Relevant bibliographies by topics / Cloud data protection

Academic literature on the topic 'Cloud data protection'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Cloud data protection"

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Begum, Shameena, V. Ratna Vasuki, and K. V. V. Srinivas K.V.V.Srinivas. "Data Security and Protection in Cloud Computing." International Journal of Scientific Research 1, no. 2 (June 1, 2012): 31–34. http://dx.doi.org/10.15373/22778179/jul2012/9.

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Al-Museelem, Waleed, and Chun Lin Li. "Data Security and Data Privacy in Cloud Computing." Advanced Materials Research 905 (April 2014): 687–92. http://dx.doi.org/10.4028/www.scientific.net/amr.905.687.

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Cloud computing has led to the development of IT to more sophisticated levels by improving the capacity and flexibility of data storage and by providing a scalable computation and processing power which matches the dynamic data requirements. Cloud computing has many benefits which has led to the transfer of many enterprise applications and data to public and hybrid clouds. However, many organizations refer to the protection of privacy and the security of data as the major issues which prevent them from adopting cloud computing. The only way successful implementation of clouds can be achieved is through effective enhancement and management of data security and privacy in clouds. This research paper analyzes the privacy and protection of data in cloud computing through all data lifecycle stages providing an overall perspective of cloud computing while highlighting key security issues and concerns which should be addressed. It also discusses several current solutions and further proposes more solutions which can enhance the privacy and security of data in clouds. Finally, the research paper describes future research work on the protection of data privacy and security in clouds.
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G, Indira, Sujitha S, and S. Ganapathy Subramanian. "Data Integrity Protection in Cloud." International Journal on Cybernetics & Informatics 10, no. 2 (May 31, 2021): 211–18. http://dx.doi.org/10.5121/ijci.2021.100223.

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In cloud computing integrity of data and access control are challenging issues. Protection of outsourced data in cloud storage becomes critical. Codes which are regenerating of data provide fault tolerance. Therefore, remotely checking the integrity of data against corruptions and other issues under a real time cloud storage setting is our problem of study. It practically design and implement Data Integrity Protection (DIP) environment.
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Henze, Martin, René Hummen, Roman Matzutt, Daniel Catrein, and Klaus Wehrle. "Maintaining User Control While Storing and Processing Sensor Data in the Cloud." International Journal of Grid and High Performance Computing 5, no. 4 (October 2013): 97–112. http://dx.doi.org/10.4018/ijghpc.2013100107.

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Clouds provide a platform for efficiently and flexibly aggregating, storing, and processing large amounts of data. Eventually, sensor networks will automatically collect such data. A particular challenge regarding sensor data in Clouds is the inherent sensitive nature of sensed information. For current Cloud platforms, the data owner loses control over her sensor data once it enters the Cloud. This imposes a major adoption barrier for bridging Cloud computing and sensor networks, which we address henceforth. After analyzing threats to sensor data in Clouds, the authors propose a Cloud architecture that enables end-to-end control over sensitive sensor data by the data owner. The authors introduce a well-defined entry point from the sensor network into the Cloud, which enforces end-to-end data protection, applies encryption and integrity protection, and grants data access. Additionally, the authors enforce strict isolation of services. The authors show the feasibility and scalability of their Cloud architecture using a prototype and measurements.
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Song, Dawn, Elaine Shi, Ian Fischer, and Umesh Shankar. "Cloud Data Protection for the Masses." Computer 45, no. 1 (January 2012): 39–45. http://dx.doi.org/10.1109/mc.2012.1.

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Singh, Niharika, and Ashutosh Kumar Singh. "Data Privacy Protection Mechanisms in Cloud." Data Science and Engineering 3, no. 1 (November 25, 2017): 24–39. http://dx.doi.org/10.1007/s41019-017-0046-0.

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Dai, Xue Bing, Zhao Jing Wang, and Yan Zhang. "Data Security and Privacy Protection of Cloud Computing." Advanced Materials Research 846-847 (November 2013): 1570–73. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.1570.

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Data security and privacy protection of cloud computing as a new IT application mode are the most valued and concerned issues of the cloud user,and thus of utmost significance to the security of cloud computing. This paper describes and analyzes in detail the risks of data security and privacy showup brought by cloud computing,discusses the protective approaches of data security and privacy in cloud computing environment. Furthermore, this paper based on the newly developed fully homomorphism encryption then proposed a data security scheme which can operate encrypted data directly on cloud server without decrypt while all communication between client and server is encrypted, it can assure data security at the mean time assure the operate efficiency.
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Wei, PengCheng, Dahu Wang, Yu Zhao, Sumarga Kumar Sah Tyagi, and Neeraj Kumar. "Blockchain data-based cloud data integrity protection mechanism." Future Generation Computer Systems 102 (January 2020): 902–11. http://dx.doi.org/10.1016/j.future.2019.09.028.

