Cloud technology options towards Free Flow of Data

This whitepaper collects the technology solutions that the projects in the Data Protection, Security and Privacy Cluster propose to address the challenges raised by the working areas of the Free Flow of Data initiative. The document describes the technologies, methodologies, models, and tools researched and developed by the clustered projects mapped to the ten areas of work of the Free Flow of Data initiative. The aim is to facilitate the identification of the state-of-the-art of technology options towards solving the data security and privacy challenges posed by the Free Flow of Data initiative in Europe. The document gives reference to the Cluster, the individual projects and the technologies produced by them

A Framework for Uncertain Cloud Data Security and Recovery Based on Hybrid Multi-User Medical Decision Learning Patterns

Machine learning has been supporting real-time cloud based medical computing systems. However, most of the computing servers are independent of data security and recovery scheme in multiple virtual machines due to high computing cost and time. Also, this cloud based medical applications require static security parameters for cloud data security. Cloud based medical applications require multiple servers to store medical records or machine learning patterns for decision making. Due to high Uncertain computational memory and time, these cloud systems require an efficient data security framework to provide strong data access control among the multiple users. In this work, a hybrid cloud data security framework is developed to improve the data security on the large machine learning patterns in real-time cloud computing environment. This work is implemented in two phases’ i.e. data replication phase and multi-user data access security phase. Initially, machine decision patterns are replicated among the multiple servers for Uncertain data recovering phase. In the multi-access cloud data security framework, a hybrid multi-access key based data encryption and decryption model is implemented on the large machine learning medical patterns for data recovery and security process. Experimental results proved that the present two-phase data recovering, and security framework has better computational efficiency than the conventional approaches on large medical decision patterns

Light-Weight Accountable Privacy Preserving Protocol in Cloud Computing Based on a Third-Party Auditor

Cloud computing is emerging as the next disruptive utility paradigm [1]. It provides extensive storage capabilities and an environment for application developers through virtual machines. It is also the home of software and databases that are accessible, on-demand. Cloud computing has drastically transformed the way organizations, and individual consumers access and interact with Information Technology. Despite significant advancements in this technology, concerns about security are holding back businesses from fully adopting this promising information technology trend. Third-party auditors (TPAs) are becoming more common in cloud computing implementations. Hence, involving auditors comes with its issues such as trust and processing overhead. To achieve productive auditing, we need to (1) accomplish efficient auditing without requesting the data location or introducing processing overhead to the cloud client; (2) avoid introducing new security vulnerabilities during the auditing process. There are various security models for safeguarding the CCs (Cloud Client) data in the cloud. The TPA systematically examines the evidence of compliance with established security criteria in the connection between the CC and the Cloud Service Provider (CSP). The CSP provides the clients with cloud storage, access to a database coupled with services. Many security models have been elaborated to make the TPA more reliable so that the clients can trust the third-party auditor with their data. Our study shows that involving a TPA might come with its shortcomings, such as trust concerns, extra overhead, security, and data manipulation breaches; as well as additional processing, which leads to the conclusion that a lightweight and secure protocol is paramount to the solution. As defined in [2] privacy-preserving is making sure that the three cloud stakeholders are not involved in any malicious activities coming from insiders at the CSP level, making sure to remediate to TPA vulnerabilities and that the CC is not deceitfully affecting other clients. In our survey phase, we have put into perspective the privacy-preserving solutions as they fit the lightweight requirements in terms of processing and communication costs, ending up by choosing the most prominent ones to compare with them our simulation results. In this dissertation, we introduce a novel method that can detect a dishonest TPA: The Light-weight Accountable Privacy-Preserving (LAPP) Protocol. The lightweight characteristic has been proven simulations as the minor impact of our protocol in terms of processing and communication costs. This protocol determines the malicious behavior of the TPA. To validate our proposed protocol’s effectiveness, we have conducted simulation experiments by using the GreenCloud simulator. Based on our simulation results, we confirm that our proposed model provides better outcomes as compared to the other known contending methods

Data Auditing and Security in Cloud Computing: Issues, Challenges and Future Directions

