Privacy, consumer trust and big data: Privacy by design and the 3 C'S

Chibba, Michelle; Cavoukian, Ann

doi:10.1109/kaleidoscope.2015.7383624

Cited by 10 publications

(6 citation statements)

References 4 publications

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“…The so-called 'management by magazine' is a phenomenon that emerged from this problem whereby decisions are taken without a prior adequate analysis of direct and indirect risks. As a consequence, consumers have little faith in companies for safeguarding their data (Chibba and Cavoukian 2015). It is therefore imperative that when Big Data value is assessed, it should be done in parallel with concerns related to data security and privacy (Suresh 2014).…”

Section: Mrq6: Can We Identify Any Topics Within These Areas That Could Be Subjects For Further Research?mentioning

confidence: 99%

Enterprise architecture management as a solution for addressing general data protection regulation requirements in a big data context: a systematic mapping study

Georgiadis

Poels

2021

Inf Syst E-Bus Manage

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Context Big Data Analytics is a rapidly emerging IT practice whose applications offer benefits for a wide variety of business areas across an organisation. Given the wide scope of applications, the many types of processing involved, including those for purposes not yet foreseen, and the inherent privacy concerns resulting from collecting and storing personal data, the newly introduced General Data Protection Regulation (GDPR) poses specific challenges for safeguarding the security and protection of big data. These challenges are not limited to the IT function but extend across the entire organisation. This raises the question whether Enterprise Architecture Management (EAM), as an approach for ensuring the coherence, strategic alignment and focus on value creation of all organisational resources, offers guidance for addressing those challenges in a holistic manner, and thus provides a fruitful ground for developing an approach for complying to GDPR requirements in a Big Data context. Objective This study surveys the state-of-the-art in research on security, privacy, and protection of big data. The focus is on investigating which specific issues and challenges have been identified and whether these have been linked to GDPR requirements. Further, it examines whether previous research has investigated the potential of EAM in addressing those challenges and what the main findings of those studies are. Method We used Systematic Mapping Review (SMR), which is a methodology for literature review aimed at surveying the state-of-the-art in a research field as it is documented in the scientific literature. Further, we used Template Analysis, which is a thematic analysis technique, for coding the texts of the selected papers, classifying the research studies, and interpreting the different themes addressed in the literature.

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Section: Mrq6: Can We Identify Any Topics Within These Areas That Could Be Subjects For Further Research?mentioning

confidence: 99%

Enterprise architecture management as a solution for addressing general data protection regulation requirements in a big data context: a systematic mapping study

Georgiadis

Poels

2021

Inf Syst E-Bus Manage

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“…drilling rig [123]). Apart from safety benefits, these collected camera images also introduce significant challenges for privacy and security protection [124]- [127]. Some non-personal data can become personal data if these data are associated with a specific individual (e.g.…”

Section: Data Privacymentioning

confidence: 99%

“…Fitbit, Jawbone) for fitness applications, studies have reported that the company failed to disclose enough information to the end-users about the amount of collected data and the engagement of third-party companies in data processing [130], [136], [137]. This lack of information may give rise to conflicts between employees and employers, which affects consumer trust and company reputation [124]. For example, the employer can utilize surveillance data to evaluate employee performance even when off-duty.…”

Section: Data Privacy Preservation Implication In the Workplacementioning

confidence: 99%

“…In some cases, within a company structure, a new department is necessary to deal with data privacy. To prevent a breach of privacy, Chibba et al proposed embedding protective privacy measures into the design of BD systems, networked facilities and business practices [124]. Similar cases of privacy harm can occur in O&G applications.…”

Section: Data Privacy Preservation Implication In the Workplacementioning

confidence: 99%

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A Systematic Review of Big Data Analytics for Oil and Gas Industry 4.0

2020

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Big data (BD) analytics is one of the critical components in the digitalization of the oil and gas (O&G) industry. Its focus is managing and processing a high volume of data to improve operational efficiency, enhance decision making and mitigate risks in the workplace. Enhanced processing of seismic data also provides the industry with a better understanding of BD applications. However, the industry still exercises caution in adopting new technologies. The slow pace of technology adoption can be attributed to various causes, from the obstacles to the integration with existing systems, to cybersecurity for defending the BD system against cyber attacks. In some applications using wearable devices, physiological and location-tracking data also causes concerns related to workplace privacy implications. These shortcomings give rise to uncertainties about the practical benefits and effectiveness of applying BD in O&G activities. The objective of this paper is to perform a systematic review of BD analytics within the context of the O&G industry. This paper attempts to evaluate technical and nontechnical factors affecting the adoption of BD technologies. The study includes BD development platforms, network architecture, data privacy implications, cybersecurity, and the opportunities and challenges of adopting BD technologies in the O&G industry.INDEX TERMS Big data analytics, O&G digitalization, Industry 4.0, data privacy and security.

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“…Veri mahremiyeti literatürde, "bilgisel seçici kontrol" [4] ve "muhatapların bilgilerinin doğru kullanımı ve muhatabın hangi bilgisinin, kiminle ve ne derecede paylaşılmasına karar verme mekanizması" [5] [7];…”

Section: Veri Mahremiyeti (Data Prıvacy)unclassified