1 / 15

Protecting Data Privacy in the Era of Big Data

This presentation provides an overview of big data analytics, the importance of data privacy and security, and other concerns related to the use of big data. It emphasizes the principles of privacy by design, data security, radical transparency, and simplicity by design. The presentation also discusses the challenges of protecting personal identifiable information in the context of big data analytics and the need to carefully consider the implications of big data predictions and insights. Lastly, it highlights the importance of Open Source Intelligence (OSINT) and the risks of breached data on the internet.

wblevins
Download Presentation

Protecting Data Privacy in the Era of Big Data

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. How to protect data privacy in the era of big data?Dr. Amirudin bin Abdul WahabCHIEF EXECUTIVE OFFICER, cybersecurity malaysiaSERI KEMBANGAN, SELANGOR,MALAYSIA

  2. PRESENTATION AGENDA • An Overview to Big Data Analytics • Data Privacy & Security • Other Concerns • Conclusion

  3. Overview of Big Data "The goal is to turn data into information, and information into insight.” – Carly Fiorina, former chief executive of Hewlett-Packard Company.

  4. Big Data Analytic Techniques “The ability to take data - to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it — that’s going to be a hugely important skill in the next decades.” - Hal R. Varian – Economist, UC Berkeley School of Information

  5. Expected Values From Big Data Analytics

  6. PRESENTATION AGENDA • An Overview to Big Data Analytics • Data Privacy & Security • Other Concerns • Conclusion

  7. Data Privacy Principle PRIVACY BY DESIGN make privacy part of the DNA of the organisation SECURE THE DATA only keep the data really required to do business with, and keep it as secure as possible RADICAL TRANSPARENCY inform customers about the data collect about them and what exactly it is used for SIMPLICITY BY DESIGN keep it simple and understandable for consumers;

  8. Big Data and Infrastructure Security 1 APPLICATION ACCESS DATA INSIGHT DATA VISUALIZATION Ensuring privacy of data is a matter of defining and enforcing information security rules – not just rules about data collection, but about data use and retention. People should have the ability to manage the flow of their private information across massive, third-party analytical systems. DASHBOARD C Statistical Analysis Machine Learning Data Mining Language Processing 2 DATA ACCESS Large-Scale Data Storage & Data Management 3 DATA ENCRYPTION Web Data Extractor BIG DATA INFRA

  9. Big Data and Personal Identifiable Identity Privacy protections aren’t enough any more. Big data analytics can compromise identity by allowing data-driven organisation to moderate and even determine who we are before we make up our own minds. We need to begin to think about the kind of big data predictions and inferences that we will allow, and the ones that we should not.

  10. Big Data and Insights “Open Source Intelligence (OSINT) is form of intelligence collection management that involves finding, selecting and acquiring information from publicly available sources and analyzing it to produce actionable intelligence.”

  11. PRESENTATION AGENDA • An Overview to Big Data Analytics • Data Privacy & Security • Other Concerns • Conclusion

  12. Breached Data On the Internet

  13. PRESENTATION AGENDA • An Overview to Big Data Analytics • Data Privacy & Security • Other Concerns • Conclusion

  14. Conclusion

More Related