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Beckham, Olly, Gord Oldman, Julie Karrie, and Dorth Craig. "Techniques used to formulate confidential data by means of fragmentation and hybrid encryption." International research journal of management, IT and social sciences 6, no. 6 (October 15, 2019): 68–86. http://dx.doi.org/10.21744/irjmis.v6n6.766.

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Cloud computing is a concept shifting in the approach how computing resources are deployed and purchased. Even though the cloud has a capable, elastic, and consistent design, several security concerns restrain customers to completely accept this novel technology and move from traditional computing to cloud computing. In the article, we aspire to present a form of a novel architectural model for offering protection to numerous cloud service providers with the intention to devise and extend security means for cloud computing. In this work, we presented a two-tier architecture for security in multi-clouds; one at the client side, and other at the server side. The article presented a security domination outline for multi-clouds and supports security needs like Confidentiality, Integrity, Availability, Authorization, and Non-repudiation for cloud storage. Through this document we have anticipated, HBDaSeC, a secure-computation protocol to ease the challenges of enforcing the protection of data for information security in the cloud.
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M. Dillibabu, M. Dillibabu, S. Kumari S. Kumari, T. Saranya T. Saranya, and R. Preethi R. Preethi. "Assured Protection & Veracity for Cloud Data Using Merkle Hash Tree Algorithm." Indian Journal of Applied Research 3, no. 3 (October 1, 2011): 124–26. http://dx.doi.org/10.15373/2249555x/mar2013/39.

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Dissertations / Theses on the topic "Cloud data protection"

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Oduyiga, Adeshola Oyesanya. "Security in Cloud Storage : A Suitable Security Algorithm for Data Protection." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34428.

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The purpose of this thesis work was to conduct a general research on existing security techniques and come up with a considerable algorithm for data security in cloud storage. Cloud storage is an infrastructure or is a model of computer data storage in which the digital data is stored in logical pools. It unifies object storage for both developers and enterprises, from live applications data to cloud archival. It help to save valuable space on PC computers or mobile devices and provides the easy storage and access of data anywhere in the world. However, just as the benefits of cloud computing abounds, so also are the risks involved. If data are not well secured or encrypted before deployment for storage in the cloud, in case of negligence on the side of the developers, then hackers can gain unauthorized access to the data. The behavior of existing security algorithms on data were studied, the encryption and decryption process of the each algorithm on data was studied and also their weaknesses against attacks. Apart from data encryption, security policies also plays an important roll in cloud storage which was also covered in this report. The research work was conducted through the use of online publications, literature review, books, academic publications and reputable research materials. The study showed that regardless of the challenges in cloud storage, there is still a suitable algorithm for protecting data against attack in the cloud.
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Syckor, Jens. "Dropbox & Co, alles schon ge-cloud?" Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-153998.

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Cloudspeicherdienste sind zu einem Standard für den Austausch großer Datenmengen in virtuellen Gemeinschaften geworden, sowohl im privaten Umfeld als auch im öffentlichen Bereich. Einfache Bedienbarkeit sowie nahtlose Integration in Applikationen, Betriebssystemen und Endgeräten sind wesentliche Bausteine dieses Siegeszuges.
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Sobati, Moghadam Somayeh. "Contributions to Data Privacy in Cloud Data Warehouses." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE2020.

