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Co-funded by the European Commission Horizon 2020 -
Grant #777154
Objectives of the Project
atmosphere-eubrazil.eu @AtmosphereEUBR
ATMOSPHERE is a 24-month project
aiming at the design and development of a
framework and a platform to implement
trustworthy cloud services on top of an
intercontinental hybrid and federated
resource pool.
Considering a broad spectrum of
trustworthiness properties and their measures.
Supporting the development, build,
deployment, measurement and evolution of
trustworthy cloud resources, data management
services and data processing services,
Demonstrated on a sensitive scenario of
distributed telemedicine.
ATMOSPHERE GOALS &
PARTNERS
Activities
Trustworthiness Assessment &
Monitoring Framework
Cloud services managing
federated and hybrid resources
Distributed Trustworthy
Data Management Services
Trustworthy Data
Processing Services
Pilot & Use
Cases
CommunityEngagement,Communication&Impact
ExploitationandSustainability
Trustworthiness is considered in its multiple
dimensions
Security, Privacy, Coherence, Isolation, Stability,
Fairness, Transparency and Dependability.
Trustworthiness metrics define the
properties that can be evaluated in each one
of these dimensions
A priori and a posteriori evaluation of vulnerability,
performance, integrity, robustness, scalability, resource
consumption, fairness, isolation, etc.
Enabling creating self-adaptive applications
Tracing the degree of compliance of regulations such
as the EU-GDPR
Privacy protection, traceability, confidentiality warning,
etc.
Trustworthiness life-cycle
A hybrid and federated platform to evaluate trustworthiness
Considerng both Virtual Machines and LxD containers as first class hypervisors.
Develop a federation model for LXD containers providing an AAI based on existing IdPs, a synchronized
repository of microimages, a CLI and a service specification for managing the whole platform.
Execution of applications through a function-oriented Dashboard.
Federated Network management beyond the boundaries of the sites,
Providing Network as a Service NFV and facing issues such as the scarce of public IPs.
ATMOSPHERE will offer a multi-site network federation
mechanism to enable the migration of configured
resources without needing to change IP
configuration and securely isolating
multi-tenant federated networks.
Considering containers as first-class
resources for network federation.
Hybrid federated container
platform
ATMOSPHERE not only measures trustworthiness but provides a set of
services to improve it.
A Distributed Data Management Platform will be developed such services as
storage, retrieval, update and access of data in a cloud, guaranteeing
features such as confidentiality and revocation and access authorization.
Policy engines for Secure Data Management.
Based on enclaves and focusing
on SQL and NoSQL Databases.
Supporting Spark.
Privacy preservation and
annotation.
Distributed Trustworthy Data
Management Services
Data
sources
PSFT in DTDMS
Sensitive Data
Original
Data
Derived
Data
Anonymized
Data
PSFTAssurance
Forgotten PSFT date
External
Systems
generates
maintains
removes
A layer of data analytic techniques implemented as a set of building blocks,
as well as a framework for the development of applications from the building
blocks on top of the Data Management Platform.
Trustworthy evaluation in design and
runtime
Evaluation of privacy risks, estimation of
execution deadlines for a given resource
allocation.
Detailed monitoring for the evaluation of
performance, fairness, robustness and
scalability with adaptive measures.
Workflow orchestration.
Trustworthy Data Processing
Services
The use case of the project focuses on telemedicine based on the processing
of echocardio images
Depending on the features of the images and the processing services, different risks can
be assumed.
Processing services that could lead to the identification of personal data must comply a
higher level of protection.
Application will serve to measure trustworthiness a priori and dynamically in a
broader sense, which will enable creating self-adaptive applications and
tracing the compliance of regulations such as the EU-GDPR.
Applications that cannot reach a defined level of
certification can be still trustful for specific operations
with lower risks, such as pure anonymised data, best
effort computations and long-term research.
Use Case
ATMOSPHERE will provide
A definition of Trustworthiness
Metrics.
A platform to measure such
metrics.
A hybrid and federated
container-based infrastructure.
Performance modelling services
for the applications.
Trustworthy Data Management
and Processing services.
