Big Data and Security
Moderní technologie a bezpečnost (BSSn4411)
Modern technologies and conflict (CDSn4003)
Jan Kleiner
2.11.2020
Fakulta sociálních studií - Masarykova univerzita - Vysoké školy

Presentation outline
Big Data | A word cloud featuring "Big Data". This is licens… | Flickr
•Big Data – theoretical and methodological prism.
•Legitimate ways of use.
•Problematic ways of use.

Manyika et al. (2011, 1):
•„Big Data refers to datasets, whose size is beyond the ability of typical database software tools
to capture, store, manage, and analyse.“

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Manyika et al. (2011, 1):
•Definition intentionally subjective and moving.
•It also depends on a software tools and usual data size in a given sector.
•„… as technology advances over time, size of datasets that qualify as big data will also
increase.“
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Are data more valuable than oil?
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Three approaches (PWC, 2019)
•Market:
•Active markets for data are rare, mostly illegal.
•Shutterstock, Flicker.
•Cost:
•Straight-forward, how much does the data currently cost (e.g. CPC).
•Fails to capture future revenues a holder can get from the data.
•Income:
•Measure of cash flows the data are expected to generate.

Are data more valuable than oil? It depends on the data.
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How to do research with Big Data?
•The distinction from „normal“ research is in the data collection.
•à How to collect „Big Data“?
•Google – Trends, Keyword Planner, 3rd parties – SEMRush, Keywordtool
•Social media – Twitter API, scrapers (Octoparse)
•Wikileaks
•Pastebin
•Cyber security – Shodan (academic licence)
•Open science repositories
•https://openscience.muni.cz/
•European legislation on open data and the re-use of public sector information
•https://ec.europa.eu/digital-single-market/en/european-legislation-reuse-public-sector-information
•

•How is Big Data (e.g. searches from Google) different from „conventional“
survey/interview/experiment etc. data?
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There are pros as well as cons (Davidowitz, 2015)
•Overcome respondent bias (social desirability).
•Efficiency. Wider and deeper insight.
•Representativeness?
•Population of searchers? How big is it?
•Misformulated seed words.
•We need to intepret results with explicit limits and deliberation in the relation with
quantitative and qualitative methodologies.
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Legitimate ways of use
•Army and law enforcement recruitment (see Jahedi, Wenger and Yeung, 2016).
•Studies on public perception (Kostakos, 2018).
•And others…
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Problematic ways of use
•Cambridge Analytica (see Isaak and Hanna, 2018) – Facebook data.
•Bulk surveillance (privacy vs. security debate) – e.g. PRISM programme exposed by Edward Snowden.
•Wikileaks.

References
•Manyika, J. et al. (2011). Executive summary: Big data: The next frontier for innovation,
competition, and productivity. McKinsey Global Institute. Available from:
https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/big-data-the-next-frontie
r-for-Innovation.
•PWC. (2019). Putting a value on data. Available from:
https://www.pwc.co.uk/data-analytics/documents/putting-value-on-data.pdf.
•Jahedi, S., Wenger, J. W. a Yeung, D. (2016). Searching for Information online: Using Big Data to
Identify the Concerns of Potential Army Recruits. RAND Corp. ISBN: 978-0-8330-9414-8. Available
from: https://www.rand.org/pubs/research_reports/RR1197.html.
•Isaak, J. and Hanna, M. J. (2018). User Data Privacy: Facebook, Cambridge Analytica, and Privacy
Protection. Computer 51(8), pp. 56-59. DOI: 10.1109/MC.2018.3191268. Available from:
https://ieeexplore.ieee.org/abstract/document/8436400
•Davidowitz, S. S. a Varian, H. (2015). A Hands-on Guide to Google Data. pp. 9-25. (dostupné přes
Google Scholar).
•Kostakos, P. (2018). Public Perceptions on Organised Crime, Mafia,and Terrorism: A Big Data
Analysis based onTwitter and Google Trends. International Journal of Cyber Criminology. 12(1). pp.
282-289. DOI: 10.5281/zenodo.1467919.
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Thank you for the attention. Questions and your presentations.