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Actuellement, les scénarios d’externalisation de données deviennent de plus en plus courants avec l’avènement de l’infonuagique. L’infonuagique attire les entreprises et les organisations en raison d’une grande variété d’avantages fonctionnels et économiques.De plus, l’infonuagique offre une haute disponibilité, le passage d’échelle et une reprise après panne efficace. L’un des services plus notables est la base de données en tant que service (Database-as-a-Service), où les particuliers et les organisations externalisent les données, le stockage et la gestion `a un fournisseur de services. Ces services permettent de stocker un entrepôt de données chez un fournisseur distant et d’exécuter des analysesen ligne (OLAP).Bien que l’infonuagique offre de nombreux avantages, elle induit aussi des problèmes de s´sécurité et de confidentialité. La solution usuelle pour garantir la confidentialité des données consiste à chiffrer les données localement avant de les envoyer à un serveur externe. Les systèmes de gestion de base de données sécurisés utilisent diverses méthodes de cryptage, mais ils induisent un surcoût considérable de calcul et de stockage ou révèlent des informations sur les données.Dans cette thèse, nous proposons une nouvelle méthode de chiffrement (S4) inspirée du partage secret de Shamir. S4 est un système homomorphique additif : des additions peuvent être directement calculées sur les données cryptées. S4 trait les points faibles des systèmes existants en réduisant les coûts tout en maintenant un niveau raisonnable de confidentialité. S4 est efficace en termes de stockage et de calcul, ce qui est adéquat pour les scénarios d’externalisation de données qui considèrent que l’utilisateur dispose de ressources de calcul et de stockage limitées. Nos résultats expérimentaux confirment l’efficacité de S4 en termes de surcoût de calcul et de stockage par rapport aux solutions existantes.Nous proposons également de nouveaux schémas d’indexation qui préservent l’ordre des données, OPI et waOPI. Nous nous concentrons sur le problème de l’exécution des requêtes exacts et d’intervalle sur des données chiffrées. Contrairement aux solutions existantes, nos systèmes empêchent toute analyse statistique par un adversaire. Tout en assurant la confidentialité des données, les schémas proposés présentent de bonnes performances et entraînent un changement minimal dans les logiciels existants
Nowadays, data outsourcing scenarios are ever more common with the advent of cloud computing. Cloud computing appeals businesses and organizations because of a wide variety of benefits such as cost savings and service benefits. Moreover, cloud computing provides higher availability, scalability, and more effective disaster recovery rather than in-house operations. One of the most notable cloud outsourcing services is database outsourcing (Database-as-a-Service), where individuals and organizations outsource data storage and management to a Cloud Service Provider (CSP). Naturally, such services allow storing a data warehouse (DW) on a remote, untrusted CSP and running on-line analytical processing (OLAP).Although cloud data outsourcing induces many benefits, it also brings out security and in particular privacy concerns. A typical solution to preserve data privacy is encrypting data locally before sending them to an external server. Secure database management systems use various encryption schemes, but they either induce computational and storage overhead or reveal some information about data, which jeopardizes privacy.In this thesis, we propose a new secure secret splitting scheme (S4) inspired by Shamir’s secret sharing. S4 implements an additive homomorphic scheme, i.e., additions can be directly computed over encrypted data. S4 addresses the shortcomings of existing approaches by reducing storage and computational overhead while still enforcing a reasonable level of privacy. S4 is efficient both in terms of storage and computing, which is ideal for data outsourcing scenarios that consider the user has limited computation and storage resources. Experimental results confirm the efficiency of S4 in terms of computation and storage overhead with respect to existing solutions.Moreover, we also present new order-preserving schemes, order-preserving indexing (OPI) and wrap-around order-preserving indexing (waOPI), which are practical on cloud outsourced DWs. We focus on the problem of performing range and exact match queries over encrypted data. In contrast to existing solutions, our schemes prevent performing statistical and frequency analysis by an adversary. While providing data privacy, the proposed schemes bear good performance and lead to minimal change for existing software
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Skolmen, Dayne Edward. "Protection of personal information in the South African cloud computing environment: a framework for cloud computing adoption." Thesis, Nelson Mandela Metropolitan University, 2016. http://hdl.handle.net/10948/12747.

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Cloud Computing has advanced to the point where it may be considered an attractive proposition for an increasing number of South African organisations, yet the adoption of Cloud Computing in South Africa remains relatively low. Many organisations have been hesitant to adopt Cloud solutions owing to a variety of inhibiting factors and concerns that have created mistrust in Cloud Computing. One of the top concerns identified is security within the Cloud Computing environment. The approaching commencement of new data protection legislation in South Africa, known as the Protection of Personal Information Act (POPI), may provide an ideal opportunity to address the information security-related inhibiting factors and foster a trust relationship between potential Cloud users and Cloud providers. POPI applies to anyone who processes personal information and regulates how they must handle, store and secure that information. POPI is considered to be beneficial to Cloud providers as it gives them the opportunity to build trust with potential Cloud users through achieving compliance and providing assurance. The aim of this dissertation is, therefore, to develop a framework for Cloud Computing adoption that will assist in mitigating the information security-related factors inhibiting Cloud adoption by fostering a trust relationship through compliance with the POPI Act. It is believed that such a framework would be useful to South African Cloud providers and could ultimately assist in the promotion of Cloud adoption in South Africa.
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Xu, Cheng. "Authenticated query processing in the cloud." HKBU Institutional Repository, 2019. https://repository.hkbu.edu.hk/etd_oa/620.

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With recent advances in data-as-a-service (DaaS) and cloud computing, outsourcing data to the cloud has become a common practice. In a typical scenario, the data owner (DO) outsources the data and delegates the query processing service to a service provider (SP). However, as the SP is often an untrusted third party, the integrity of the query results cannot be guaranteed and is thus imperative to be authenticated. To tackle this issue, a typical approach is letting the SP provide a cryptographic proof, which can be used to verify the soundness and completeness of the query results by the clients. Despite extensive research on authenticated query processing for outsourced databases, existing techniques have only considered limited query types. They fail to address a variety of needs demanded by enterprise customers such as supporting aggregate queries over set-valued data, enforcing fine-grained access control, and using distributed computing paradigms. In this dissertation, we take the first step to comprehensively investigate the authenticated query processing in the cloud that fulfills the aforementioned requirements. Security analysis and performance evaluation show that the proposed solutions and techniques are robust and efficient under a wide range of system settings.
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Cerf, Sophie. "control theory for computing systems : application to big-data cloud services & location privacy protection." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAT024.

