Data Analytics Management, Governance, and Compliance

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    Towards Ethical Big Data Artifacts: A Conceptual Design
    ( 2018-01-03) Tona, Olgerta ; Someh, Ida Asadi ; Mohajeri, Kaveh ; Shanks, Graeme ; Davern, Michael ; Carlsson, Sven ; Kajtazi, Miranda
    Although Big Data generates many benefits for individuals, organizations and society, significant ethical issues are forcing governments to review their regulations so that citizens’ rights are protected. Given these ethical issues and a gradual increase of awareness about them, individuals are in need of new technical solutions to engage with organizations that extract value from Big Data. Currently, available solutions do not adequately accommodate the conflicting interests of individuals and organizations. In this paper, we propose a conceptual design for an artifact that will raise awareness amongst individuals about Big Data ethical issues and help to restore the power balance between individuals and organizations. Furthermore, we set forward a design agenda outlining future activities towards building and evaluating our proposed artifact. Our work is grounded in discourse ethics and stakeholder theory and intertwined with the European General Data Protection Regulation (GDPR)
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    Catching the Banksters: The Use of Big Data Analytics in Billion Dollar Regulatory Investigations
    ( 2018-01-03) Daniel, Gozman ; Wendy, Currie ; Jonathan, Seddon
    Following the financial crisis, emboldened regulators have increased the magnitude of fines levied for financial malfeasance. The automation of the data discovery process underpins the rise in internal investigations, which financial organizations are obliged to conduct on the behest of regulators, keen to reduce information asymmetries and bolster transparency. Yet little research exists into the technologies which underpin post-crisis regulatory agendas. Our study focuses on big data technologies (eDiscovery tools) which facilitate investigations, where rare yet serious breaches have occurred. We focus on the micro/data level (volume, veracity, variety and velocity) to understand how these tools are influencing regulatory outcomes. The findings illustrate the need for financial organizations to adopt robust information governance policies to ease future investigatory efforts. We identify various practices which may help compliance managers better respond to regulatory investigations faster and more easily to ease the burden of post-crisis regulation.
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    Privacy Preserving Network Security Data Analytics: Architectures and System Design
    ( 2018-01-03) DeYoung, Mark ; Kobezak, Philip ; Raymond, David ; Marchany, Randy ; Tront, Joseph
    An incessant rhythm of data breaches, data leaks, and privacy exposure highlights the need to improve control over potentially sensitive data. History has shown that neither public nor private sector organizations are immune. Lax data handling, incidental leakage, and adversarial breaches are all contributing factors. Prudent organizations should consider the sensitive nature of network security data. Logged events often contain data elements that are directly correlated with sensitive information about people and their activities -- often at the same level of detail as sensor data. Our intent is to produce a database which holds network security data representative of people's interaction with the network mid-points and end-points without the problems of identifiability. In this paper we discuss architectures and propose a system design that supports a risk based approach to privacy preserving data publication of network security data that enables network security data analytics research.
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