Mining social networks and security informatics /

Mining social networks and security informatics /

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Bibliographic Details
Imprint:Dordrecht ; New York : Springer, c2013.
Description:1 online resource.
Language:English
Series:Lecture notes in social networks, 2190-5428
Lecture Notes in Social Networks.
Subject:
Data Mining.
Computer Security.
Computer Communication Networks.
Social Support.
Data mining.
Online social networks.
Computer networks -- Security measures.
Computer networks -- Security measures.
Data mining.
Online social networks.
Electronic books.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/9851344
Hidden Bibliographic Details
Other authors / contributors:Özyer, Tansel.
ISBN:9789400763593 (electronic bk.)
940076359X (electronic bk.)
9789400763586
Summary:Crime, terrorism and security are in the forefront of current societal concerns. This edited volume presents research based on social network techniques showing how data from crime and terror networks can be analyzed and how information can be extracted. The topics covered include crime data mining and visualization; organized crime detection; crime network visualization; computational criminology; aspects of terror network analyses and threat prediction including cyberterrorism and the related area of dark web; privacy issues in social networks; security informatics; graph algorithms for soci
Table of Contents:
  • Mining Social Networks and Security Informatics; Contents; A Model for Dynamic Integration of Data Sources; 1 Introduction; 1.1 What Is Data Integration?; 1.2 Is Data Integration a Hard Problem?; 2 Data Sources; 2.1 What Is Data Source?; 2.2 Data Source Types; 2.3 Data Quality and Completeness; 3 Dynamic Integration of Data Sources; 3.1 Data Structure Matching; 3.2 Unstructured Data Categorization; 3.3 Unstructured Data Feature Extraction; 3.4 Unstructured Data Matching; 3.5 Ontology; 3.6 Data Matching; 3.7 Metadata; 3.8 Data Fusion and Sharing; 4 A Sample Case; 5 Conclusions and Future Work
  • 1 Introduction2 SNA in the Context of Intelligence Analysis; 3 Uncertain Social Networks; 4 Extraction of Entities and Relations from Unstructured Text; 4.1 Extraction of Named Entities; 4.2 Extraction of Relations; 4.3 Generating Social Networks; 5 Suggested Approach for Creating Uncertain Social Networks from Unstructured Text; 5.1 Module for Extraction of Named Entities and Uncertain Relations; 5.2 The Fusion Module; 6 Experiment; 7 Discussion; 8 Conclusions; References; Privacy Breach Analysis in Social Networks; 1 Introduction; 1.1 Graph Notation; 2 Privacy Breaches in Social Networks
  • 2.1 Interactive Privacy Breaches2.2 Active Privacy Breaches; 2.3 Passive Privacy Breaches; 3 Social Network Graph Anonymization; 3.1 k-Anonymity; 3.2 Anonymization Techniques; 4 Measuring Graph Anonymity; 5 Conclusion; References; Partitioning Breaks Communities; 1 Introduction; 1.1 Cliques as Lower Bound Communities; 1.2 Partitioning Community Finding Algorithms; 1.3 Related Work; 2 Experiments; 2.1 Network Datasets Examined; 2.2 Partition by Modularity Maximisation; 2.3 Relation of Modularity Found to Proportion Split; 2.4 Partition by Normalised Edge Cut
  • 3 Fundamental Partitionability of Networks3.1 Partitions that Directly Minimise Clique Splits; 3.2 Detailed Analysis of Sample Networks; 3.3 D̀istinct' Cliques; 3.4 Random and Synthetic Models of Community; 4 Overlapping Community Finding Algorithms; 4.1 Algorithms Examined; 4.2 Analysis in Terms of Split Cliques; 4.3 Community Overlap Graphs; 4.4 Analysis of Community Overlap Graphs of Overlapping CFAs; 5 Conclusion; 6 Further Work; References; SAINT: Supervised Actor Identi{uFB01}cation for Network Tuning; 1 Introduction; 2 Background; 3 Problem Formulation; 4 Entity Resolution Pipeline

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