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Cette thèse présente une application de la théorie du contrôle pour les systèmes informatiques. Un algorithme de contrôle peut gérer des systèmes plus grands et plus complexes, même lorsqu'ils sont particulièrement sensibles aux variations de leur environnement. Cependant, l'application du contrôle aux systèmes informatiques soulève plusieurs défis, par exemple dû au fait qu'aucune physique ne les régisse. D'une part, le cadre mathématique fourni par la théorie du contrôle peut être utilisé pour améliorer l'automatisation, la robustesse et la fiabilité des systèmes informatiques. D'autre part, les défis spécifiques de ces cas d'étude permettent d'élargir la théorie du contrôle elle-même. L'approche adoptée dans ce travail consiste à utiliser deux systèmes informatiques d'application: la protection de vie privée liée à la mobilité et les performances des services clouds. Ces deux cas d'utilisation sont complémentaires par la nature de leurs technologies, par leur échelle et par leurs utilisateurs finaux.La popularité des appareils mobiles a favorisé la diffusion et la collecte des données de localisation, que ce soit pour que l'utilisateur bénéficie d'un service personnalisé (e.g. une planification d'itinéraire) ou pour que le prestataire de services tire des informations utiles des bases de données de mobilité (e.g. la popularité de lieux). En effet, de nombreuses informations peuvent être extraites de données de localisation, y compris des données personnelles très sensibles. Pour remédier à cette atteinte à la vie privée, des mécanismes de protection spécifiques aux données de mobilité (LPPM) ont été élaborés. Ce sont des algorithmes qui modifient les données de localisation de l'utilisateur, dans le but de cacher des informations sensibles. Cependant, ces outils ne sont pas facilement configurables par des non experts et sont des processus statiques qui ne s'adaptent pas à la mobilité de l'utilisateur. Dans cette thèse, nous développons deux outils, l'un pour les bases de données déjà collectées et l'autre pour l'utilisation en ligne, qui garantissent aux utilisateurs des niveaux de protection de la vie privée et de préservation de la qualité des services en configurant les LPPMs. Nous présentons la première formulation du problème en termes de théorie du contrôle (système et contrôleur, signaux d’entrée et de sortie), et un contrôleur PI pour servir de démonstration d’applicabilité. Dans les deux cas, la conception, la mise en œuvre et la validation ont été effectuées par le biais d'expériences utilisant des données d'utilisateurs réels recueillies sur le terrain.L'essor récent des bigdata a conduit au développement de programmes capables de les analyser, tel que MapReduce. Les progrès des pratiques informatiques ont également permis d'établir le modèle du cloud (où il est possible de louer des ressources de bas niveau pour permettre le développement d'applications de niveau supérieur sans se préoccuper d'investissement ou de maintenance) comme une solution incontournable pour tous types d'utilisateurs. Garantir les performances des tâches MapReduce exécutées sur les clouds est donc une préoccupation majeure pour les grandes entreprises informatiques et leurs clients. Dans ce travail, nous développons des techniques avancées de contrôle du temps d'exécution des tâches et de la disponibilité de la plate-forme en ajustant la taille du cluster de ressources et en réalisant un contrôle d'admission, fonctionnant quelle que soit la charge des clients. Afin de traiter les non linéarités de MapReduce, un contrôleur adaptatif a été conçu. Pour réduire l'utilisation du cluster (qui entraîne des coûts financiers et énergétiques considérables), nous présentons une nouvelle formulation du mécanisme de déclenchement du contrôle événementiel, combiné à un contrôleur prédictif optimal. L'évaluation est effectuée sur un benchmark s'exécutant en temps réel sur un cluster, et en utilisant des charges de travail industrielles
This thesis presents an application of Control Theory for Computing Systems. It aims at investigating techniques to build and control efficient, dependable and privacy-preserving computing systems. Ad-hoc service configuration require a high level of expertise which could benefit from automation in many ways. A control algorithm can handle bigger and more complex systems, even when they are extremely sensitive to variations in their environment. However, applying control to computing systems raises several challenges, e.g. no physics governs the applications. On one hand, the mathematical framework provided by control theory can be used to improve automation and robustness of computing systems. Moreover, the control theory provides by definition mathematical guarantees that its objectives will be fulfilled. On the other hand, the specific challenges of such use cases enable to expand the control theory itself. The approach taken in this work is to use two application computing systems: location privacy and cloud control. Those two use-cases are complementary in the nature of their technologies and softwares, their scale and in their end-users.The widespread of mobile devices has fostered the broadcasting and collection of users’ location data. It could be for the user to benefit from a personalized service (e.g. weather forecast or route planning) or for the service provider or any other third party to derive useful information from the mobility databases (e.g. road usage frequency or popularity of places). Indeed, many information can be retrieved from location data, including highly sensitive personal data. To overcome this privacy breach, Location Privacy Protection Mechanisms (LPPMs) have been developed. They are algorithm that modify the user’s mobility data, hopefully to hide some sensitive information. However, those tools are not easily configurable by non experts and are static processes that do not adapt to the user’s mobility. We develop two tools, one for already collected databases and one for online usage, that, by tuning the LPPMs, guarantee to the users objective-driven levels of privacy protection and of service utility preservation. First, we present an automated tool able to choose and configure LPPMs to protect already collected databases while ensuring a trade-off between privacy protection and database processing quality. Second, we present the first formulation of the location privacy challenge in control theory terms (plant and control, disturbance and performance signals), and a feedback controller to serve as a proof of concept. In both cases, design, implementation and validation has been done through experiments using data of real users collected on the field.The surge in data generation of the last decades, the so-called bigdata, has lead to the development of frameworks able to analyze them, such as the well known MapReduce. Advances in computing practices has also settled the cloud paradigms (where low-level resources can be rented to allow the development of higher level application without dealing with consideration such as investment in hardware or maintenance) as premium solution for all kind of users. Ensuring the performances of MapReduce jobs running on clouds is thus a major concern for the big IT companies and their clients. In this work, we develop advanced monitoring techniques of the jobs execution time and the platform availability by tuning the resource cluster size and realizing admission control, in spite of the unpredictable client workload. In order to deal with the non linearities of the MapReduce system, a robust adaptive feedback controller has been designed. To reduce the cluster utilization (leading to massive financial and energetic costs), we present a new event-based triggering mechanism formulation combined with an optimal predictive controller. Evaluation is done on a MapReduce benchmark suite running on a large-scale cluster, and using real jobs workloads
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Van, der Schyff Karl Izak. "Cloud information security : a higher education perspective." Thesis, Rhodes University, 2014. http://hdl.handle.net/10962/d1011607.