Cloud computing is one of the significant development that utilizes progressive computational power and upgrades data distribution and data storing facilities. With cloud information services, it is essential for information to be saved in the cloud and also distributed across numerous customers. Cloud information repository is involved with issues of information integrity, data security and information access by unapproved users. Hence, an autonomous reviewing and auditing facility is necessary to guarantee that the information is effectively accommodated and used in the cloud. In this paper, a comprehensive survey on the state-of-art techniques in data auditing and security are discussed. Challenging problems in information repository auditing and security are presented. Finally, directions for future research in data auditing and security have been discussed

Data auditing and security in cloud computing: issues, challenges and future directions

Cloud computing is one of the significant development that utilizes progressive computational power and upgrades data distribution and data storing facilities. With cloud information services, it is essential for information to be saved in the cloud and also distributed across numerous customers. Cloud information repository is involved with issues of information integrity, data security and information access by unapproved users. Hence, an autonomous reviewing and auditing facility is necessary to guarantee that the information is effectively accommodated and used in the cloud. In this paper, a comprehensive survey on the state-of-art techniques in data auditing and security are discussed. Challenging problems in information repository auditing and security are presented. Finally, directions for future research in data auditing and security have been discusse

AI-enabled privacy-preservation phrase with multi-keyword ranked searching for sustainable edge-cloud networks in the era of industrial IoT

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Health data in cloud environments

The process of provisioning healthcare involves massive healthcare data which exists in different forms on disparate data sources and in different formats. Consequently, health information systems encounter interoperability problems at many levels. Integrating these disparate systems requires the support at all levels of a very expensive infrastructures. Cloud computing dramatically reduces the expense and complexity of managing IT systems. Business customers do not need to invest in their own costly IT infrastructure, but can delegate and deploy their services effectively to Cloud vendors and service providers. It is inevitable that electronic health records (EHRs) and healthcare-related services will be deployed on cloud platforms to reduce the cost and complexity of handling and integrating medical records while improving efficiency and accuracy. The paper presents a review of EHR including definitions, EHR file formats, structures leading to the discussion of interoperability and security issues. The paper also presents challenges that have to be addressed for realizing Cloudbased healthcare systems: data protection and big health data management. Finally, the paper presents an active data model for housing and protecting EHRs in a Cloud environment

Service-Oriented Foreign Direct Investment: Legal and Policy Frameworks Protecting Digital Assets in Offshoring Information Technology (IT) - Enabled Services

This thesis examines challenges caused by global cyberspace, which continues to undermine the ability of regulatory instruments aimed at cyber security and deterring cybercrime so that digital assets including those associated with Foreign Direct Investment (FDI) are protected. Progress in information and communication technology (ICT) has brought about both challenges and opportunities for mankind. While ICT has enabled seamless communication on cyberspace, it has also made every phenomenon, positive or negative on cyberspace possible. The good side of ICT is the endless opportunities provided to harness multiple features and capabilities of associated technologies while its side effect being the enormous security challenge on cyberspace. Legal and policy frameworks are needed to help mitigate cyber security threats and safeguard digital assets against such threats while promoting the benefits of ICT. To this end nations attempt to regulate cyberspace within their territories, but may quickly find out that issues on cyberspace are both global and national at the same time, and as such not fully controllable at national levels only. If nations cannot fully regulate ICT and cyberspace, this will have negative implications for digital investor’s assets in their territories as well. That is investor’s information assets may not be adequately safeguarded by means of national legal instruments. This dissertation seeks to analyze the question as to whether it is entirely possible for nation-states to address the multifaceted challenges introduced by cyberspace with appropriate national legal and policy frameworks alone to protect digital investments. This dissertation argues that, on the one hand, nations are behind in providing proper regulatory coverage for cyberspace, while, on the other hand, existing regulations have largely been unsuccessful in containing cyber security threats primarily due to complications caused by the ubiquitous global presence of cyberspace per se. Consequently, investor’s digital assets are more susceptible to unauthorized access and use, or destruction, all of which cannot be fully accounted for with currently available legal or technical means. There is a strong indication that digital investor assets demand more protection efforts from both investors and forum nations alike compared to what is needed to protect and promote traditional FDI

A patient agent controlled customized blockchain based framework for internet of things

Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph