Multi-Fractal Traffic and Anomaly Detection in Computer Communications

Cover
Half Title
Title Page
Copyright Page
Dedication
Contents
Preface
Acknowledgments
Part I: Fundamentals
	Chapter 1: Fractal Time Series
		1.1. BACKGROUND
		1.2. FRACTAL TIME SERIES: A VIEW FROM FRACTIONAL SYSTEMS
		1.3. BASIC PROPERTIES OF FRACTAL TIME SERIES
		1.4. SOME MODELS OF FRACTAL TIME SERIES
		1.5. SUMMARY
		REFERENCES
	Chapter 2: On 1/f Noise
		2.1. INTRODUCTION
		2.2. PRELIMINARIES
		2.3. HYPERBOLICALLY DECAYED ACFS AND 1/f NOISE
		2.4. HEAVY-TAILED PDFS AND 1/f NOISE
		2.5. FRACTIONALLY GENERALIZED LANGEVIN EQUATION AND 1/f NOISE
		2.6. SUMMARY
		REFERENCES
	Chapter 3: Power Laws of Fractal Data in Cyber-Physical Networking Systems
		3.1. BACKGROUND
		3.2. BIREF OF POWER LAWS
		3.3. CASES OF POWER LAWS IN CPNS
		3.4. SOME EQUATIONS FOR POWER-LAW-TYPE DATA
		3.5. SUMMARY
		REFERENCES
	Chapter 4: Ergodicity of Long-Range-Dependent Traffic
		4.1. BACKGROUND
		4.2. PRELIMINARIES
		4.3. PROBLEM STATEMENTS
		4.4. RESULTS
		4.5. DISCUSSIONS AND SUMMARY
		REFERENCES
	Chapter 5: Predictability of Long-Range-Dependent Series
		5.1. INTRODUCTION
		5.2. PROBLEM STATEMENTS
		5.3. PREDICTABILITY OF LRD SERIES
		5.4. SUMMARY
		REFERENCES
Part II: Traffic Modeling and Traffic Data Processing
	Chapter 6: Long-Range Dependence and Self-Similarity of Daily Traffic with Different Protocols
		6.1. BACKGROUND
		6.2. DATA
		6.3. PRELIMINARIES: BRIEF OF GENERALIZED CAUCHY PROCESS
		6.4. MODELING RESULTS
		6.5. DISCUSSIONS
		6.6. SUMMARY
		REFERENCES
	Chapter 7: Stationarity Test of Traffic
		7.1. BACKGROUND
		7.2. CORRELATION METHOD FOR STATIONARITY TEST OF LRD TRAFFIC
		7.3. CASE STUDY
		7.4. DISCUSSIONS
		7.5. SUMMARY
		REFERENCES
	Chapter 8: Record Length Requirement of LRD Traffic
		8.1. BACKGROUND AND PROBLEM STATEMENTS
		8.2. THEORETICAL RESULTS
		8.3. PRACTICAL CONSIDERATIONS
		8.4. CASE STUDY
		8.5. DISCUSSIONS
		8.6. SUMMARY
		REFERENCES
Part III: Multi-fractal Models of Traffic
	Chapter 9: Multi-Fractional Generalized Cauchy Process and Its Application to Traffic
		9.1. INTRODUCTION
		9.2. THE MGC PROCESS
		9.3. PSD OF THE MGC PROCESS
		9.4. COMPUTATIONS OF D(T) AND H(T)
		9.5. CASE STUDY
		9.6. DISCUSSIONS
		9.7. SUMMARY
		REFERENCES
	Chapter 10: Modified Multi-fractional Gaussian Noise and Its Application to Traffic
		10.1. INTRODUCTION
		10.2. MODIFIED MULTI-FRACTIONAL GUASSIAN NOISE
		10.3. ON STATIONARITY OF MMFGN
		10.4. APPLICATION TO STATIONARITY TEST OF TRAFFIC
		10.5. SUMMARY
		REFERENCES
	Chapter 11: Traffic Simulation
		11.1. INTRODUCTION
		11.2. SIMULATIONS BASED ON GIVEN PDF/PSD/ACF
		11.3. GENERATION OF LRD TRAFFIC OF GC TYPE
		11.4. DISCUSSIONS
		11.5. SUMMARY
		REFERENCES
Part IV: Anomaly Detection of Traffic
	Chapter 12: Reliably Identifying Signs of DDOS Flood Attacks Based on Traffic Pattern Recognition
		12.1. BACKGROUND
		12.2. FEATURE EXTRACTION
		12.3. IDENTIFICATION DECISION
		12.4. CASE STUDY
		12.5. DISCUSSIONS AND SUMMARY
		REFERENCES
	Chapter 13: Change Trend of Hurst Parameter of Multi-Scale Traffic under DDOS Flood Attacks
		13.1. BACKGROUND
		13.2. TEST DATA
		13.3. BRIEF OF DATA TRAFFIC
		13.4. USING H TO DESCRIBE ABNORMALITY OF TRAFFIC UNDER DDOS FLOOD ATTACKS
		13.5. CHANGE TREND OF H
		13.6. SUMMARY
		REFERENCES
	Chapter 14: Postscript
		14.1. LOCAL VERSUS GLOBAL OF FRACTAL TRAFFIC
		14.2. STATIONARITY VERSUS MULTI-FRACTAL PROPERTY OF TRAFFIC
		14.3. OPEN PROBLEMS
		REFERENCES
APPENDIX
INDEX