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In recent years higher education institutions have come under increasing financial pressure. This has not only prompted universities to investigate more cost effective means of delivering course content and maintaining research output, but also to investigate the administrative functions that accompany them. As such, many South African universities have either adopted or are in the process of adopting some form of cloud computing given the recent drop in bandwidth costs. However, this adoption process has raised concerns about the security of cloud-based information and this has, in some cases, had a negative impact on the adoption process. In an effort to study these concerns many researchers have employed a positivist approach with little, if any, focus on the operational context of these universities. Moreover, there has been very little research, specifically within the South African context. This study addresses some of these concerns by investigating the threats and security incident response life cycle within a higher education cloud. This was done by initially conducting a small scale survey and a detailed thematic analysis of twelve interviews from three South African universities. The identified themes and their corresponding analyses and interpretation contribute on both a practical and theoretical level with the practical contributions relating to a set of security driven criteria for selecting cloud providers as well as recommendations for universities who have or are in the process of adopting cloud computing. Theoretically several conceptual frameworks are offered allowing the researcher to convey his understanding of how the aforementioned practical concepts relate to each other as well as the concepts that constitute the research questions of this study.
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Villarino, Marzo Jorge. "La privacidad en el entorno del cloud computing." Doctoral thesis, Universitat Abat Oliba, 2017. http://hdl.handle.net/10803/456904.

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L’evolució tecnològica ha tingut un enorme impacte en els drets fonamentals, donant lloc al naixement de la quarta generació de drets. Un d’aquests drets ha sigut, sens dubte, el dret a la protecció de dades. La privacitat constitueix una de les grans preocupacions de la societat. Per aquesta raó, qualsevol desenvolupament tecnològic planteja nous reptes a la regulació de la protecció de dades. La computació en núvol és una nova realitat tecnològica caracteritzada per la ubiqüitat, l’elasticitat, el dinamisme, la virtualització, l’escalabilitat i el pagament sota demanda. En aquest treball s’analitza si la regulació actual del dret fonamental a la protecció de dades és vàlida per fer front als reptes que planteja la computació en núvol o si és necessari un nou règim jurídic.
La evolución tecnológica ha tenido un enorme impacto en los derechos fundamentales, dando lugar al nacimiento de la cuarta generación de derechos. Uno de estos derechos ha sido, sin duda, el derecho a la protección de datos. La privacidad constituye una de las grandes preocupaciones de la sociedad. Por esta razón, cualquier desarrollo tecnológico plantea nuevos retos a la regulación de la protección de datos La computación en nube es una nueva realidad tecnológica caracterizada por la ubicuidad, la elasticidad, el dinamismo, la virtualización, la escalabilidad y el pago bajo demanda. En este trabajo se analiza si la regulación actual del derecho fundamental a la protección de datos es válida para hacer frente a los retos que plantea la computación en nube o si es necesario un nuevo régimen jurídico
The technological evolution has had a great impact on fundamental rights, giving rise to the fourth generation of human rights. One of these has been, with no doubts, the right to data protection. Privacy is one of the main concerns of society. For this reason, any new technological development poses new challenges to data protection regulation. Cloud computing is a new technological reality characterized by ubiquity, elasticity, dynamism, virtualization, scalability and pay on demand. In this dissertation we will analyze if the current data protection regulation is valid to face the new challenges pose by cloud computing or if a new legal regime is mandatory.
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Imine, Youcef. "Cloud computing security." Thesis, Compiègne, 2019. http://www.theses.fr/2019COMP2520.

