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Analyzing and Securing Social Networks




ISBN 9781482243277
Published April 5, 2016 by Auerbach Publications
574 Pages - 265 B/W Illustrations

 
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Book Description

Analyzing and Securing Social Networks focuses on the two major technologies that have been developed for online social networks (OSNs): (i) data mining technologies for analyzing these networks and extracting useful information such as location, demographics, and sentiments of the participants of the network, and (ii) security and privacy technologies that ensure the privacy of the participants of the network as well as provide controlled access to the information posted and exchanged by the participants.

The authors explore security and privacy issues for social media systems, analyze such systems, and discuss prototypes they have developed for social media systems whose data are represented using semantic web technologies. These experimental systems have been developed at The University of Texas at Dallas. The material in this book, together with the numerous references listed in each chapter, have been used for a graduate-level course at The University of Texas at Dallas on analyzing and securing social media. Several experimental systems developed by graduate students are also provided.

The book is divided into nine main sections: (1) supporting technologies, (2) basics of analyzing and securing social networks, (3) the authors’ design and implementation of various social network analytics tools, (4) privacy aspects of social networks, (5) access control and inference control for social networks, (6) experimental systems designed or developed by the authors on analyzing and securing social networks, (7) social media application systems developed by the authors, (8) secure social media systems developed by the authors, and (9) some of the authors’ exploratory work and further directions.

Table of Contents

Introduction
Overview
Analyzing Social Networks
Securing Social Networks
Outline of the Book
Next Steps

SUPPORTING TECHNOLOGIES

Social Networks: A Survey

Introduction
Survey of Social Networks
Details of Four Popular Social Networks
Summary and Conclusion

Data Security and Privacy
Overview
Security Policies
Policy Enforcement and Related Issues
Data Privacy
Summary and Directions
References

Data Mining Techniques
Introduction
Overview of Data Mining Tasks and Techniques
Artificial Neural Networks
Support Vector Machines
Markov Model
Association Rule Mining (ARM)
Multiclass Problem
Image Mining
Summary
References

Cloud Computing and Semantic Web Technologies
Introduction
Cloud Computing
Semantic Web
Semantic Web and Security
Cloud Computing Frameworks Based on Semantic Web Technologies
Summary and Directions
References

ASPECTS OF ANALYZING AND SECURING SOCIAL NETWORKS

Analyzing and Securing Social Networks
Introduction
Applications in Social Media Analytics
Data Mining Techniques for SNA
Security and Privacy
Summary and Directions
References

Semantic Web-Based Social Network Representation and Analysis
Introduction
Social Network Representation
Our Approach to Social Network Analysis
Summary and Directions
Reference

Confidentiality, Privacy, and Trust for Social Media Data
Introduction
Trust, Privacy, and Confidentiality
CPT Framework
Our Approach to Confidentiality Management
Privacy for Social Networks
Trust for Social Networks
Integrated System
CPT within the Context of Social Networks
Summary and Directions
References

TECHNIQUES AND TOOLS FOR SOCIAL NETWORK ANALYTICS

Developments and Challenges in Location Mining
Introduction
Key Aspects of Location Mining
Efforts in Location Mining
Challenges in Location Mining
Geospatial Proximity and Friendship
Our Contributions to Location Mining
Summary and Directions
References

TweetHood: A Social Media Analytics Tool
Introduction
TweetHood
Experiments and Results
Summary and Directions
References

Tweecalization: Location Mining Using Semisupervised Learning
Introduction
Tweecalization
Trustworthiness and Similarity Measure
Experiments and Results
Summary and Directions
References

Tweeque: Identifying Social Cliques for Location Mining
Introduction
Effect of Migration
Temporal Data Mining
Social Clique Identification
Experiments and Results
Location Prediction
Agglomerative Hierarchical Clustering
MapIt: Location Mining from Unstructured Text
Summary and Directions
References

Understanding News Queries with Geo-Content Using Twitter
Introduction
Application of Location Mining and Social Networks for Improving Web Search
Assigning Weights to Tweets
Semantic Similarity
Experiments and Results
Summary and Directions
References

SOCIAL NETWORK ANALYTICS AND PRIVACY CONSIDERATIONS

Our Approach to Studying Privacy in Social Networks
Introduction
Related Work
Definitional Preliminaries
Analysis
Data Gathering
Summary and Directions
References

