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Methods and tools for GDPR compliance through Privacy and Data Protection Engineering

Deliverables

Risk management tool for data protection and privacy v2

This is the source code of the tool, the evolved version of M33.

Knowledge base for data protection risk management

This is a data base containing the knowledge base produced in T3.4.

Knowledge base for assurance and certification

This is a data base containing the knowledge base produced in T6.4.

Knowledge base for privacy and data protection requirements

This is a data base containing the knowledge base produced in T4.4.

Model-driven design tool for data protection and privacy v2

This is the source code of the tool, the evolved version of M33.

Risk management tool for data protection and privacy v1

This is the source code of the tool. An evolved version will be delivered in M33.

Assurance tool for data protection and privacy v2

This is the source code of the tool, the evolved version of M33.

Model-driven design tool for privacy and data protection v1

This is the source code of the tool. An evolved version will be delivered in M33.

Requirements engineering tool for privacy and data protection v2

This is the source code of the tool, the evolved version of M33.

Assurance tool for data protection and privacy v1

This is the source code of the tool. An evolved version will be delivered in M33.

Requirements engineering tool for privacy and data protection v1

This is the source code of the tool. An evolved version will be delivered in M33.

Risk management methods for data protection and privacy v1

This document will describe the risk management method, including all methodological elements besides the tool. The document will be revised in M23 to adapt the method to the feedback received from stakeholders.

Risk management methods for data protection and privacy v2

This document will describe the risk management method, including all methodological elements besides the tool. The document will be revised in M23 to adapt the method to the feedback received from stakeholders.

Specification and design of model-driven design tool for privacy and data protection v3

This document will provide the detailed design of the tool for data protection and privacy model-driven design tool. A first version will be delivered in M14, which will be revised in M18 and M33 introducing the insights from the validation activities.

Overall system requirements v1

This document will specify the prioritized technical requirements to be satisfied by the PDP4E tools. A revised version will be delivered in M23 following the first validation.

Methods for data protection model-driven design v1

This document will describe the data-protection model-driven design method, including all methodological elements besides the tool. The document will be revised in M23 to adapt the method to the feedback received from stakeholders.

Specification and design of model-driven design tool for privacy and data protection v1

This document will provide the detailed design of the tool for data protection and privacy model-driven design tool. A first version will be delivered in M14, which will be revised in M18 and M33 introducing the insights from the validation activities.

Requirements engineering methods for privacy and data protection v2

This document will describe the requirements engineering method, including all methodological elements besides the tool. The document will be revised in M23 to adapt the method to the feedback received from stakeholders.

Integration report v2

This document will report on the interoperability among the different tools delivered, proposing changes for the second development iteration. It will be a first version on Month 18, after validation, and this will be the v2 by the Month 36, at the end of the project.

Specification and design of risk management tool for data protection and privacy v2

This document will report on the interoperability among the different tools delivered, proposing changes for the second development iteration. It will be a first version on Month 18, after validation, it will be a v2 by the Month 33, at the end of the project.

Specification and design of model-driven design tool for privacy and data protection v2

This document will provide the detailed design of the tool for data protection and privacy model-driven design tool. A first version will be delivered in M14, which will be revised in M18 and M33 introducing the insights from the validation activities.

Assurance methods for data protection and privacy v1

This document will describe the assurance method for data protection and privacy, including all methodological elements besides the tool. The document will be revised in M23 to adapt the method to the feedback received from stakeholders.

D2.1 Multi-stakeholder specification

This document will collect the needs expressed by the different PDP4E stakeholders, including the customers targeted by the demonstration pilots (T2.1) and the developers from the open-source community (T2.1), as well as the legal and ethical constraints identified in T2.2.

Specification and design of assurance tool for data protection and privacy v2

This document will provide the detailed design of the tool for data protection and privacy assurance tool. A first version will be delivered in M14, which will be revised in M18 and M33 introducing the insights from the validation activities.

Assurance methods for data protection and privacy v2

This document will describe the assurance method for data protection and privacy, including all methodological elements besides the tool. The document will be revised in M23 to adapt the method to the feedback received from stakeholders.

Methods for data protection model-driven design v2

This document will describe the data-protection model-driven design method, including all methodological elements besides the tool. The document will be revised in M23 to adapt the method to the feedback received from stakeholders.

Overall architecture and methodological framework v2

This deliverable will detail the architecture of the software tools, their interfaces and data models, as well as the underlying methodological framework. A revision will be delivered in M23 to introduce the changes derived from the validation.