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Ces dernières années, nous assistons à une immense révolution numérique de l’internet où de nombreuses applications, innovantes telles que l’internet des objets, les voitures autonomes, etc., ont émergé. Par conséquent, l’adoption des technologies d’externalisations des données, telles que le cloud ou le fog computing, afin de gérer cette expansion technologique semble inévitable. Cependant, l’utilisation du cloud ou du fog computing en tant que plateforme d’externalisation pour le stockage ou le partage des données crée plusieurs défis scientifiques. En effet, externaliser ses données signifie que l’utilisateur perd le contrôle sur ces derniers. D’où la sécurité des données devienne une préoccupation majeure qui doit être proprement traitée. C’est dans ce contexte que s’inscrivent les travaux de cette thèse dans laquelle nous avons déterminé dans un premier temps les principaux problèmes de sécurité liés à l’adoption du cloud et du fog computing. Puis, nous avons adressé trois problématiques de sécurité majeure, qui sont : 1 - Le contrôle d’accès aux données dans une architecture de type Cloud storage, où nous avons proposé une nouvelle solution de contrôle d’accès basée sur le chiffrement à base d’attributs. Notre solution assure un contrôle d’accès souple et à grains fins. De plus, elle permet d’effectuer une révocation immédiate des utilisateurs et des attributs sans aucune mise à jour des clés de chiffrement fournies aux utilisateurs. 2 - Le problème de l’authentification mutuelle entre les utilisateurs et les serveurs Fog dans une architecture Fog computing, où nous avons proposé un nouveau schéma d’authentification efficace, qui assure l’authentification mutuelle et qui est robuste contre les comportements malicieux des serveurs Fog. 3 - Le problème de traçabilité et de la protection de la vie privée dans le cadre des applications de partage d’informations publiques, où nous avons proposé une nouvelle solution pour le partage d’informations publiques assurant le service de traçabilité tout en préservant les informations privées des utilisateurs. Avec notre solution, les serveurs d’externalisations authentifient les utilisateurs sans pouvoir obtenir des informations sur leur vie privée. En cas de comportements malicieux, notre solution permet de tracer les utilisateurs malveillants grâce à une autorité
These last years, we are witnessing a real digital revolution of Internet where many innovative applications such as Internet of Things, autonomous cars, etc., have emerged. Consequently, adopting externalization technologies such as cloud and fog computing to handle this technological expansion seems to be an inevitable outcome. However, using the cloud or fog computing as a data repository opens many challenges in prospect. This thesis addresses security issues in cloud and fog computing which is a major challenge that need to be appropriately overcomed. Indeed, adopting these technologies means that the users lose control over their own data, which exposes it to several security threats. Therefore, we first investigated the main security issues facing the adoption of cloud and fog computing technologies. As one of the main challenges pointed in our investigation, access control is indeed a cornerstone of data security. An efficient access control mechanism must provide enforced and flexible access policies that ensure data protection, even from the service provider. Hence, we proposed a novel secure and efficient attribute based access control scheme for cloud data-storage applications. Our solution ensures flexible and fine-grained access control and prevents security degradations. Moreover, it performs immediate users and attributes revocation without any key regeneration. Authentication service in fog computing architecture is another issue that we have addressed in this thesis. Some traditional authentication schemes endure latency issues while others do not satisfy fog computing requirements such as mutual authentication between end-devices and fog servers. Thus, we have proposed a new, secure and efficient authentication scheme that ensures mutual authentication at the edge of the network and remedies to fog servers' misbehaviors.Finally, we tackled accountability and privacy-preserving challenges in information-sharing applications for which several proposals in the literature have treated privacy issues, but few of them have considered accountability service. Therefore, we have proposed a novel accountable privacy preserving solution for public information sharing in data externalization platforms. Externalization servers in our scheme authenticate any user in the system without violating its privacy. In case of misbehavior, our solution allows to trace malicious users thanks to an authority
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Trebulová, Debora. "Zálohování dat a datová úložiště." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2017. http://www.nusl.cz/ntk/nusl-318599.

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This diploma thesis focuses on ways of backing up data and their practical use in a specific proposal for Transroute Group s.r.o.. In the introduction part the theoretical knowledge on this issue is presented. Next part of the thesis deals with the analysis of the current state of backup in the company. This section is followed by a chapter where several solutions are presented each with their financial evaluation. The ending part is composed of the choice of a specific solution and a time estimate for its implementation.
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Books on the topic "Cloud data protection"

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Data Security Council of India. Data protection challenges in cloud computing: An Indian perspective : study report. New Delhi: Data Security Council of India, 2010.

