Data Mining for Malicious Code Detection.
Appendix A: Data Management Systems: Developments and Trends Overview Developments in Database Systems Status, Vision, and Issues Data Management Systems Framework Building Information Systems from the Framework Relationship between the Texts Summary and Directions References Appendix B: Trustworthy Systems Overview Secure Systems.2.1 Overview.2.2.
Table of Contents, introduction, trends, data autodesk 3ds max 2010 64 bit activation code Mining and Security Technologies, data Mining for Email Worm Detection.
Data Length (CDL) Combining Features and Compute Combined Feature Vector Classification Summary and Directions References Evaluation and Results Introduction Dataset Experimental Setup.3.1 Parameter Settings.2.2 Baseline Techniques Results.4.1 Running Time Analysis Robustness and Limitations.6.1 Robustness against Obfuscations.6.2 Limitations Summary and Directions.Introduction to Part I: Data Mining and Security.Data Mining for Cyber Security.2.1 Overview.2.2 Cyber-terrorism, Insider Threats, and External Attacks.2.3 Malicious Intrusions.2.4 Credit Card Fraud and Identity Theft.2.5 Attacks on Critical Infrastructures.2.6 Data Mining for Cyber Security.Organization of This Book, next Steps, part I: data mining AND security.
Data Mining for Detecting Remote Exploits.
Downloads (12 Months n/a, downloads (6 Weeks n/a).
Artificial Neural Network, support Vector Machines, markov Model.
Publication: Book, data Mining Tools for Malware Detection 1st, auerbach Publications Boston, MA, USA 2011.
Summary, references, malware, introduction, viruses, worms, trojan Horses.Data Mining Techniques, introduction, overview of Data Mining Tasks and Techniques.Data Mining for Botnet Detection, stream Data Mining, emerging Data Mining Tools for Cyber Security Applications.Isbn: Book, bibliometrics, citation Count: 1, downloads (cumulative n/a.Association Rule Mining (ARM multi-class Problem.7.1 One-VS-One.7.2 One-VS-All, image Mining.8.1 Feature Selection.8.2 Automatic Image Annotation.8.3 Image Classification.Current Research and Development, summary References Design and Implementation of Data Mining Tools Introduction Intrusion Detection Web Page Surfing Prediction Image Classification Summary and Directions References Conclusion to Part I data mining FOR email worm detection Introduction to Part II Email Worm Detection Introduction Architecture.Time and Logic Bombs, botnet, spyware, summary, references, data Mining for Security Applications, overview.