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Big data analytics with applications in insider threat detection

Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to...

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Bibliographic Details
Main Authors:	Thuraisingham, Bhavani M., Masud, Mehedy (Author), Parveen, Pallabi (Author), Khan, Latifur (Author)
Format:	eBook
Language:	English
Published:	Boca Raton, FL CRC Press 2018
Subjects:	Computer Networks / Access Control / Http://id.loc.gov/authorities/subjects/sh2007008424 Big Data / Fast Big Data / Http://id.loc.gov/authorities/subjects/sh2012003227 Logiciels Malveillants Malware (computer Software) / Http://id.loc.gov/authorities/subjects/sh2009005103 Criminalité Informatique / Enquêtes Données Volumineuses Computer Crimes / Investigation / Fast Computer Security / Data Processing Sécurité Informatique / Informatique Computer Crimes / Investigation / Http://id.loc.gov/authorities/subjects/sh85029493 Malware (computer Software) / Fast Computer Networks / Access Control / Fast
Online Access:	https://learning.oreilly.com/library/view/~/978135...
Collection:	O'Reilly - Collection details see MPG.ReNa

Table of Contents:

part PART III Stream Data Analytics for Insider Threat Detection
chapter Introduction to Part III
chapter 14 Insider Threat Detection as a Stream Mining Problem
chapter 15 Survey of Insider Threat and Stream Mining
chapter 16 Ensemble-Based Insider Threat Detection
chapter 17 Details of Learning Classes
chapter 18 Experiments and Results for Nonsequence Data
chapter 19 Insider Threat Detection for Sequence Data
chapter 20 Experiments and Results for Sequence Data
chapter 21 Scalability Using Big Data Technologies
chapter 22 Stream Mining and Big Data for Insider Threat Detection
chapter Conclusion to Part III
part PART IV Experimental BDMA and BDSP Systems
chapter Introduction to Part IV
chapter 23 Cloud Query Processing System for Big Data Management
chapter 24 Big Data Analytics for Multipurpose Social Media Applications
chapter 25 Big Data Management and Cloud for Assured Information Sharing
Includes bibliographical references and index
Chapter 1 Introduction
part PART I Supporting Technologies for BDMA and BDSP
chapter Introduction to Part I
chapter 2 Data Security and Privacy
chapter 3 Data Mining Techniques
chapter 4 Data Mining for Security Applications
chapter 5 Cloud Computing and Semantic Web Technologies
chapter 6 Data Mining and Insider Threat Detection
chapter 7 Big Data Management and Analytics Technologies
chapter Conclusion to Part I
part PART II Stream Data Analytics
chapter Introduction to Part II
chapter 8 Challenges for Stream Data Classification
chapter 9 Survey of Stream Data Classification
chapter 10 A Multi-Partition, Multi-Chunk Ensemble for Classifying Concept-Drifting Data Streams
chapter 11 Classification and Novel Class Detection in Concept-Drifting Data Streams
chapter 12 Data Stream Classification with Limited Labeled Training Data
chapter 13 Directions in Data Stream Classification
chapter Conclusion to Part II
chapter 26 Big Data Management for Secure Information Integration
chapter 27 Big Data Analytics for Malware Detection
chapter 28 A Semantic Web-Based Inference Controller for Provenance Big Data
part PART V Next Steps for BDMA and BDSP
chapter Introduction to Part V
chapter 29 Confidentiality, Privacy, and Trust for Big Data Systems
chapter 30 Unified Framework for Secure Big Data Management and Analytics
chapter 31 Big Data, Security, and the Internet of Things
chapter 32 Big Data Analytics for Malware Detection in Smartphones
chapter 33 Toward a Case Study in Healthcare for Big Data Analytics and Security
chapter 34 Toward an Experimental Infrastructure and Education Program for BDMA and BDSP
chapter 35 Directions for BDSP and BDMA
chapter Conclusion to Part V
chapter 36 Summary and Directions

Big data analytics with applications in insider threat detection

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