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Brennscheidt, Kirstin. Cloud Computing und Datenschutz. Baden-Baden: Nomos, 2013.

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Cheung, Anne S. Y., and Rolf H. Weber. Privacy and legal issues in cloud computing. Cheltenham, UK ; Northampton, MA, USA: Edward Elgar Publishing., 2015.

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Kalteis, Michael. Neue Technologien und netzbasierte Medien als Herausforderungen des Datenschutzrechts: Untersuchungen am Beispiel von Cloud Computing, Smart Metering und dem Einsatz mobiler Apps. Wien: Verlag Österreich, 2014.

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Auditing cloud computing: A security and privacy guide. Hoboken, N.J: John Wiley & Sons, 2011.

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United States. Congress. House. Committee on Homeland Security. Subcommittee on Cybersecurity, Infrastructure Protection, and Security Technologies. Cloud computing: What are the security implications? : hearing before the Subcommittee on Cybersecurity, Infrastructure Protection, and Security Technologies of the Committee on Homeland Security, House of Representatives, One Hundred Twelfth Congress, first session, October 6, 2011. Washington: U.S. Government Printing Office, 2012.

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Cloud computing: An overview of the technology and the issues facing American innovators : hearing before the Subcommittee on Intellectual Property, Competition, and the Internet of the Committee on the Judiciary, House of Representatives, One Hundred Twelfth Congress, second session, July 25, 2012. Washington: U.S. G.P.O., 2012.

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Ernesto, Pimentel, Zavattaro Gianluigi, and SpringerLink (Online service), eds. Service-Oriented and Cloud Computing: First European Conference, ESOCC 2012, Bertinoro, Italy, September 19-21, 2012. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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United, States Congress House Committee on the Judiciary Subcommittee on Crime Terrorism Homeland Security and Investigations. ECPA: Lawful access to stored content : hearing before the Subcommittee on Crime, Terrorism, Homeland Security, and Investigations of the Committee on the Judiciary, House of Representatives, One Hundred Thirteenth Congress, first session, March 19, 2013. Washington: U.S. Government Printing Office, 2013.

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Cappellini, Vito, ed. Electronic Imaging & the Visual Arts. EVA 2014 Florence. Florence: Firenze University Press, 2014. http://dx.doi.org/10.36253/978-88-6655-573-5.

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Information Technologies of interest for Culture Heritage are presented: multimedia systems, data-bases, data protection, access to digital content, Virtual Galleries. Particular reference is reserved to digital images (Electronic Imaging & the Visual Arts), regarding Cultural Institutions (Museums, Libraries, Palace - Monuments, Archaeological Sites). The International Conference includes the following Sessions: Strategic Issues; EC Projects and Related Networks & Initiatives; 2D - 3D Technologies and Applications; Virtual Galleries - Museums and Related Initiatives; Access to the Culture Information. Three Workshops regard: International Cooperation; Innovation and Enterprise; e.Culture Cloud.
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Book chapters on the topic "Cloud data protection"

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De Capitani di Vimercati, Sabrina, Sara Foresti, and Pierangela Samarati. "Data Protection in Cloud Scenarios." In Lecture Notes in Computer Science, 3–10. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-29883-2_1.

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Wei, Yu, and Yongsheng Zhang. "Cloud Computing Data Security Protection Strategy." In Cloud Computing and Security, 376–86. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00006-6_34.

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Garg, Disha. "Privacy in Cloud Healthcare Data." In Data Protection and Privacy in Healthcare, 21–36. Boca Raton, FL : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9781003048848-2.

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Lehner, Jonas, Andreas Oberweis, and Gunther Schiefer. "Data Protection in the Cloud - The MimoSecco Approach." In Trusted Cloud Computing, 177–86. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12718-7_11.

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Batman, Ayşe Necibe. "European Cloud Service Data Protection Certification." In Regulating New Technologies in Uncertain Times, 261–80. The Hague: T.M.C. Asser Press, 2019. http://dx.doi.org/10.1007/978-94-6265-279-8_14.

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Praveena, D., S. Thanga Ramya, V. P. Gladis Pushparathi, Pratap Bethi, and S. Poopandian. "Hybrid Cloud Data Protection Using Machine Learning Approach." In Studies in Big Data, 151–66. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75657-4_7.

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Kunz, Thomas, Annika Selzer, and Ulrich Waldmann. "Automatic Data Protection Certificates for Cloud-Services based on Secure Logging." In Trusted Cloud Computing, 59–75. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12718-7_5.

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Creese, Sadie, Paul Hopkins, Siani Pearson, and Yun Shen. "Data Protection-Aware Design for Cloud Services." In Lecture Notes in Computer Science, 119–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10665-1_11.

