DEFeND architecture: a privacy by design platform for GDPR compliance.

The advent of the European General Data Protection Regulation (GDPR) imposes organizations to cope with radical changes concerning user data protection paradigms. GDPR, by promoting a Privacy by Design approach, obliges organizations to drastically change their methods regarding user data acquisition, management, processing, as well as data breaches monitoring, notification and preparation of prevention plans. This enforces data subjects (e.g., citizens, customers) rights by enabling them to have more information regarding usage of their data, and to take decisions (e.g., revoking usage permissions). Moreover, organizations are required to trace precisely their activities on user data, enabling authorities to monitor and sanction more easily. Indeed, since GDPR has been introduced, authorities have heavily sanctioned companies found as not GDPR compliant. GDPR is difficult to apply also for its length, complexity, covering many aspects, and not providing details concerning technical and organizational security measures to apply. This calls for tools and methods able to support organizations in achieving GDPR compliance. From the industry and the literature, there are many tools and prototypes fulfilling specific/isolated GDPR aspects, however there is not a comprehensive platform able to support organizations in being compliant regarding all GDPR requirements. In this paper, we propose the design of an architecture for such a platform, able to reuse and integrate peculiarities of those heterogeneous tools, and to support organizations in achieving GDPR compliance. We describe the architecture, designed within the DEFeND EU project, and discuss challenges and preliminary benefits in applying it to the healthcare and energy domains

Privacy, security, legal and technology acceptance requirements for a GDPR compliance platform.

GDPR entered into force in May 2018 for enhancing user data protection. Even though GDPR leads towards a radical change with many advantages for the data subjects it turned out to be a significant challenge. Organizations need to make long and complex changes for the personal data processing activities to become GDPR compliant. Citizens as data subjects are empowered with new rights, which however they need to become aware of and understand. Finally, the role of data protection authorities changes as well as their expectations from organizations. GDPR compliance being a challenging matter for the relevant stakeholders calls for a software platform that can support their needs. The aim of the Data govErnance For supportiNg gDpr (DEFeND) EU Project is to deliver such a platform. To succeed, the platform needs to satisfy legal and privacy requirements, be effective in supporting organizations in GDPR compliance, and provide functionalities that data controllers request for supporting GDPR compliance. Further, it needs to satisfy acceptance requirements, for assuring that its users will embrace and use the platform. In this paper, we describe the process, within the DEFeND EU Project, for eliciting and analyzing requirements for such a complex platform, by involving stakeholders from the banking, energy, health and public administration sectors, and using advanced frameworks for privacy requirements and acceptance requirements. The paper also contributes by providing elicited privacy and acceptance requirements concerning a holistic platform for supporting GDPR compliance

Privacy, security, legal and technology acceptance elicited and consolidated requirements for a GDPR compliance platform

Purpose– General data protection regulation (GDPR) entered into force in May 2018 for enhancing personal data protection. Even though GDPR leads toward many advantages for the data subjects it turned out to be a significant challenge. Organizations need to implement long and complex changes to become GDPR compliant. Data subjects are empowered with new rights, which, however, they need to become aware of. GDPR compliance is a challenging matter for the relevant stakeholders calls for a software platform that can support their needs. The aim of data governance for supporting GDPR (DEFeND) EU project is to deliver such a platform. The purpose of this paper is to describe the process, within the DEFeND EU project, for eliciting and analyzing requirements for such a complex platform. Design/methodology/approach– The platform needs to satisfy legal and privacy requirements and provide functionalities that data controllers request for supporting GDPR compliance. Further, it needs to satisfy acceptance requirements, for assuring that its users will embrace and use the platform. In this paper, the authors describe the methodology for eliciting and analyzing requirements for such a complex platform, by analyzing data attained by stakeholders from different sectors. Findings– The findings provide the process for the DEFeND platform requirements’elicitation and an indicative sample of those. The authors also describe the implementation of a secondary process for consolidating the elicited requirements into a consistent set of platform requirements. Practical implications– The proposed software engineering methodology and data collection tools(i.e. questionnaires) are expected to have a significant impact for software engineers in academia and industry. Social implications– It is reported repeatedly that data controllers face difficulties in complying with theGDPR. The study aims to offer mechanisms and tools that can assist organizations to comply with the GDPR,thus, offering a significant boost toward the European personal data protection objectives. Originality/value– This is the first paper, according to the best of the authors’ knowledge, to provide software requirements for a GDPR compliance platform, including multiple perspectives

