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

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

Privacy-Enhanced Dependable and Searchable Storage in a Cloud-of-Clouds

In this dissertation we will propose a solution for a trustable and privacy-enhanced storage architecture based on a multi-cloud approach. The solution provides the necessary support for multi modal on-line searching operation on data that is always maintained encrypted on used cloud-services. We implemented a system prototype, conducting an experimental evaluation. Our results show that the proposal offers security and privacy guarantees, and provides efficient information retrieval capabilities without sacrificing precision and recall properties on the supported search operations. There is a constant increase in the demand of cloud services, particularly cloud-based storage services. These services are currently used by different applications as outsourced storage services, with some interesting advantages. Most personal and mobile applications also offer the user the choice to use the cloud to store their data, transparently and sometimes without entire user awareness and privacy-conditions, to overcome local storage limitations. Companies might also find that it is cheaper to outsource databases and keyvalue stores, instead of relying on storage solutions in private data-centers. This raises the concern about data privacy guarantees and data leakage danger. A cloud system administrator can easily access unprotected data and she/he could also forge, modify or delete data, violating privacy, integrity, availability and authenticity conditions. A possible solution to solve those problems would be to encrypt and add authenticity and integrity proofs in all data, before being sent to the cloud, and decrypting and verifying authenticity or integrity on data downloads. However this solution can be used only for backup purposes or when big data is not involved, and might not be very practical for online searching requirements over large amounts of cloud stored data that must be searched, accessed and retrieved in a dynamic way. Those solutions also impose high-latency and high amount of cloud inbound/outbound traffic, increasing the operational costs. Moreover, in the case of mobile or embedded devices, the power, computation and communication constraints cannot be ignored, since indexing, encrypting/decrypting and signing/verifying all data will be computationally expensive. To overcome the previous drawbacks, in this dissertation we propose a solution for a trustable and privacy-enhanced storage architecture based on a multi-cloud approach, providing privacy-enhanced, dependable and searchable support. Our solution provides the necessary support for dependable cloud storage and multi modal on-line searching operations over always-encrypted data in a cloud-of-clouds. We implemented a system prototype, conducting an experimental evaluation of the proposed solution, involving the use of conventional storage clouds, as well as, a high-speed in-memory cloud-storage backend. Our results show that the proposal offers the required dependability properties and privacy guarantees, providing efficient information retrieval capabilities without sacrificing precision and recall properties in the supported indexing and search operations

Enhancing the Programmability of Cloud Object Storage

En un món que depèn cada vegada més de la tecnologia, les dades digitals es generen a una escala sense precedents. Això fa que empreses que requereixen d'un gran espai d'emmagatzematge, com Netflix o Dropbox, utilitzin solucions d'emmagatzematge al núvol. Mes concretament, l'emmagatzematge d'objectes, donada la seva simplicitat, escalabilitat i alta disponibilitat. No obstant això, aquests magatzems s'enfronten a tres desafiaments principals: 1) Gestió flexible de càrregues de treball de múltiples usuaris. Normalment, els magatzems d'objectes són sistemes multi-usuari, la qual cosa significa que tots ells comparteixen els mateixos recursos, el que podria ocasionar problemes d'interferència. A més, és complex administrar polítiques d'emmagatzematge heterogènies a gran escala en ells. 2) Autogestió de dades. Els magatzems d'objectes no ofereixen molta flexibilitat pel que fa a l'autogestió de dades per part dels usuaris. Típicament, són sistemes rígids, la qual cosa impedeix gestionar els requisits específics dels objectes. 3) Còmput elàstic prop de les dades. Situar els càlculs prop de les dades pot ser útil per reduir la transferència de dades. Però, el desafiament aquí és com aconseguir la seva elasticitat sense provocar contenció de recursos i interferències en la capa d'emmagatzematge. En aquesta tesi presentem tres contribucions innovadores que resolen aquests desafiaments. En primer lloc, presentem la primera arquitectura d'emmagatzematge definida per programari (SDS) per a magatzems d'objectes que separa les capes de control i de dades. Això permet gestionar les càrregues de treball de múltiples usuaris d'una manera flexible i dinàmica. En segon lloc, hem dissenyat una nova abstracció de polítiques anomenada "microcontrolador" que transforma els objectes comuns en objectes intel·ligents, permetent als usuaris programar el seu comportament. Finalment, presentem la primera plataforma informàtica "serverless" guiada per dades i elàstica, que mitiga els problemes de col·locar el càlcul prop de les dades.En un mundo que depende cada vez más de la tecnología, los datos digitales se generan a una escala sin precedentes. Esto hace que empresas que requieren de un gran espacio de almacenamiento, como Netflix o Dropbox, usen soluciones de almacenamiento en la nube. Mas concretamente, el almacenamiento de objectos, dada su escalabilidad y alta disponibilidad. Sin embargo, estos almacenes se enfrentan a tres desafíos principales: 1) Gestión flexible de cargas de trabajo de múltiples usuarios. Normalmente, los almacenes de objetos son sistemas multi-usuario, lo que significa que todos ellos comparten los mismos recursos, lo que podría ocasionar problemas de interferencia. Además, es complejo administrar políticas de almacenamiento heterogéneas a gran escala en ellos. 2) Autogestión de datos. Los almacenes de objetos no ofrecen mucha flexibilidad con respecto a la autogestión de datos por parte de los usuarios. Típicamente, son sistemas rígidos, lo que impide gestionar los requisitos específicos de los objetos. 3) Cómputo elástico cerca de los datos. Situar los cálculos cerca de los datos puede ser útil para reducir la transferencia de datos. Pero, el desafío aquí es cómo lograr su elasticidad sin provocar contención de recursos e interferencias en la capa de almacenamiento. En esta tesis presentamos tres contribuciones que resuelven estos desafíos. En primer lugar, presentamos la primera arquitectura de almacenamiento definida por software (SDS) para almacenes de objetos que separa las capas de control y de datos. Esto permite gestionar las cargas de trabajo de múltiples usuarios de una manera flexible y dinámica. En segundo lugar, hemos diseñado una nueva abstracción de políticas llamada "microcontrolador" que transforma los objetos comunes en objetos inteligentes, permitiendo a los usuarios programar su comportamiento. Finalmente, presentamos la primera plataforma informática "serverless" guiada por datos y elástica, que mitiga los problemas de colocar el cálculo cerca de los datos.In a world that is increasingly dependent on technology, digital data is generated in an unprecedented way. This makes companies that require large storage space, such as Netflix or Dropbox, use cloud object storage solutions. This is mainly thanks to their built-in characteristics, such as simplicity, scalability and high-availability. However, cloud object stores face three main challenges: 1) Flexible management of multi-tenant workloads. Commonly, cloud object stores are multi-tenant systems, meaning that all tenants share the same system resources, which could lead to interference problems. Furthermore, it is now complex to manage heterogeneous storage policies in a massive scale. 2) Data self-management. Cloud object stores themselves do not offer much flexibility regarding data self-management by tenants. Typically, they are rigid, which prevent tenants to handle the specific requirements of their objects. 3) Elastic computation close to the data. Placing computations close to the data can be useful to reduce data transfers. But, the challenge here is how to achieve elasticity in those computations without provoking resource contention and interferences in the storage layer. In this thesis, we present three novel research contributions that solve the aforementioned challenges. Firstly, we introduce the first Software-defined Storage (SDS) architecture for cloud object stores that separates the control plane from the data plane, allowing to manage multi-tenant workloads in a flexible and dynamic way. For example, by applying different service levels of bandwidth to different tenants. Secondly, we designed a novel policy abstraction called microcontroller that transforms common objects into smart objects, enabling tenants to programmatically manage their behavior. For example, a content-level access control microcontroller attached to an specific object to filter its content depending on who is accessing it. Finally, we present the first elastic data-driven serverless computing platform that mitigates the resource contention problem of placing computation close to the data

Data security in cloud storage services

Cloud Computing is considered to be the next-generation architecture for ICT where it moves the application software and databases to the centralized large data centers. It aims to offer elastic IT services where clients can benefit from significant cost savings of the pay-per-use model and can easily scale up or down, and do not have to make large investments in new hardware. However, the management of the data and services in this cloud model is under the control of the provider. Consequently, the cloud clients have less control over their outsourced data and they have to trust cloud service provider to protect their data and infrastructure from both external and internal attacks. This is especially true with cloud storage services. Nowadays, users rely on cloud storage as it offers cheap and unlimited data storage that is available for use by multiple devices (e.g. smart phones, tablets, notebooks, etc.). Besides famous cloud storage providers, such as Amazon, Google, and Microsoft, more and more third-party cloud storage service providers are emerging. These services are dedicated to offering more accessible and user friendly storage services to cloud customers. Examples of these services include Dropbox, Box.net, Sparkleshare, UbuntuOne or JungleDisk. These cloud storage services deliver a very simple interface on top of the cloud storage provided by storage service providers. File and folder synchronization between different machines, sharing files and folders with other users, file versioning as well as automated backups are the key functionalities of these emerging cloud storage services. Cloud storage services have changed the way users manage and interact with data outsourced to public providers. With these services, multiple subscribers can collaboratively work and share data without concerns about their data consistency, availability and reliability. Although these cloud storage services offer attractive features, many customers have not adopted these services. Since data stored in these services is under the control of service providers resulting in confidentiality and security concerns and risks. Therefore, using cloud storage services for storing valuable data depends mainly on whether the service provider can offer sufficient security and assurance to meet client requirements. From the way most cloud storage services are constructed, we can notice that these storage services do not provide users with sufficient levels of security leading to an inherent risk on users\u27 data from external and internal attacks. These attacks take the form of: data exposure (lack of data confidentiality); data tampering (lack of data integrity); and denial of data (lack of data availability) by third parties on the cloud or by the cloud provider himself. Therefore, the cloud storage services should ensure the data confidentiality in the following state: data in motion (while transmitting over networks), data at rest (when stored at provider\u27s disks). To address the above concerns, confidentiality and access controllability of outsourced data with strong cryptographic guarantee should be maintained. To ensure data confidentiality in public cloud storage services, data should be encrypted data before it is outsourced to these services. Although, users can rely on client side cloud storage services or software encryption tools for encrypting user\u27s data; however, many of these services fail to achieve data confidentiality. Box, for example, does not encrypt user files via SSL and within Box servers. Client side cloud storage services can intentionally/unintentionally disclose user decryption keys to its provider. In addition, some cloud storage services support convergent encryption for encrypting users\u27 data exposing it to “confirmation of a file attack. On the other hand, software encryption tools use full-disk encryption (FDE) which is not feasible for cloud-based file sharing services, because it encrypts the data as virtual hard disks. Although encryption can ensure data confidentiality; however, it fails to achieve fine-grained access control over outsourced data. Since, public cloud storage services are managed by un-trusted cloud service provider, secure and efficient fine-grained access control cannot be realized through these services as these policies are managed by storage services that have full control over the sharing process. Therefore, there is not any guarantee that they will provide good means for efficient and secure sharing and they can also deduce confidential information about the outsourced data and users\u27 personal information. In this work, we would like to improve the currently employed security measures for securing data in cloud store services. To achieve better data confidentiality for data stored in the cloud without relying on cloud service providers (CSPs) or putting any burden on users, in this thesis, we designed a secure cloud storage system framework that simultaneously achieves data confidentiality, fine-grained access control on encrypted data and scalable user revocation. This framework is built on a third part trusted (TTP) service that can be employed either locally on users\u27 machine or premises, or remotely on top of cloud storage services. This service shall encrypts users data before uploading it to the cloud and decrypts it after downloading from the cloud; therefore, it remove the burden of storing, managing and maintaining encryption/decryption keys from data owner\u27s. In addition, this service only retains user\u27s secret key(s) not data. Moreover, to ensure high security for these keys, it stores them on hardware device. Furthermore, this service combines multi-authority ciphertext policy attribute-based encryption (CP-ABE) and attribute-based Signature (ABS) for achieving many-read-many-write fine-grained data access control on storage services. Moreover, it efficiently revokes users\u27 privileges without relying on the data owner for re-encrypting massive amounts of data and re-distributing the new keys to the authorized users. It removes the heavy computation of re-encryption from users and delegates this task to the cloud service provider (CSP) proxy servers. These proxy servers achieve flexible and efficient re-encryption without revealing underlying data to the cloud. In our designed architecture, we addressed the problem of ensuring data confidentiality against cloud and against accesses beyond authorized rights. To resolve these issues, we designed a trusted third party (TTP) service that is in charge of storing data in an encrypted format in the cloud. To improve the efficiency of the designed architecture, the service allows the users to choose the level of severity of the data and according to this level different encryption algorithms are employed. To achieve many-read-many-write fine grained access control, we merge two algorithms (multi-authority ciphertext policy attribute-based encryption (MA- CP-ABE) and attribute-based Signature (ABS)). Moreover, we support two levels of revocation: user and attribute revocation so that we can comply with the collaborative environment. Last but not least, we validate the effectiveness of our design by carrying out a detailed security analysis. This analysis shall prove the correctness of our design in terms of data confidentiality each stage of user interaction with the cloud

Composable and Robust Outsourced Storage

The security of data outsourcing mechanisms has become a crucial aspect of today\u27s IT infrastructures and are the cryptographic foundations of real-world applications. The very fundamental goals are ensuring storage integrity and auditability, confidentiality, and access pattern hiding, as well as combinations of all of them. Despite sharing a common setting, security analyses of these tasks are often performed in a stand-alone fashion expressed in different models, which makes it hard to assess the overall security of a protocol or application involving several security schemes at once. In this work, we fill this gap and propose a composable framework suitable to capture various aspects of outsourced storage security and its applications. We instantiate the basic client-server setting in this model, where the goal of the honest client is to retain security in the presence of a malicious server. Three specific contributions of this paper are: 1.) We present a novel definition for secure and robust outsourcing schemes and underline why this is needed in practice. Our definition is stronger than previous definitions for oblivious RAM or software protection in that it assures strong security guarantees against active attacks. Schemes meeting the definition not only assure that an attacker cannot learn the access pattern, but guarantee resilience to errors and the prevention of targeted attacks to specific locations. Unfortunately, several existing schemes cannot achieve this high level of security. For completeness, we provide a protocol based on Path ORAM that showcases that stronger security is actually achievable. 2.) We present a novel definition for auditable storage, capturing the guarantee that a successful audit implies that the current server state allows the client to retrieve his data. We develop an audit mechanism, based on secure and robust outsourcing schemes, that is similar to the construction by Cash et al. (Eurocrpyt 2013), but is universally composable and fault-tolerant. 3.) We revisit the security claim of a widely-used challenge-response audit mechanism, in which the server has to compute a hash $H(F||c)$ on the file $F$ concatenated with a uniformly random challenge $c$ chosen by the client. Being concerned with composable security, we prove that this audit mechanism is not secure, even in the random oracle model, without additional assumptions. The composable security of this basic audit scheme was implicitly assumed in Ristenpart et al. (Eurocrypt 2011). To complete the picture, we state the additional assumptions for this audit mechanism to be provably secure and investigate the (in)applicability of hash-function constructions in this setting

TOWARDS ENHANCING SECURITY IN CLOUD STORAGE ENVIRONMENTS

Although widely adopted, one of the biggest concerns with cloud computing is how to preserve the security and privacy of client data being processed and/or stored in a cloud computing environment. When it comes to cloud data protection, the methods employed can be very similar to protecting data within a traditional data center. Authentication and identity, access control, encryption, secure deletion, integrity checking, and data masking are all data protection methods that have applicability in cloud computing. Current research in cloud data protection primarily falls into three main categories: 1) Authentication & Access Control, 2) Encryption, and 3) Intrusion Detection. This thesis examines the various mechanisms that currently exist to protect data being stored in a public cloud computing environment. It also looks at the methods employed to detect intrusions targeting cloud data when and if data protection mechanisms fail. In response to these findings, we present three primary contributions that focus on enhancing the overall security of user data residing in a hosted environment such as the cloud. We first provide an analysis of Cloud Storage vendors that shows how data can be exposed when shared - even in the most `secure' environments. Secondly, we o er Pretty Good Privacy (PGP) as a method of securing data within this environment while enhancing PGP'sWeb of Trust validation mechanism using Bitcoin. Lastly, we provide a framework for protecting data exfiltration attempts in Software-as-a-Service (SaaS) Cloud Storage environments using Cyber Deception

Empirical and Analytical Perspectives on the Robustness of Blockchain-related Peer-to-Peer Networks