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Lu, Xin, Lifeng Cao, Xuehui Du, and Zhiyan Hu. "A Tag-Based Protection Method for Multi-tenant Data Security." In Cloud Computing and Security, 553–65. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00009-7_50.

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Mei, Rui, Han-Bing Yan, Yongqiang He, Qinqin Wang, Shengqiang Zhu, and Weiping Wen. "Considerations on Evaluation of Practical Cloud Data Protection." In Communications in Computer and Information Science, 51–69. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-8285-9_4.

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AbstractWith the continuous growth of enterprises’ digital transformation, business-driven cloud computing has seen tremendous growth. The security community has proposed a large body of technical mechanisms, operational processes, and practical solutions to achieve cloud security. In addition, diverse jurisdictions also present regulatory requirements on data protection to mitigate possible risks, for instance, unauthorized access, data leakage, sensitive information and privacy disclosure. In view of this, several practical standards, frameworks, and best practices in the industry are proposed to evaluate and improve the protection level of cloud data. However, few evaluation models can conduct a comprehensive quantitative evaluation for cloud data protection that includes security, privacy, and even ethical considerations. In this paper, we first make a comprehensive review of cloud data security and privacy issues, especially also including ethical concerns that we consider as a type of specific risks caused by human factors, which refers to acting honorably, honestly, justly, and legally, due diligence, and due care. Then, we propose a novel evaluation model for cloud data protection that can quantitatively assess the protection level. Finally, based on the parallel evaluation between manual assessment by experts and our evaluation model, results show that our evaluation model is consistent with the manual evaluation conclusion.
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Conference papers on the topic "Cloud data protection"

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Benjamin, Bruce, Joel Coffman, Hadi Esiely-Barrera, Kaitlin Farr, Dane Fichter, Daniel Genin, Laura Glendenning, et al. "Data Protection in OpenStack." In 2017 IEEE 10th International Conference on Cloud Computing (CLOUD). IEEE, 2017. http://dx.doi.org/10.1109/cloud.2017.77.

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Matveev, Artem. "Cost-Efficient Data Privacy Protection in Multi Cloud Storage." In 3rd International Conference on Data Mining and Machine Learning (DMML 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.120706.

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Data privacy in the cloud is a big concern for all of its users, especially for public clouds. Modern trends in studies utilise multiple clouds to achieve data privacy protection. Most of the present studies focus on business-oriented solutions, but current study aims to create a solution for individual users which would not increase the cost of ownership, and provide enough flexibility and privacy protection by combining password protection, key-derivation, multilayer encryption and key distribution across multiple clouds. New design allows to use single cloud to store protected user data, meanwhile use free plans on other clouds to store key information on others and thereby does not rise a cost of the solution. As a result, proposed design gives multiple layers of protection of Data Privacy while having a low cost of use. With some further adaptation it could be proposed as a business solution.
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Shi, Yue. "Data Security and Privacy Protection in Public Cloud." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8622531.

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Aparajit, Srushti, Rashi Shah, Riddhi Chopdekar, and Rupali Patil. "Data Protection: The Cloud Security Perspective." In 2022 3rd International Conference for Emerging Technology (INCET). IEEE, 2022. http://dx.doi.org/10.1109/incet54531.2022.9825151.

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Holle, Ronald L., Nicholas W. S. Demetriades, and Amitabh Nag. "Lightning warnings with NLDN cloud and cloud-to-ground lightning data." In 2014 International Conference on Lightning Protection (ICLP). IEEE, 2014. http://dx.doi.org/10.1109/iclp.2014.6973143.

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Colombo, Maurizio, Rasool Asal, Quang Hieu Hieu, Fadi Ali El-Moussa, Ali Sajjad, and Theo Dimitrakos. "Data Protection as a Service in the Multi-Cloud Environment." In 2019 IEEE 12th International Conference on Cloud Computing (CLOUD). IEEE, 2019. http://dx.doi.org/10.1109/cloud.2019.00025.

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Marikyan, Davit, Savvas Papagiannidis, Rajiv Ranjan, and Omer Rana. "General data protection regulation." In UCC '21: 2021 IEEE/ACM 14th International Conference on Utility and Cloud Computing. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3492323.3495620.

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Sinkar, Yogita Deepak, and C. Rajabhushanam. "Data Protection On Cloud Using GWOA Model." In 2021 International Conference on Computer Communication and Informatics (ICCCI). IEEE, 2021. http://dx.doi.org/10.1109/iccci50826.2021.9402346.

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Chen, Lingfeng, and Doan B. Hoang. "Novel Data Protection Model in Healthcare Cloud." In Communication (HPCC). IEEE, 2011. http://dx.doi.org/10.1109/hpcc.2011.148.

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Zhang, Wei, Xinwei Sun, and Tao Xu. "Data privacy protection using multiple cloud storages." In 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC). IEEE, 2013. http://dx.doi.org/10.1109/mec.2013.6885340.

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