ECEN Security and Privacy for Big Data. Introduction Professor Yanmin Gong 08/22/2017

Transcription

1 ECEN Security and Privacy for Big Data Introduction Professor Yanmin Gong 08/22/2017

2 Administrivia Course Hour: T/R 3:30-4:45 CLB 101 Office Hour: T/R 2:30-3:30 pm Any question besides assignment office hour: Contact yanmin.gong@okstate.edu and include Course 5060 in the title of the

3 Assignments (20% of Grade) Weekly reading of assigned papers/articles Lateness All assignments are due at the beginning of class Late assignments are assessed a 15% per-day late penalty, with a maximum of four days Students with legitimate reasons should contact the professor before the deadline to apply for an extension

4 Course Project (30% of Grade) Every student complete one project independently End Result: Research Presentation Motivation for an Experiment Background Related Work Experimental Approach Experimental Evaluation I will provide sample topic areas

5 Exam (50% of Grade) Two exams Grading ASSIGNMENT 20% EXAM 1 25% EXAM 2 25% PROJECT PROPOSAL 10% PROJECT PRESENTATION 10% PROJECT REPORT 10% CLASS PARTICIPATION 10% A, B, C, D, below 60 F

6 Why you should take this course Data security and privacy is one of the most important grand challenges in managing today s data! Leakage of databases happen everyday Privacy may be leaked in ways that you don t realize

7 Why you should take this course Very active field and tons of interesting research. We will read papers in: Cryptography/Security Theory Machine Learning

8 Why you should take this course Introduction to research by working on a cool project Read scientific papers about exciting data applications Implement a security/privacy-preserving solution

9 Today Bird s-eye view introduction to security and privacy in big data Privacy attacks in the real-world Course overview

10 INTRODUCTION TO BIG DATA

11 Oklahoma State University Data Explosion: Internet Generate data through online activities Estimated User Data Generated per day: 8-10 GB public content, ~4TB private content

12 Data Explosion: Mobile Track all objects all the time with mobile devices ~5 billion mobile phones in use!

13 Data Explosion: IoT Measure all kinds of data in Internet of Things (IoT)

14 Data Explosion: Computing Collect all sorts of data for scientific computing

15 Big Data Characteristics: 4 V s Volume: scale of data 43 zettabytes (i.e., 1012 GB) of data will be created by 2020 Velocity: generating speed of data 1 TB of trade information during each trading session captured by the NYSE Variety: different forms of data Database, text, image, voice, video, raw sensor data, etc. Veracity: accuracy of data Poor data quality costs the U.S. economy $3.1 trillion per year

16 The Value in Big Data Big-Data impacts all aspects of our life

17 The value in Big Data (cont.) + 79% clicks +250% clicks +43% clicks

18 The value in Big Data (cont.) Significant value in big data across sectors (Mckinsey) 60% increase in operating margin for a retailer $300+ billion every year saved for US healthcare $149 billion saving in operation efficiency improvements for EU government administration 50% decrease in production development and assembly cost for manufacturing

19 DATA SECURITY AND PRIVACY

20 Traditional security mechanisms are inadequate for big data Large-scale cloud infrastructures Diversity of data sources and formats Streaming nature of data acquisition High-volume inter-cloud migration

21 Personal Big Data

22 Sometimes users can control and know who sees their information

23 But not always Users data might be used in wrong context Compromises and data breaches

24 But not always! User s data may be used in wrong context Inference of sensitive information

25 23 and me Genome sequencing But not always Given choices that you do not really understand: one egg or two eggs?

26 Big data brings big privacy concerns Key Challenge: Big data technologies collect so much data and analyze them so efficiently that it is possible to learn far more than before Massive data collection from sensors in everything to phones Advanced data analytical tools through data mining and other analytics

27 The Massachusetts Governor Privacy Breach [Sweeney IJUFKS 2002]

28 The Massachusetts Governor Privacy Breach [Sweeney IJUFKS 2002]

29 The Massachusetts Governor Privacy Breach [Sweeney IJUFKS 2002] Governor of MA uniquely identified using Zipcode, Birth Date, and Sex Name linked to diagnosis

30 AOL data publishing fiasco AOL anonymously released a list of 21 million web search queries

31 AOL data publishing fiasco AOL anonymously released a list of 21 million web search queries User IDs were replaced by random numbers

32 No > Thelma Arnold Queries for landscapers in Lilburn, Ga, several people with the last name Arnold and homes sold in shadow lake subdivision gwinnett county georgia.

33 Privacy Breach: Informal Definition A data sharing mechanism M that allows an unauthorized party to learn sensitive information about any individual, which could not have learnt without access to M User has control over his own data

34 Trade-offs between Privacy and Utility

35 Trade-offs between Privacy and Utility

36 Course Overview Course Objective Introduce you to the emerging trends and issues in security and privacy of big data systems and applications What you will learn How to identify security and privacy issues How to choose and apply appropriate approaches, tools and technology How to evaluate the security and privacy of a solution

37 Textbook No official textbook. Course Overview Recommended: Introduction to Modern Cryptography Recommended: Algorithmic Foundation of Differential Privacy Some of the course readings will come from seminal papers in the field.

38 Outline of the Course Module 1: Introduction Module 2: Privacy, Secrecy, and Cryptography Module 3: Privacy and Differential Privacy Module 4: Real World Applications

39 Course Schedule Theory and Algorithms (Lec. 1-15) Cryptography and data security Data privacy Applications (Lec ) Project Presentations (Lec )

40 Topics Covered in this Course See Syllabus.

41 A Note on Academic Integrity Academic integrity violations include Unauthorized collaboration Multiple submissions Plagiarism Consequences Violations become part of your permanent education record. Impact your GPA, scholarship/aim funding, enrollment holds, visa status for international students etc.