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

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

Towards Secure Collaboration in Federated Cloud Environments

Public administrations across Europe have been actively following and adopting cloud paradigms at various degrees. By establishing modern data centers and consolidating their infrastructures, many organizations already benefit from a range of cloud advantages. However, there is a growing need to further support the consolidation and sharing of resources across different public entities. The ever increasing volume of processed data and diversity of organizational interactions stress this need even further, calling for the integration on the levels of infrastructure, data and services. This is currently hindered by strict requirements in the field of data security and privacy. In this paper, we present ongoing work aimed at enabling secure private cloud federations for public administrations, performed in the scope of the SUNFISH H2020 project. We focus on architectural components and processes that establish cross-organizational enforcement of data security policies in mixed and heterogeneous environments. Our proposal introduces proactive restriction of data flows in federated environments by integrating real-time based security policy enforcement and its post-execution conformance verification. The goal of this framework is to enable secure service integration and data exchange in cross-entity contexts by inspecting data flows and assuring their conformance with security policies, both on organizational and federation level

Cloud-based identity and identity meta-data: secure and control own data in globalization era.

This paper proposes a new identity, and its underlying meta-data, model. The approach enables secure spanning of identity meta-data across many boundaries such as health-care, financial and educational institutions, including all others that store and process sensitive personal data. It introduces the new concepts of Compound Personal Record (CPR) and Compound Identifiable Data (CID) ontology, which aim to move toward own your own data model. The CID model ensures: authenticity of identity meta-data; high availability via unified Cloud-hosted XML data structure; and privacy through encryption, obfuscation and anonymity applied to Ontology-based XML distributed content. Additionally CID via XML ontologies is enabled for identity federation. The paper also proposes that access over sensitive data is strictly governed through an access control model with granular policy enforcement on the service side. This includes the involvement of relevant access control model entities which are enabled to authorize an ad-hoc break-glass data access which should give high accountability for data access attempts

Comparison and Alignment of Access Control Models

Turvasüsteemipoliitikat rakendatakse arvutis juurdepääsu kontrollimehhanismi kaudu. Juurdepääsu kontrollmehhanismi peamised kontrollid on konfidentsiaalsus, terviklikkus ja turvalisus. Juurdepääsu kontrollmehhanismi saab rakendada mistahes juurdepääsu kontrollmudelite kaudu. See on viis, kuidas volitamata kasutaja eest teavet või ressursse kaitsta, tagades juurdepääsu ainult volitatud kasutajale. On olemas erinevad juurdepääsu kontrollimudelid, kus kõik mudelid pole tänapäeva digitaalkeskkonnale piisavad. Seega tekib probleem ülesande lahendamisel, milline juurdepääsukontrolli mudel sobib teatud tüüpi mitme kasutaja infrastruktuuriga, millel on erinevad juurdepääsuvajadused. Juurdepääsu kontrollmudel erineb vastavalt keskkonnale. On olemas keskkond, mis annab juurdepääsu oma kasutajatele konkreetses võrgustikus ja keskkonnas, kus on kasutajaid, kes vahetavad võrke, et kasutada dünaamiliselt erinevaid ressursse. Seega on ressursside ja võrgu tõhusa kasutamise õige mudeli määramine keeruline, välja arvatud juhul, kui on võimalik olemasolevas mudelis kasutada vajalikke kontseptsioone, et muuta meie uus mudel paindlikumaks.Juurdepääsu kontrollimise standardid erinevate juurdepääsupõhiste õiguste haldamiseks on keerukad. Tekkivate tehnoloogiatega muutuvad süsteemi komponendid ajakohastatuks, seega on väljakutse leida sobiv ja paindlik juhtimismudel, mis vastab süsteemile. Isegi kui saadaval on erinevad juurdepääsukontrolli mudelid, on tõeline probleem leidmaks vajalikku juurdepääsu kontrollimehhanismi, mida saab kasutada meie uue juurdepääsukontrolli mudeli täiustamiseks, et turvaliselt juurde pääsedes ressursse tõhusalt kasutada.Lahenduseks on mõista juurdepääsu kontrollimudeli nõrku ja tugevaid omadusi, võrrelda erinevaid mudeleid ja viia nende parimad omadused kokku paindliku juurdepääsu kontrollimudeli koostamiseks. See saavutatakse süstemaatilise küsitluse abil, kus osalejad kinnitavad, et juurdepääsu kontrollimudelit saab mõista ja võrrelda kolme põhikomponendi: subjekti, poliitika ja objektiga, mille aluseks olevad põhimõtted, metamudelid ja kolme erineva juurdepääsu kontrollimudeli näitel.Erinevate juurdepääsukontrolli mudelite analüütiline võrdlus põhineb aruandel selle kohta, kuidas kasutajad sellega erinevatel juhtudel tegelevad. See uuring aitas saada erinevate inimeste arvamust reaalselt nii, et see empiiriline katsete läbiviimise viis suudaks leida tugevaid ja nõrgemaid tegureid. Lõpuks viiakse kõik tugevad tegureid kooskõlla uue paindliku juurdepääsukontrolli mudeli loomisega.Tulemus aitab võrrelda, uurida ja rakendada sobivat ja vajalikku juurdepääsu kontrollisüsteemile. See paneb meid mõtlema ka sellele, kuidas saab uut juurdepääsu kontrollisüsteemi analüüsida ja võrrelda olemasolevatega. Reaalajas vaatajaskonna abil saab selle väljund olla realistlik. Seda uurimustöö tulemust saab kasutada juurdepääsu kontrolli mudelite edasiseks täiustamiseks.Security system policies are implemented in the computer through access control mechanism. The primary controls that the access control mechanism possesses are confidentiality, integrity, and security. Access control mechanism can be applied through any of the access control models. It is is a way of protecting information or resources from the unauthorized user to provide access to authorized user. There exist different access control models in which all models are not adequate for today's digital environment. So, the problem arises in difficulty faced to choose which access control model suits well for a particular type of multi-user infrastructure with various access needs. Access control model differs according to the environment. There is an environment which grants access to its users within a particular network and for an environment which has users, who switch dynamically between different networks to access resources. Hence, determining the right model for the efficient use of resources and network is difficult, unless, there is a way to implement the needed concepts in our existing model as to make our new flexible model. Access control standards for managing different access privileges are complex to understand. With the emerging technologies, components of a system are getting updated, so, it will be a challenge to find out the suitable and flexible access control model that matches the system. Even though there are different access control model available, there is the real problem in finding out the needed access control mechanism which can be employed for the improvement of our new access control model for the efficient use of the resources to be accessed securely.The solution is to understand the weak and strong features of access control model by comparing different models and aligning their best features to compose into a flexible access control model. It is achieved with the help of systematic survey, where a group of audience validated that access control model can be understood and compared with three main components, subject, policy and object with underlying principles, meta-models and examples of three different access control model. Analytical comparison of different access control model is drawn from a report of how the audience deals with it at various cases that were analyzed. This survey helped to receive the opinion of different people realistically, such that this empirical way of conducting experiments concludes with the way for finding strong and weak factors. Finally, all the strong factors are aligned to form a new flexible access control model. The result helps to compare, study and implement a suitable and necessary access control system. It also makes us think in a way how a new access control system can be analyzed and compared with the existing ones. This research work result can be used for further research in future for the potential enhancement of newer access control models

Taking Computation to Data: Integrating Privacy-preserving AI techniques and Blockchain Allowing Secure Analysis of Sensitive Data on Premise

PhD thesis in Information technologyWith the advancement of artificial intelligence (AI), digital pathology has seen significant progress in recent years. However, the use of medical AI raises concerns about patient data privacy. The CLARIFY project is a research project funded under the European Union’s Marie Sklodowska-Curie Actions (MSCA) program. The primary objective of CLARIFY is to create a reliable, automated digital diagnostic platform that utilizes cloud-based data algorithms and artificial intelligence to enable interpretation and diagnosis of wholeslide-images (WSI) from any location, maximizing the advantages of AI-based digital pathology. My research as an early stage researcher for the CLARIFY project centers on securing information systems using machine learning and access control techniques. To achieve this goal, I extensively researched privacy protection technologies such as federated learning, differential privacy, dataset distillation, and blockchain. These technologies have different priorities in terms of privacy, computational efficiency, and usability. Therefore, we designed a computing system that supports different levels of privacy security, based on the concept: taking computation to data. Our approach is based on two design principles. First, when external users need to access internal data, a robust access control mechanism must be established to limit unauthorized access. Second, it implies that raw data should be processed to ensure privacy and security. Specifically, we use smart contractbased access control and decentralized identity technology at the system security boundary to ensure the flexibility and immutability of verification. If the user’s raw data still cannot be directly accessed, we propose to use dataset distillation technology to filter out privacy, or use locally trained model as data agent. Our research focuses on improving the usability of these methods, and this thesis serves as a demonstration of current privacy-preserving and secure computing technologies

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