Die Erfindung von Bitcoin hat ein großes Interesse an dezentralen Systemen geweckt. Eine häufige Zuschreibung an dezentrale Systeme ist dabei, dass eine Dezentralisierung automatisch zu einer höheren Sicherheit und Widerstandsfähigkeit gegenüber Angriffen führt. Diese Dissertation widmet sich dieser Zuschreibung, indem untersucht wird, ob dezentralisierte Anwendungen tatsächlich so robust sind. Dafür werden exemplarisch drei Systeme untersucht, die häufig als Komponenten in komplexen Blockchain-Anwendungen benutzt werden: Ethereum als Infrastruktur, IPFS zur verteilten Datenspeicherung und schließlich "Stablecoins" als Tokens mit Wertstabilität. Die Sicherheit und Robustheit dieser einzelnen Komponenten bestimmt maßgeblich die Sicherheit des Gesamtsystems in dem sie verwendet werden; darüber hinaus erlaubt der Fokus auf Komponenten Schlussfolgerungen über individuelle Anwendungen hinaus. Für die entsprechende Analyse bedient sich diese Arbeit einer empirisch motivierten, meist Netzwerklayer-basierten Perspektive -- angereichert mit einer ökonomischen im Kontext von Wertstabilen Tokens. Dieses empirische Verständnis ermöglicht es Aussagen über die inhärenten Eigenschaften der studierten Systeme zu treffen. Ein zentrales Ergebnis dieser Arbeit ist die Entdeckung und Demonstration einer "Eclipse-Attack" auf das Ethereum Overlay. Mittels eines solchen Angriffs kann ein Angreifer die Verbreitung von Transaktionen und Blöcken behindern und Netzwerkteilnehmer aus dem Overlay ausschließen. Des weiteren wird das IPFS-Netzwerk umfassend analysiert und kartografiert mithilfe (1) systematischer Crawls der DHT sowie (2) des Mitschneidens von Anfragenachrichten für Daten. Erkenntlich wird hierbei, dass die hybride Overlay-Struktur von IPFS Segen und Fluch zugleich ist, da das Gesamtsystem zwar robust gegen Angriffe ist, gleichzeitig aber eine umfassende Überwachung der Netzwerkteilnehmer ermöglicht wird. Im Rahmen der wertstabilen Kryptowährungen wird ein Klassifikations-Framework vorgestellt und auf aktuelle Entwicklungen im Gebiet der "Stablecoins" angewandt. Mit diesem Framework wird somit (1) der aktuelle Zustand der Stablecoin-Landschaft sortiert und (2) ein Mittel zur Verfügung gestellt, um auch zukünftige Designs einzuordnen und zu verstehen.The inception of Bitcoin has sparked a large interest in decentralized systems. In particular, popular narratives imply that decentralization automatically leads to a high security and resilience against attacks, even against powerful adversaries. In this thesis, we investigate whether these ascriptions are appropriate and if decentralized applications are as robust as they are made out to be. To this end, we exemplarily analyze three widely-used systems that function as building blocks for blockchain applications: Ethereum as basic infrastructure, IPFS for distributed storage and lastly "stablecoins" as tokens with a stable value. As reoccurring building blocks for decentralized applications these examples significantly determine the security and resilience of the overall application. Furthermore, focusing on these building blocks allows us to look past individual applications and focus on inherent systemic properties. The analysis is driven by a strong empirical, mostly network-layer based perspective; enriched with an economic point of view in the context of monetary stabilization. The resulting practical understanding allows us to delve into the systems' inherent properties. The fundamental results of this thesis include the demonstration of a network-layer Eclipse attack on the Ethereum overlay which can be leveraged to impede the delivery of transaction and blocks with dire consequences for applications built on top of Ethereum. Furthermore, we extensively map the IPFS network through (1) systematic crawling of its DHT, as well as (2) monitoring content requests. We show that while IPFS' hybrid overlay structure renders it quite robust against attacks, this virtue of the overlay is simultaneously a curse, as it allows for extensive monitoring of participating peers and the data they request. Lastly, we exchange the network-layer perspective for a mostly economic one in the context of monetary stabilization. We present a classification framework to (1) map out the stablecoin landscape and (2) provide means to pigeon-hole future system designs. With our work we not only scrutinize ascriptions attributed to decentral technologies; we also reached out to IPFS and Ethereum developers to discuss results and remedy potential attack vectors

Proceedings of the 5th bwHPC Symposium

In modern science, the demand for more powerful and integrated research infrastructures is growing constantly to address computational challenges in data analysis, modeling and simulation. The bwHPC initiative, founded by the Ministry of Science, Research and the Arts and the universities in Baden-Württemberg, is a state-wide federated approach aimed at assisting scientists with mastering these challenges. At the 5th bwHPC Symposium in September 2018, scientific users, technical operators and government representatives came together for two days at the University of Freiburg. The symposium provided an opportunity to present scientific results that were obtained with the help of bwHPC resources. Additionally, the symposium served as a platform for discussing and exchanging ideas concerning the use of these large scientific infrastructures as well as its further development

Advances in Information Security and Privacy

With the recent pandemic emergency, many people are spending their days in smart working and have increased their use of digital resources for both work and entertainment. The result is that the amount of digital information handled online is dramatically increased, and we can observe a significant increase in the number of attacks, breaches, and hacks. This Special Issue aims to establish the state of the art in protecting information by mitigating information risks. This objective is reached by presenting both surveys on specific topics and original approaches and solutions to specific problems. In total, 16 papers have been published in this Special Issue