A use case on telemedicine
Expected Outputs &
Exploitation plan
Improving
Trustworthiness of
Data Analytics
Contact
Ignacio Blanquer – iblanque@dsic.upv.es - (Universitat Politècnica de
València)
Francisco Brasileiro – fubica@computacao.ufcg.edu.br -
(Universidade Federal de Campina Grande)
atmosphere-eubrazil.eu

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ATMOSPHERE Objectives of the Project (ICT Week Brasilia - Brazil)

  • 1. Co-funded by the European Commission Horizon 2020 - Grant #777154 Objectives of the Project atmosphere-eubrazil.eu @AtmosphereEUBR
  • 2. ATMOSPHERE is a 24-month project aiming at the design and development of a framework and a platform to implement trustworthy cloud services on top of an intercontinental hybrid and federated resource pool. Considering a broad spectrum of trustworthiness properties and their measures. Supporting the development, build, deployment, measurement and evolution of trustworthy cloud resources, data management services and data processing services, Demonstrated on a sensitive scenario of distributed telemedicine. ATMOSPHERE GOALS & PARTNERS
  • 3. Activities Trustworthiness Assessment & Monitoring Framework Cloud services managing federated and hybrid resources Distributed Trustworthy Data Management Services Trustworthy Data Processing Services Pilot & Use Cases CommunityEngagement,Communication&Impact ExploitationandSustainability
  • 4. Trustworthiness is considered in its multiple dimensions Security, Privacy, Coherence, Isolation, Stability, Fairness, Transparency and Dependability. Trustworthiness metrics define the properties that can be evaluated in each one of these dimensions A priori and a posteriori evaluation of vulnerability, performance, integrity, robustness, scalability, resource consumption, fairness, isolation, etc. Enabling creating self-adaptive applications Tracing the degree of compliance of regulations such as the EU-GDPR Privacy protection, traceability, confidentiality warning, etc. Trustworthiness life-cycle
  • 5. A hybrid and federated platform to evaluate trustworthiness Considerng both Virtual Machines and LxD containers as first class hypervisors. Develop a federation model for LXD containers providing an AAI based on existing IdPs, a synchronized repository of microimages, a CLI and a service specification for managing the whole platform. Execution of applications through a function-oriented Dashboard. Federated Network management beyond the boundaries of the sites, Providing Network as a Service NFV and facing issues such as the scarce of public IPs. ATMOSPHERE will offer a multi-site network federation mechanism to enable the migration of configured resources without needing to change IP configuration and securely isolating multi-tenant federated networks. Considering containers as first-class resources for network federation. Hybrid federated container platform
  • 6. ATMOSPHERE not only measures trustworthiness but provides a set of services to improve it. A Distributed Data Management Platform will be developed such services as storage, retrieval, update and access of data in a cloud, guaranteeing features such as confidentiality and revocation and access authorization. Policy engines for Secure Data Management. Based on enclaves and focusing on SQL and NoSQL Databases. Supporting Spark. Privacy preservation and annotation. Distributed Trustworthy Data Management Services Data sources PSFT in DTDMS Sensitive Data Original Data Derived Data Anonymized Data PSFTAssurance Forgotten PSFT date External Systems generates maintains removes
  • 7. A layer of data analytic techniques implemented as a set of building blocks, as well as a framework for the development of applications from the building blocks on top of the Data Management Platform. Trustworthy evaluation in design and runtime Evaluation of privacy risks, estimation of execution deadlines for a given resource allocation. Detailed monitoring for the evaluation of performance, fairness, robustness and scalability with adaptive measures. Workflow orchestration. Trustworthy Data Processing Services
  • 8. The use case of the project focuses on telemedicine based on the processing of echocardio images Depending on the features of the images and the processing services, different risks can be assumed. Processing services that could lead to the identification of personal data must comply a higher level of protection. Application will serve to measure trustworthiness a priori and dynamically in a broader sense, which will enable creating self-adaptive applications and tracing the compliance of regulations such as the EU-GDPR. Applications that cannot reach a defined level of certification can be still trustful for specific operations with lower risks, such as pure anonymised data, best effort computations and long-term research. Use Case
  • 9. ATMOSPHERE will provide A definition of Trustworthiness Metrics. A platform to measure such metrics. A hybrid and federated container-based infrastructure. Performance modelling services for the applications. Trustworthy Data Management and Processing services. A use case on telemedicine Expected Outputs & Exploitation plan
  • 10. Improving Trustworthiness of Data Analytics Contact Ignacio Blanquer – iblanque@dsic.upv.es - (Universitat Politècnica de València) Francisco Brasileiro – fubica@computacao.ufcg.edu.br - (Universidade Federal de Campina Grande) atmosphere-eubrazil.eu