Requirements engineering methods for privacy and data protection v1

This document will describe the requirements engineering method, including all methodological elements besides the tool. The document will be revised in M23 to adapt the method to the feedback received from stakeholders.

Overall system requirements v2

This document will specify the prioritized technical requirements to be satisfied by the PDP4E tools. A revised version will be delivered in M23 following the first validation.

Specification and design of risk management tool for data protection and privacy v1

This document will provide the detailed design of the tool for data protection and privacy risk management. A first version will be delivered in M14, which will be revised in M18 and M33 introducing the insights from the validation activities.

Specification and design of assurance tool for data protection and privacy v1

This document will provide the detailed design of the tool for data protection and privacy assurance tool. A first version will be delivered in M14, which will be revised in M18 and M33 introducing the insights from the validation activities.

Specification and design of assurance tool for data protection and privacy v3

This document will provide the detailed design of the tool for data protection and privacy assurance tool. A first version will be delivered in M14, which will be revised in M18 and M33 introducing the insights from the validation activities.

Specification and design of requirements engineering tool for privacy and data protection v2

This document will provide the detailed design of the tool for data protection and privacy requirements engineering. A first version will be delivered in M14, which will be revised in M18 and M33 introducing the insights from the validation activities.

Specification and design of requirements engineering tool for data protection and privacy v3

This document will provide the detailed design of the tool for data protection and privacy requirements engineering. A first version will be delivered in M14, which will be revised in M18 and M33 introducing the insights from the validation activities.

Specification and design of requirements engineering tool for privacy and data protection v1

This document will provide the detailed design of the tool for data protection and privacy requirements engineering. A first version will be delivered in M14, which will be revised in M18 and M33 introducing the insights from the validation activities.

Overall architecture and methodological framework v1

This deliverable will detail the architecture of the software tools, their interfaces and data models, as well as the underlying methodological framework. A revision will be delivered in M23 to introduce the changes derived from the validation.

Multistakeholder specification v2

This document will collect the needs expressed by the different PDP4E stakeholders, including the customers targeted by the demonstration pilots (T2.1) and the developers from the open-source community (T2.1), as well as the legal and ethical constraints identified in T2.2. This deliverable will encompass the modifications according to use case Automotive.

Integration report v1

This document will report on the interoperability among the different tools delivered, proposing changes for the second development iteration. It will be a first version on Month 18, after validation, it will be a v2 by the Month 36, at the end of the project.

Specification and design of risk management tool for data protection and privacy v3

This document will report on the interoperability among the different tools delivered, proposing changes for the second development iteration. It will be a first version on Month 18, after validation, it will be a v2 by the Month 33, at the end of the project.

D8.1 PDP4E website

This is the project’s public website.

Training material

This is the set of the training material created in PDP4E, including e.g. slide-sets, handouts, videos, or case studies.

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Publications

Security Risk Management for the Internet of Things: Technologies and Techniques for IoT Security, Privacy and Data Protection

Author(s): Victor Muntés-Mulero | Jacek Dominiak | Elena González | David Sanchez-Charles
Published in: 2020, ISBN 978-1-68083-683-7
Publisher: John Soldatos
DOI: 10.1561/9781680836837

Protecting Citizens’ Personal Data and Privacy: Joint Effort from GDPR EU Cluster Research Projects

Author(s): Renata M. de Carvalho, Camillo Del Prete, Yod Samuel Martin, Rosa M. Araujo Rivero, Melek Önen, Francesco Paolo Schiavo, Ángel Cuevas Rumín, Haralambos Mouratidis, Juan C. Yelmo, Maria N. Koukovini
Published in: SN Computer Science, 1/4, 2020, ISSN 2662-995X
Publisher: SN Computer Science (2020)
DOI: 10.1007/s42979-020-00218-8

Preventative Nudges: Introducing Risk Cues for Supporting Online Self-Disclosure Decisions

Author(s): Nicolás E. Díaz Ferreyra, Tobias Kroll, Esma Aïmeur, Stefan Stieglitz, Maritta Heisel
Published in: Information, 11/8, 2020, Page(s) 399, ISSN 2078-2489
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/info11080399

Agile risk management for multi-cloud software development

Author(s): Victor Muntés-Mulero, Oscar Ripolles, Smrati Gupta, Jacek Dominiak, Eric Willeke, Peter Matthews, Balázs Somosköi
Published in: IET Software, 13/3, 2019, Page(s) 172-181, ISSN 1751-8806
Publisher: Institution of Engineering and Technology
DOI: 10.1049/iet-sen.2018.5295

