures are too expensive to ignore cost efficiency in storing human genomes, and they lack the proper knowledge and mechanisms to protect the privacy of sample donors. This thesis proposes an efficient storage system for human genomes that medical and lifesciences institutions may trust and afford. It enhances traditional storage ecosystems with privacy-aware, data-reduction, and auditability techniques to enable the efficient, dependable use of multi-tenant infrastructures to store human genomes. Contributions from this thesis include (1) a study on the privacy-sensitivity of human genomes; (2) to detect genomes’ privacy-sensitive portions systematically; (3) specialised data reduction algorithms for sequencing data; (4) an independent auditability scheme for secure dispersed storage; and (5) a complete storage pipeline that obtains reasonable privacy protection, security, and dependability guarantees at modest costs (e.g., less than 1/Genome/Year) by integrating the proposed mechanisms with appropriate storage configurations
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