9 research outputs found

    Privacy-preserving efficient searchable encryption

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

    Cyber-Storms Come from Clouds: Security of Cloud Computing in the IoT Era

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    The Internet of Things (IoT) is rapidly changing our society to a world where every "thing" is connected to the Internet, making computing pervasive like never before. This tsunami of connectivity and data collection relies more and more on the Cloud, where data analytics and intelligence actually reside. Cloud computing has indeed revolutionized the way computational resources and services can be used and accessed, implementing the concept of utility computing whose advantages are undeniable for every business. However, despite the benefits in terms of flexibility, economic savings, and support of new services, its widespread adoption is hindered by the security issues arising with its usage. From a security perspective, the technological revolution introduced by IoT and Cloud computing can represent a disaster, as each object might become inherently remotely hackable and, as a consequence, controllable by malicious actors. While the literature mostly focuses on security of IoT and Cloud computing as separate entities, in this article we provide an up-to-date and well-structured survey of the security issues of Cloud computing in the IoT era. We give a clear picture of where security issues occur and what their potential impact is. As a result, we claim that it is not enough to secure IoT devices, as cyber-storms come from Clouds

    Cyber-storms come from clouds:Security of cloud computing in the IoT era

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    The Internet of Things (IoT) is rapidly changing our society to a world where every “thing” is connected to the Internet, making computing pervasive like never before. This tsunami of connectivity and data collection relies more and more on the Cloud, where data analytics and intelligence actually reside. Cloud computing has indeed revolutionized the way computational resources and services can be used and accessed, implementing the concept of utility computing whose advantages are undeniable for every business. However, despite the benefits in terms of flexibility, economic savings, and support of new services, its widespread adoption is hindered by the security issues arising with its usage. From a security perspective, the technological revolution introduced by IoT and Cloud computing can represent a disaster, as each object might become inherently remotely hackable and, as a consequence, controllable by malicious actors. While the literature mostly focuses on the security of IoT and Cloud computing as separate entities, in this article we provide an up-to-date and well-structured survey of the security issues of cloud computing in the IoT era. We give a clear picture of where security issues occur and what their potential impact is. As a result, we claim that it is not enough to secure IoT devices, as cyber-storms come from Clouds

    Secure policies for the distributed virtual machines in mobile cloud computing

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    Mobile Cloud Computing (MCC) is a combination of cloud computing and mobile computing through wireless technology in order to overcome mobile devices' resource limitations. In MCC, virtualization plays a key role whereas the cloud resources are shared among many users to help them achieve an efficient performance and exploiting the maximum capacity of the cloud’s servers. However, the lack of security aspect impedes the benefits of virtualization techniques, whereby malicious users can violate and damage sensitive data in distributed Virtual Machines (VMs). Thus, this study aims to provide protection of distributed VMs and mobile user’s sensitive data in terms of security and privacy. This study proposes an approach based on cloud proxy known as Proxy-3S that combines three security policies for VMs; user’s access control, secure allocation, and secure communication. The Proxy-3S keeps the distributed VMs safe in different servers on the cloud. It enhances the grants access authorization for permitted distributed intensive applications’ tasks. Furthermore, an algorithm that enables secure communication among distributed VMs and protection of sensitive data in VMs on the cloud is proposed. A prototype is implemented on a NetworkCloudSim simulator to manage VMs security and data confidentiality automatically. Several experiments were conducted using real-world healthcare distributed application in terms of efficiency, coverage and execution time. The experiments show that the proposed approach achieved lower attacker’s efficiency and coverage ratios; equal to 0.35 and 0.41 respectively in all experimented configurations compared with existing works. In addition, the execution time of the proposed approach is satisfactory ranging from 441ms to 467ms of small and large cloud configurations. This study serves to provide integrity and confidentiality in exchanging sensitive information among multistakeholder in distributed mobile applications