Classification of Social Networks Incorporating Link Types
Introduction
Related Work
Learning Methods
Experiments
Results
Summary and Directions
References

Extending Classification of Social Networks through Indirect Friendships
Introduction
Related Work and Our Contributions
Definitions
Our Approach
Experiments and Results
Summary and Directions
References

Social Network Classification through Data Partitioning
Introduction
Related Work and Our Contributions
Metrics
Distributed Social Network Classification
Experiments
Summary and Directions
References

Sanitization of Social Network Data for Release to Semitrusted Third Parties
Introduction
Learning Methods on Social Networks
Hiding Private Information
Experiments
Effect of Sanitization on Other Attack Techniques
Effect of Sanitization on Utility
Summary and Directions
References

ACCESS CONTROL AND INFERENCE FOR SOCIAL NETWORKS

Access Control for Social Networks
Introduction
Related Work
Modeling Social Networks Using Semantic Web Technologies
Security Policies for OSNs
Security Policy Specification
Security Rule Enforcement
Summary and Directions
References

Implementation of an Access Control System for Social Networks
Introduction
Security in Online Social Networks
Framework Architecture
Experiments
Summary and Directions
References

Inference Control for Social Media
Overview
Design of an Inference Controller
Inference Control through Query Modification
Application to Social Media Data
Summary and Directions
References

Implementing an Inference Controller for Social Media Data
Overview
Inference and Provenance
Implementation of the Inference Controller
Generators
Use Case: Medical Example
Implementing Constraints
Summary and Directions
References

SOCIAL MEDIA INTEGRATION AND ANALYTICS SYSTEMS

Social Graph Extraction, Integration, and Analysis
Introduction
Entity Extraction and Integration
Ontology-Based Heuristic Reasoning
Graph Analysis
Managing and Querying Large RDF Graphs
Summary and Directions
References

Semantic Web-Based Social Network Integration
Overview
Information Integration in Social Networks
Jena–HBase: A Distributed, Scalable, and Efficient RDF Triple Store
StormRider: Harnessing Storm for Social Networks
Ontology-Driven Query Expansion Using MapReduce Framework
Summary and Directions
References

Experimental Cloud Query Processing System for Social Networks
Introduction
Our Approach
Related Work
Architecture
MapReduce Framework
Results

Summary and Directions
References

Social Networking in the Cloud
Introduction
Foundational Technologies for SNODSOC++
Design of SNODSOC
Toward SNODSOC++
Cloud-Based Social Network Analysis
StormRider: Harnessing Storm for Social Networks
Related Work
Summary and Directions
References

SOCIAL MEDIA APPLICATION SYSTEMS

Graph Mining for Insider Threat Detection
Introduction
Challenges, Related Work, and Our Approach
Graph Mining for Insider Threat Detection
Comprehensive Framework
Summary and Directions
References

Temporal Geosocial Mobile Semantic Web
Introduction
Challenges for a Successful SARO
Supporting Technologies for SARO
Our Approach to Building a SARO System
Conclusion
References

Social Media and Bioterrorism
Introduction
Simulating Bioterrorism through Epidemiology Abstraction
On the Mitigation of Bioterrorism through the Game Theory
Summary and Directions
References

Stream Data Analytics for Multipurpose Social Media Applications
Introduction
Our Premise
Modules of InXite
Other Applications
Related Work
Summary and Directions
References

SECURE SOCIAL MEDIA SYSTEMS

Secure Cloud Query Processing with Relational Data for Social Media
Overview
Related Work
System Architecture
Implementation Details and Results
Summary and Directions
References

Secure Cloud Query Processing for Semantic Web-Based Social Media
Overview
Background
Access Control
System Architecture
Experimental Setup and Results
Summary and Directions
References

Cloud-Centric Assured Information Sharing for Social Networks
Introduction
Design Philosophy
System Design
Related Work
Commercial Developments
Extensions for Social Media Applications
Summary and Directions
References

Social Network Integration and Analysis with Privacy Preservation
Introduction
Social Network Analysis
Limitations of Current Approaches for Privacy-Preserving Social Networks
Privacy Preservation of Social Network Data
Approach by Yang and Thuraisingham
Framework of Information Sharing and Privacy Preservation for Integrating Social Networks
Summary and Directions
References