Accountability Requirements in the Cloud Provider Chain

In order to be responsible stewards of other people’s data, cloud providers must be accountable for their data handling practices. The potential long provider chains in cloud computing introduce additional accountability challenges, with many stakeholders involved. Symmetry is very important in any requirements’ elicitation activity, since input from diverse stakeholders needs to be balanced. This article ventures to answer the question “How can one create an accountable cloud service?” by examining requirements which must be fulfilled to achieve an accountability-based approach, based on interaction with over 300 stakeholders.publishedVersio

Legal compliance by design (LCbD) and through design (LCtD) : preliminary survey

1st Workshop on Technologies for Regulatory Compliance co-located with the 30th International Conference on Legal Knowledge and Information Systems (JURIX 2017). The purpose of this paper is twofold: (i) carrying out a preliminary survey of the literature and research projects on Compliance by Design (CbD); and (ii) clarifying the double process of (a) extending business managing techniques to other regulatory fields, and (b) converging trends in legal theory, legal technology and Artificial Intelligence. The paper highlights the connections and differences we found across different domains and proposals. We distinguish three different policydriven types of CbD: (i) business, (ii) regulatory, (iii) and legal. The recent deployment of ethical views, and the implementation of general principles of privacy and data protection lead to the conclusion that, in order to appropriately define legal compliance, Compliance through Design (CtD) should be differentiated from CbD

FIN-DM: finantsteenuste andmekaeve protsessi mudel

Andmekaeve hõlmab reeglite kogumit, protsesse ja algoritme, mis võimaldavad ettevõtetel iga päev kogutud andmetest rakendatavaid teadmisi ammutades suurendada tulusid, vähendada kulusid, optimeerida tooteid ja kliendisuhteid ning saavutada teisi eesmärke. Andmekaeves ja -analüütikas on vaja hästi määratletud metoodikat ja protsesse. Saadaval on mitu andmekaeve ja -analüütika standardset protsessimudelit. Kõige märkimisväärsem ja laialdaselt kasutusele võetud standardmudel on CRISP-DM. Tegu on tegevusalast sõltumatu protsessimudeliga, mida kohandatakse sageli sektorite erinõuetega. CRISP-DMi tegevusalast lähtuvaid kohandusi on pakutud mitmes valdkonnas, kaasa arvatud meditsiini-, haridus-, tööstus-, tarkvaraarendus- ja logistikavaldkonnas. Seni pole aga mudelit kohandatud finantsteenuste sektoris, millel on omad valdkonnapõhised erinõuded. Doktoritöös käsitletakse seda lünka finantsteenuste sektoripõhise andmekaeveprotsessi (FIN-DM) kavandamise, arendamise ja hindamise kaudu. Samuti uuritakse, kuidas kasutatakse andmekaeve standardprotsesse eri tegevussektorites ja finantsteenustes. Uurimise käigus tuvastati mitu tavapärase raamistiku kohandamise stsenaariumit. Lisaks ilmnes, et need meetodid ei keskendu piisavalt sellele, kuidas muuta andmekaevemudelid tarkvaratoodeteks, mida saab integreerida organisatsioonide IT-arhitektuuri ja äriprotsessi. Peamised finantsteenuste valdkonnas tuvastatud kohandamisstsenaariumid olid seotud andmekaeve tehnoloogiakesksete (skaleeritavus), ärikesksete (tegutsemisvõime) ja inimkesksete (diskrimineeriva mõju leevendus) aspektidega. Seejärel korraldati tegelikus finantsteenuste organisatsioonis juhtumiuuring, mis paljastas 18 tajutavat puudujääki CRISP- DMi protsessis. Uuringu andmete ja tulemuste abil esitatakse doktoritöös finantsvaldkonnale kohandatud CRISP-DM nimega FIN-DM ehk finantssektori andmekaeve protsess (Financial Industry Process for Data Mining). FIN-DM laiendab CRISP-DMi nii, et see toetab privaatsust säilitavat andmekaevet, ohjab tehisintellekti eetilisi ohte, täidab riskijuhtimisnõudeid ja hõlmab kvaliteedi tagamist kui osa andmekaeve elutsüklisData mining is a set of rules, processes, and algorithms that allow companies to increase revenues, reduce costs, optimize products and customer relationships, and achieve other business goals, by extracting actionable insights from the data they collect on a day-to-day basis. Data mining and analytics projects require well-defined methodology and processes. Several standard process models for conducting data mining and analytics projects are available. Among them, the most notable and widely adopted standard model is CRISP-DM. It is industry-agnostic and often is adapted to meet sector-specific requirements. Industry- specific adaptations of CRISP-DM have been proposed across several domains, including healthcare, education, industrial and software engineering, logistics, etc. However, until now, there is no existing adaptation of CRISP-DM for the financial services industry, which has its own set of domain-specific requirements. This PhD Thesis addresses this gap by designing, developing, and evaluating a sector-specific data mining process for financial services (FIN-DM). The PhD thesis investigates how standard data mining processes are used across various industry sectors and in financial services. The examination identified number of adaptations scenarios of traditional frameworks. It also suggested that these approaches do not pay sufficient attention to turning data mining models into software products integrated into the organizations' IT architectures and business processes. In the financial services domain, the main discovered adaptation scenarios concerned technology-centric aspects (scalability), business-centric aspects (actionability), and human-centric aspects (mitigating discriminatory effects) of data mining. Next, an examination by means of a case study in the actual financial services organization revealed 18 perceived gaps in the CRISP-DM process. Using the data and results from these studies, the PhD thesis outlines an adaptation of CRISP-DM for the financial sector, named the Financial Industry Process for Data Mining (FIN-DM). FIN-DM extends CRISP-DM to support privacy-compliant data mining, to tackle AI ethics risks, to fulfill risk management requirements, and to embed quality assurance as part of the data mining life-cyclehttps://www.ester.ee/record=b547227

