Towards an Ontology for Privacy Requirements via a Systematic Literature Review

Gharib, Mohamad; Giorgini, Paolo; Mylopoulos, John

doi:10.1007/978-3-319-69904-2_16

Cited by 38 publications

(48 citation statements)

References 35 publications

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“…Several papers address privacy requirements as a special case of security requirements, but this approach overlooks fundamental privacy goals [23]. Privacy is a concept that can be confused with security: "conceptually and methodologically privacy is often confounded with security" [22] and "the common misperception is that information security equates to privacy" [20].…”

Section: Background To Pbdmentioning

confidence: 99%

A Systematic Mapping Study on Privacy by Design in Software Engineering

Morales-Trujillo

García-Mireles

Matla-Cruz

et al. 2019

CLEIej

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Protecting personal data in current software systems is a complex issue that requires legal regulations and constraints to manage personal data as well as a methodological support to develop software systems that would safeguard data privacy of their respective users. Privacy by Design (PbD) approach has been proposed to address this issue and has been applied to systems development in a variety of application domains. The aim of this work is to determine the presence of PbD and its extent in software development efforts. A systematic mapping study was conducted in order to identify relevant literature that collects PbD principles and goals in software development as well as methods and/or practices that support privacy aware software development. 53 selected papers address PbD mostly from a theoretical perspective with proposals validation based primarily on experiences or examples. The findings suggest that there is a need to develop privacy-aware methods to be integrated at all stages of software development life cycle and validate them in industrial settings.

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Section: Background To Pbdmentioning

confidence: 99%

A Systematic Mapping Study on Privacy by Design in Software Engineering

Morales-Trujillo

García-Mireles

Matla-Cruz

et al. 2019

CLEIej

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“…Ontology-based approaches to privacy protection have been proposed in e.g. [1,[6][7][8], but the idea of creating privacy policies through a process of negotiation is mostly absent in these related works, as is that of data owners working in cooperation with data analysts. Our work can thus be viewed as filling a gap at the intersection of the domains of knowledge discovery, collaboration and privacy.…”

Section: Background and Motivationmentioning

confidence: 99%

A Domain Ontology and Software Platform for Collaborative Personal Data Analytics

Tuovinen

Smeaton

2019

Lecture Notes in Computer Science

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Collaborative knowledge discovery is a promising approach by which people with no data analytics expertise could benefit from an analysis of their own personal data by experts. To facilitate effective collaboration between data owners and knowledge discovery experts, we have developed a software platform that uses a domain ontology to represent knowledge relevant to the execution of the collaborative knowledge discovery process. The ontology provides classes representing the main elements of collaborations: collaborators and datasets. Furthermore, the ontology enables the specification of privacy constraints that determine the precise extent to which a given dataset of personal data is shared with a given collaborator. We have developed a client-server software platform that enables users to initiate collaborations, invite experts to join them, create datasets and share them with experts, and create visualisations of data. The collaborations are mediated through the creation, modification and deletion of individuals in the underlying ontology and the propagation of ontology changes to each client connected to the server.

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“…Piolle et al [17] proposed a user-centered privacy management that deals with the privacy policy. Gharib et al [24] presents an ontology for privacy requirements for systems that deal with personal information.…”

Section: Quality Management In Agent Systemsmentioning

confidence: 99%

Improving Agent Quality in Dynamic Smart Cities by Implementing an Agent Quality Management Framework

2019

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It is critical for quality requirements, such as trust, privacy, and confidentiality, to be fulfilled during the execution of smart city applications. In this study, smart city applications were modeled as agent systems composed of many agents, each with its own privacy and confidentiality properties. Violations of those properties may occur during execution due to the dynamic of agent behavior, decision-making capabilities, and social activities. In this research, a framework called Agent Quality Management was proposed and implemented to manage agent quality in agent systems. This paper demonstrates the effectiveness of the approach by applying it toward a smart city application called a crowdsourced navigation system to verify and assess agent data confidentiality. The AnyLogic Agent-Based Modeling tool was used to model and conduct the experiments. The experiments showed that the framework helped to improve the detection of agent quality violations in a dynamic smart city application. The results can be further analyzed using advanced data analytic approach to reduce future violations and improve data confidentiality in a smart city environment.

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Towards an Ontology for Privacy Requirements via a Systematic Literature Review

Cited by 38 publications

References 35 publications

A Systematic Mapping Study on Privacy by Design in Software Engineering

A Systematic Mapping Study on Privacy by Design in Software Engineering

A Domain Ontology and Software Platform for Collaborative Personal Data Analytics

Improving Agent Quality in Dynamic Smart Cities by Implementing an Agent Quality Management Framework

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