Reusable Elements for the Systematic Design of Privacy-Friendly Information Systems: A Mapping Study

Author(s): Julio C. Caiza, Yod-Samuel Martin, Danny S. Guaman, JOSE M. Del Alamo, Juan C. Yelmo
Published in: IEEE Access, 7, 2019, Page(s) 66512-66535, ISSN 2169-3536
Publisher: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/access.2019.2918003

Service level agreement-based GDPR compliance and security assurance in (multi)Cloud-based systems

Author(s): Erkuden Rios, Eider Iturbe, Xabier Larrucea, Massimiliano Rak, Wissam Mallouli, Jacek Dominiak, Victor Muntés, Peter Matthews, Luis Gonzalez
Published in: IET Software, 13/3, 2019, Page(s) 213-222, ISSN 1751-8806
Publisher: Institution of Engineering and Technology
DOI: 10.1049/iet-sen.2018.5293

Manipulation and Malicious Personalization: Exploring the Self-Disclosure Biases Exploited by Deceptive Attackers on Social Media

Author(s): Esma Aïmeur, Nicolás Díaz Ferreyra, Hicham Hage
Published in: Frontiers in Artificial Intelligence, 2, 2019, ISSN 2624-8212
Publisher: Front. Artif. Intell
DOI: 10.3389/frai.2019.00026

PDP-ReqLite: A Lightweight Approach for the Elicitation of Privacy and Data Protection Requirements

Author(s): Nicolás E. Díaz Ferreyra, Patrick Tessier, Gabriel Pedroza, Maritta Heisel
Published in: Data Privacy Management, Cryptocurrencies and Blockchain Technology - ESORICS 2020 International Workshops, DPM 2020 and CBT 2020, Guildford, UK, September 17–18, 2020, Revised Selected Papers, 12484, 2020, Page(s) 161-177, ISBN 978-3-030-66171-7
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-66172-4_10

Smart Grid Challenges Through the Lens of the European General Data Protection Regulation

Author(s): Jabier Martinez, Alejandra Ruiz, Javier Puelles, Ibon Arechalde, Yuliya Miadzvetskaya
Published in: Advances in Information Systems Development - Information Systems Beyond 2020, 39, 2020, Page(s) 113-130, ISBN 978-3-030-49643-2
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-49644-9_7

Persuasion Meets AI: Ethical Considerations for the Design of Social Engineering Countermeasures

Author(s): Nicolás Ferreyra, Esma Aïmeur, Hicham Hage, Maritta Heisel, Catherine van Hoogstraten
Published in: Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2020, Page(s) 204-211, ISBN 978-989-758-474-9
Publisher: SCITEPRESS - Science and Technology Publications
DOI: 10.5220/0010142402040211

Model-driven Evidence-based Privacy Risk Control in Trustworthy Smart IoT Systems

Author(s): Victor Muntés-Mulero, Jacek Dominiak, Elena Gonzalez, David Sanchez-Charles
Published in: Joint Proceedings of the Workshop on Model-Driven Engineering for the Internet of Things (MDE4IoT) & of the Workshop on Interplay of Model-Driven and Component-Based Software Engineering (ModComp), Vol-2442, 2019, Page(s) 15-22, ISSN 1613-0073
Publisher: CEUR-WS - http://ceur-ws.org/

Methods and Tools for GDPR Compliance Through Privacy and Data Protection Engineering

Author(s): Yod-Samuel Martin, Antonio Kung
Published in: 2018 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), 2018, 2018, Page(s) 108-111, ISBN 978-1-5386-5445-3
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/eurospw.2018.00021

The GDPR & Speech Data: Reflections of Legal and Technology Communities, First Steps Towards a Common Understanding

Author(s): Andreas Nautsch, Catherine Jasserand, Els Kindt, Massimiliano Todisco, Isabel Trancoso, Nicholas Evans
Published in: Interspeech 2019, 2019, 2019, Page(s) 3695-3699, ISSN 1990-9772
Publisher: International Speech Communication Association (ISCA)
DOI: 10.21437/interspeech.2019-2647

The Impact of Artificial Intelligence on Security: a Dual Perspective

Author(s): Avi Szychter, Hocine Ameur, Antonio Kung, Hervé Daussin
Published in: Computer and Electronics Security Applications Rendez-Vous, 2019
Publisher: Computer and Electronics Security Applications Rendez-Vous