Cover image for Mining Massive Data Sets for Security : Advances in Data Mining, Search, Social Networks and Text Mining, and Their Applications to Security.
Mining Massive Data Sets for Security : Advances in Data Mining, Search, Social Networks and Text Mining, and Their Applications to Security.
Title:
Mining Massive Data Sets for Security : Advances in Data Mining, Search, Social Networks and Text Mining, and Their Applications to Security.
Author:
Fogelman-Soulié, F.
ISBN:
9781607503620
Personal Author:
Physical Description:
1 online resource (388 pages)
Series:
NATO Science for Peace and Security Series: Information and Communication Security, v. 19 ; v.v. 19

NATO Science for Peace and Security Series: Information and Communication Security, v. 19
Contents:
Title page -- Mining Massive Data Sets for Security -- Contents -- Data Mining -- Learning Using Hidden Information: Master-Class Learning -- Learning Using Large Datasets -- Practical Feature Selection: From Correlation to Causality -- Industrial Mining of Massive Data Sets -- Large-Scale Semi-Supervised Learning -- User Modeling and Machine Learning: A Survey -- Smoothness and Sparsity Tuning for Semi-Supervised SVM -- Distributed Categorizer for Large Category Systems -- Data Stream Management and Mining -- Modelling and Analysing Systems of Agents by Agent-Aware Transition Systems -- Search -- The "Real World" Web Search Problem: Bridging the Gap Between Academic and Commercial Understanding of Issues and Methods -- Website Privacy Preservation for Query Log Publishing -- Fighting Web Spam -- Social Networks -- Emergent Patterns in Online Coactivity -- Diffusion and Cascading Behavior in Networks -- Link Analysis in Networks of Entities -- Evolving Networks -- Mining Networks Through Visual Analytics: Incremental Hypothesis Building and Validation -- A Review of Anomaly Detection on Graphs -- Text Mining -- Using Language-Independent Rules to Achieve High Multilinguality in Text Mining -- Mining the Web to Build a Complete, Large-Scale Language Model -- Integrating Text Mining and Link Analysis -- Using Linguistic Information as Features for Text Categorization -- Security Applications -- Statistical Techniques for Fraud Detection, Prevention and Assessment -- Fitting Mixtures of Regression Lines with the Forward Search -- Money Laundering Detection Using Data Mining -- Text Mining from the Web for Medical Intelligence -- Learning to Populate an Ontology of Politically Motivated Violent Events -- Filtering Multilingual Terrorist Content with Graph-Theoretic Classification Tools -- Open Source Intelligence.

Detecting Core Members in Terrorist Networks: A Case Study -- Geolocalisation in Cellular Telephone Networks -- Machine Learning for Intrusion Detection -- Subject Index -- Author Index.
Abstract:
The real power for security applications will come from the synergy of academic and commercial research focusing on the specific issue of security. This book is suitable for those interested in understanding the techniques for handling very large data sets and how to apply them in conjunction for solving security issues.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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