    Infrastructural Security for Virtualized Grid Computing

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    The goal of the grid computing paradigm is to make computer power as easy to access as an electrical power grid. Unlike the power grid, the computer grid uses remote resources located at a service provider. Malicious users can abuse the provided resources, which not only affects their own systems but also those of the provider and others. Resources are utilized in an environment where sensitive programs and data from competitors are processed on shared resources, creating again the potential for misuse. This is one of the main security issues, since in a business environment competitors distrust each other, and the fear of industrial espionage is always present. Currently, human trust is the strategy used to deal with these threats. The relationship between grid users and resource providers ranges from highly trusted to highly untrusted. This wide trust relationship occurs because grid computing itself changed from a research topic with few users to a widely deployed product that included early commercial adoption. The traditional open research communities have very low security requirements, while in contrast, business customers often operate on sensitive data that represents intellectual property; thus, their security demands are very high. In traditional grid computing, most users share the same resources concurrently. Consequently, information regarding other users and their jobs can usually be acquired quite easily. This includes, for example, that a user can see which processes are running on another user´s system. For business users, this is unacceptable since even the meta-data of their jobs is classified. As a consequence, most commercial customers are not convinced that their intellectual property in the form of software and data is protected in the grid. This thesis proposes a novel infrastructural security solution that advances the concept of virtualized grid computing. The work started back in 2007 and led to the development of the XGE, a virtual grid management software. The XGE itself uses operating system virtualization to provide a virtualized landscape. Users’ jobs are no longer executed in a shared manner; they are executed within special sandboxed environments. To satisfy the requirements of a traditional grid setup, the solution can be coupled with an installed scheduler and grid middleware on the grid head node. To protect the prominent grid head node, a novel dual-laned demilitarized zone is introduced to make attacks more difficult. In a traditional grid setup, the head node and the computing nodes are installed in the same network, so a successful attack could also endanger the user´s software and data. While the zone complicates attacks, it is, as all security solutions, not a perfect solution. Therefore, a network intrusion detection system is enhanced with grid specific signatures. A novel software called Fence is introduced that supports end-to-end encryption, which means that all data remains encrypted until it reaches its final destination. It transfers data securely between the user´s computer, the head node and the nodes within the shielded, internal network. A lightweight kernel rootkit detection system assures that only trusted kernel modules can be loaded. It is no longer possible to load untrusted modules such as kernel rootkits. Furthermore, a malware scanner for virtualized grids scans for signs of malware in all running virtual machines. Using virtual machine introspection, that scanner remains invisible for most types of malware and has full access to all system calls on the monitored system. To speed up detection, the load is distributed to multiple detection engines simultaneously. To enable multi-site service-oriented grid applications, the novel concept of public virtual nodes is presented. This is a virtualized grid node with a public IP address shielded by a set of dynamic firewalls. It is possible to create a set of connected, public nodes, either present on one or more remote grid sites. A special web service allows users to modify their own rule set in both directions and in a controlled manner. The main contribution of this thesis is the presentation of solutions that convey the security of grid computing infrastructures. This includes the XGE, a software that transforms a traditional grid into a virtualized grid. Design and implementation details including experimental evaluations are given for all approaches. Nearly all parts of the software are available as open source software. A summary of the contributions and an outlook to future work conclude this thesis