Information security frameworks assisting GDPR compliance in bank industry

In the last years, with the consequent increase use of Information Technology (IT) by the population, we watched an increase in the collection and processing of data by the organizations, for various purposes, such as for example the necessary provision of services or marketing campaigns. As a result of the increase of data, there have been several attempts to steal the data to sell or request redemptions from organizations. This situation has shown that organizations as regards data protection and security do not all have the same degree of maturity, and a determining aspect is also that the existing legislation is not the most adequate for the level of IT use in the days of today. To address these issues, the European Union (EU) decided to create the General Data Protection Regulation (GDPR), which entered into force on May 25, 2018, applicable to all organizations dealing with personal data of citizens residing in the European Union. In effect, the organizations combine all their efforts for the implementation of this new regulation, so that fines for non-compliance are not applied. Based on the previous description and with base on a set of best practices and existing frameworks of information security existent currently in the market, this thesis aims to explore how can current IS frameworks help Banks comply with GDPR by mapping the requirements of the regulation with the practices of the frameworks. In a second phase, interviews will be conducted with professionals in the field, in a specific sector where there is more sensitivity for these topics, the bank industry.Nos últimos anos com o consequente aumento do uso de Tecnologias de Informação (TI) pela população, assistimos a um aumento da recolha e tratamento dos dados por parte das organizações, destinando-se a diversos fins, como por exemplo, para a necessária prestação de serviços ou campanhas de marketing. Como consequência do aumento de dados, têm existido diversas tentativas de roubo dos mesmos para se vender ou pedir resgates às organizações. Esta situação tem revelado que as organizações no que respeita à segurança e proteção de dados nem todas têm o mesmo grau de maturidade, sendo que um aspeto também determinante é a legislação existente não ser a mais adequada para o nível de utilização das TI nos dias de hoje. Para colmatar estas falhas a União Europeia (UE) decidiu criar o Regulamento Geral de Proteção de Dados (RGPD), com entrada em vigor a 25 de maio de 2018, aplicável a todos as organizações que tratam dados pessoais de cidadãos residentes na União Europeia (EU). Com efeito as organizações conjugam todos os seus esforços para a implementação deste novo regulamento, de forma a que não sejam aplicadas multas por incumprimento ao mesmo. À imagem do que foi descrito anteriormente e com base num conjunto de boas práticas e frameworks existentes sobre segurança da informação atualmente no mercado, esta tese propõe explorar como os frameworks de segurança da informação podem ajudar os bancos a cumprir com o RGPD, através do mapeamento dos requisitos do regulamento com as práticas dos frameworks. Numa segunda fase realizar-se-á entrevistas com responsáveis na matéria, num setor específico onde existe mais sensibilidade no que toca a estes temas, o setor da banca

A Methodology for Assuring Privacy by Design in Information Systems

There is no doubt that privacy by design PbD has become a structuring paradigm for personal data protection. Certainly this paradigm has been in use since 1995; however the GDRP "The General Data Protection Regulation", by considering PbD in 2018 as a legal obligation, it testifies the PbD seven principles relevance. Companies are therefore called to put in place technical and organizational measures to integrate PbD into companies. Hence the need for a methodology to provide an exhaustive approach adapted to this implementation. Given the focus of the literature on the implementation of methodologies dedicated to the embodiment of PbD only in software systems, this article aims to propose an ISPM methodology "Information System Privacy Methodology" which focuses on the implementation of PbD in the enterprises architecture, specifically in information systems taking into account all the technical and organizational aspects which must be adopted for the said goal success