Data Mining Tools for Malware Detection

Presenting theoretical concepts, practical techniques, and experimental results, this book provides a step-by-step illustration of how data mining tools are developed for malware detection. Foscusing on email worms, malicious code, remote exploits, and botnets, the authors describe the step-by-step...

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Bibliographic Details
Main Authors:	Masud, Mehedy, Khan, Latifur, Thuraisingham, Bhavani
Format:	eBook Book
Language:	English
Published:	Boca Raton Auerbach Publications 2012 CRC Press Auerbach Publishers, Incorporated
Edition:	1
Subjects:	Anomaly detection (Computer security) Computer networks Computer networks > Security measures Computer security Data mining Malware (Computer software) Security measures Remote Exploits Bayes Net Data Chunk Feature Extraction Data Mining Tools Malicious Executables Data Mining SVM Roc Curve Botnet Detection Concept Drifting Data Streams Exploit Code Real Time Data Mining Boosted Decision Tree Binary Executables Malicious Code Detection Class Detection Technique Association Rule Mining Host Machine Baseline Techniques Insider Threat Detection IGI Global Detecting Email Worms Malware Detection Feature Vectors
ISBN:	1439854548, 9781439854549, 9781439854556, 1439854556
Online Access:	Get full text
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Table of Contents:

Front Cover -- Contents -- Preface -- Acknowledgments -- The Authors -- Copyright Permissions -- Chapter 1: Introduction -- Part I: Data Mining and Security -- Chapter 2: Data Mining Techniques -- Chapter 3: Malware -- Chapter 4: Data Mining for Security Applications -- Chapter 5: Design and Implementation of Data Mining Tools -- Conclusion to Part I -- Chapter 6: Email Worm Detection -- Part II: Data Mining for Email Worm Detection -- Chapter 7: Design of the Data Mining Tool -- Chapter 8: Evaluation and Results -- Conclusion to Part II -- Chapter 9: Malicious Executables -- Part III: Data Mining for Detecting Malicious Executables -- Chapter 10: Design of the Data Mining Tool -- Chapter 11: Evaluation and Results -- Conclusion to Part III -- Chapter 12: Detecting Remote Exploits -- Part IV: Data Mining for Detecting Remote Exploits -- Chapter 13: Design of the Data Mining Tool -- Chapter 14: Evaluation and Results -- Conclusion to Part IV -- Part V: Data Mining for Detecting Botnets -- Chapter 15: Detecting Botnets -- Chapter 16: Design of the Data Mining Tool -- Chapter 17: Evaluation and Results -- Conclusion to Part V -- Part VI: Stream Mining for Security Applications -- Chapter 18: Stream Mining -- Chapter 19: Design of the Data Mining Tool -- Chapter 20: Evaluation and Results -- Conclusion for Part VI -- Part VII: Emerging Applications -- Chapter 21: Data Mining for Active Defense -- Chapter 22: Data Mining for Insider Threat Detection -- Chapter 23: Dependable Real-Time Data Mining -- Chapter 24: Firewall Policy Analysis -- Conclusion to Part VII -- Chapter 25: Summary and Directions -- Appendix A: Data Management Systems : Developments and Trends -- Appendix B: Trustworthy Systems -- Appendix C: Secure Data, Information, and Knowledge Management -- Appendix D: Semantic Web -- Back Cover