    Safeguarding health data with enhanced accountability and patient awareness

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    Several factors are driving the transition from paper-based health records to electronic health record systems. In the United States, the adoption rate of electronic health record systems significantly increased after "Meaningful Use" incentive program was started in 2009. While increased use of electronic health record systems could improve the efficiency and quality of healthcare services, it can also lead to a number of security and privacy issues, such as identity theft and healthcare fraud. Such incidents could have negative impact on trustworthiness of electronic health record technology itself and thereby could limit its benefits. In this dissertation, we tackle three challenges that we believe are important to improve the security and privacy in electronic health record systems. Our approach is based on an analysis of real-world incidents, namely theft and misuse of patient identity, unauthorized usage and update of electronic health records, and threats from insiders in healthcare organizations. Our contributions include design and development of a user-centric monitoring agent system that works on behalf of a patient (i.e., an end user) and securely monitors usage of the patient's identity credentials as well as access to her electronic health records. Such a monitoring agent can enhance patient's awareness and control and improve accountability for health records even in a distributed, multi-domain environment, which is typical in an e-healthcare setting. This will reduce the risk and loss caused by misuse of stolen data. In addition to the solution from a patient's perspective, we also propose a secure system architecture that can be used in healthcare organizations to enable robust auditing and management over client devices. This helps us further enhance patients' confidence in secure use of their health data.PhDCommittee Chair: Mustaque Ahamad; Committee Member: Douglas M. Blough; Committee Member: Ling Liu; Committee Member: Mark Braunstein; Committee Member: Wenke Le

    Digital Forensics Investigation Frameworks for Cloud Computing and Internet of Things

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    Rapid growth in Cloud computing and Internet of Things (IoT) introduces new vulnerabilities that can be exploited to mount cyber-attacks. Digital forensics investigation is commonly used to find the culprit and help expose the vulnerabilities. Traditional digital forensics tools and methods are unsuitable for use in these technologies. Therefore, new digital forensics investigation frameworks and methodologies are required. This research develops frameworks and methods for digital forensics investigations in cloud and IoT platforms

    Strategic and Blockchain-based Market Decisions for Cloud Computing

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    The cloud computing market has been in the center of attention for years where cloud providers strive to survive by either competition or cooperation. Some cloud providers choose to compete in the market that is dominated by few large providers and try to maximize their profit without sacrificing the service quality which leads to higher user ratings. Many research proposals tried to contribute to the cloud market competition. However, the majority of these proposals focus only on pricing mechanisms, neglecting thus the cloud service quality and users satisfaction. Meanwhile, cloud providers intend to form cloud federations to enhance their services quality and revenues. Nevertheless, traditional centralized cloud federations have strict challenges that might hinder the members' motivation to participate in, such as formation of stable coalitions with long-term commitments, participants' trustworthiness, shared revenue, and security of the managed data and services. For a stable and trustworthy federation, it is vital to avoid blind-trust on the claimed SLA guarantees from the members and monitor the quality of service considering the various characteristics of cloud services. This thesis aims to tackle the issues of cloud computing market from the two perspectives of competition and cooperation by: 1) modeling and solving the conflicting situation of revenue, user ratings and service quality, to improve the providers position in the market and increase the future users' demand; 2) proposing a user-centric game theoretical framework to allow the new and smaller cloud providers to have a share in the market and increase users satisfaction through providing high quality and added-value services; 3) motivating the cloud providers to adopt a coopetition behavior through a novel, fully distributed blockchain-based federation's structure that enables them to trade their computing resources through smart contracts; 4) introducing a new role of oracle as a verifier agent to monitor the quality of service and report to the smart contract agents deployed on the blockchain while optimizing the cost of using oracles; and 5) developing a Bayesian bandit learning oracles reliability mechanism to select the oracles smartly and optimize the cost and reliability of utilized oracles. All of the contributions are validated by simulations and implementations using real-world data

    Blockchain-Based Digitalization of Logistics Processes—Innovation, Applications, Best Practices

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    Blockchain technology is becoming one of the most powerful future technologies in supporting logistics processes and applications. It has the potential to destroy and reorganize traditional logistics structures. Both researchers and practitioners all over the world continuously report on novel blockchain-based projects, possibilities, and innovative solutions with better logistic service levels and lower costs. The idea of this Special Issue is to provide an overview of the status quo in research and possibilities to effectively implement blockchain-based solutions in business practice. This Special Issue reprint contained well-prepared research reports regarding recent advances in blockchain technology around logistics processes to provide insights into realized maturity
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