Attacks on Social Media and Data Analytics Solutions
Introduction
Malware and Attacks
Attacks on Social Media
Data Analytics Solutions
Cloud-Based Malware Detection for Evolving Data Streams
Summary and Directions
References

SECURE SOCIAL MEDIA DIRECTIONS

Unified Framework for Analyzing and Securing Social Media
Overview
Design of Our Framework
Global Social Media Security and Privacy Controller
Summary and Directions
References

Integrity Management and Data Provenance for Social Media
Overview
Integrity, Data Quality, and Provenance
Integrity Management, Cloud Services, and Social Media
Summary and Directions
References

Multilevel Secure Online Social Networks
Introduction
Multilevel Secure Database Management Systems
Multilevel Online Social Networks
Summary and Directions
References

Developing an Educational Infrastructure for Analyzing and Securing Social Media
Introduction
Cybersecurity Education at UTD
Education Program in Analyzing and Securing Social Media
Summary and Directions
References

Summary and Directions
About This Chapter
Summary of This Book
Directions for Analyzing and Securing Social Media
Our Goals for Analyzing and Securing Social Media
Where Do We Go from Here?

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Author(s)

Biography

Dr. Bhavani Thuraisingham is the Louis A. Beecherl, Jr. distinguished professor of computer science and the executive director of the Cyber Security Research and Education Institute at the University of Texas at Dallas. She has 35 years of work experience in commercial industry (Honeywell), federally funded research and development center (MITRE), government (NSF) and academia. Dr. Thuraisingham has conducted research in cyber security for thirty years and specializes in applying data analytics for cyber security. Her work has resulted in over 100 keynote addresses, 120 journal papers, 300 conference papers, 15 books, and 8 patents.

Dr. Murat Kantarcioglu is a professor of computer science at The University of Texas at Dallas. He is recipient of an NSF CAREER award and a Purdue CERIAS Diamond Award for academic excellence. Currently, he is a visiting scholar at Harvard's Data Privacy Lab. His research has been supported by awards from NSF, AFOSR, ONR, NSA, and NIH. He has published over 150 peer-reviewed papers. Also, his work has been covered by media outlets such as Boston Globe and ABC News, among others, and has received three best-paper awards. He is a senior member of both ACM and IEEE.

Dr. Latifur Khan is a full professor (tenured) in the computer science department at the University of Texas at Dallas, where he has been teaching and conducting research since September 2000. He earned his PhD and MS degrees in computer science from the University of Southern California in August of 2000 and December of 1996 respectively. He has received prestigious awards, including the IEEE Technical Achievement Award for Intelligence and Security Informatics. He has given many keynote addresses, such as at the IEEE International Conference on Tools with Artificial Intelligence ICTAI 2010 in Arras, France.

Dr. Vaibhav Khadilkar completed his MS degree at Lamar University, and after working as a systems administrator for a few years, joined UTD for his PhD. He conducted research in secure semantic web, assured information sharing, and secure social networking, and completed his PhD in 2013. He received a scholarship from the CSI for his outstanding contributions. He has published numerous papers in top tier venues and is currently employed at NutraSpace in Dallas.

Satyen Abrol is a senior member of the technical staff at VMware, San Francisco Bay Area. He was a research assistant at the University of Texas at Dallas from August 2008 to May 2013, where he was associated with data mining and machine learning in online social networks. From May 2012 to August 2012, he worked at VMware in Palo Alto, CA, where he designed and implemented modules for storage, indexing, and querying of performance data. He also built pattern recognition modules for detecting performance regression, outlier detection, step detection, and correlation calculation.

Dr. Raymond Heatherly is lead data scientist at SHYFT Analytics, in the Greater Boston Area, where he is responsible for researching and implementing statistical tools for clinical and pharmaceutical analytical packages. He also is responsible for coordinating with the software development team to ensure that statistical components function within overall product offerings. Prior to that, he was a postdoctoral fellow at Vanderbilt University from August 2011 to July 2015, conducting research in electronic medical-record sharing and privacy, primarily for the eMERGE Consortium.