DDoS Attacks: Evolution, Detection, Prevention, Reaction, and Tolerance, 1st Edition (Hardback) book cover

DDoS Attacks

Evolution, Detection, Prevention, Reaction, and Tolerance, 1st Edition

By Dhruba Kumar Bhattacharyya, Jugal Kumar Kalita

Chapman and Hall/CRC

288 pages | 88 B/W Illus.

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pub: 2016-05-13
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DDoS Attacks: Evolution, Detection, Prevention, Reaction, and Tolerance discusses the evolution of distributed denial-of-service (DDoS) attacks, how to detect a DDoS attack when one is mounted, how to prevent such attacks from taking place, and how to react when a DDoS attack is in progress, with the goal of tolerating the attack. It introduces types and characteristics of DDoS attacks, reasons why such attacks are often successful, what aspects of the network infrastructure are usual targets, and methods used to launch attacks.

The book elaborates upon the emerging botnet technology, current trends in the evolution and use of botnet technology, its role in facilitating the launching of DDoS attacks, and challenges in countering the role of botnets in the proliferation of DDoS attacks. It introduces statistical and machine learning methods applied in the detection and prevention of DDoS attacks in order to provide a clear understanding of the state of the art. It presents DDoS reaction and tolerance mechanisms with a view to studying their effectiveness in protecting network resources without compromising the quality of services.

To practically understand how attackers plan and mount DDoS attacks, the authors discuss the development of a testbed that can be used to perform experiments such as attack launching, monitoring of network traffic, and detection of attacks, as well as for testing strategies for prevention, reaction, and mitigation. Finally, the authors address current issues and challenges that need to be overcome to provide even better defense against DDoS attacks.

Table of Contents


Anomalies in Networks

Distributed Denial-of-Service (DDoS) Attacks

Causes of DDoS Attacks

Targets of DDoS Attacks

Launching of DDoS Attacks

Current Trends in Botnet Technology

Machine Learning in DDoS Attack Handling

DDoS Defense

Modules of a DDoS Defense System

Types of DDoS Defense Systems

DDoS Tools and Systems

DDoS Defense Evaluation

Prior Work

Contribution of This Book

Organization of This Book

DDoS Attacks, Machine Learning, and Measures

Issues in Internet Design

DDoS Attacks and Their Types

DDoS Attack Targets

Current Trends in DDoS Attacks

Strength of DDoS Attackers

Desired Characteristics of DDoS Defense System

Recent DDoS Attacks

Machine Learning Background

Some Empirical Studies

Chapter Summary

Botnets: Trends and Challenges

DDoS Attacks Using Stationary Botnets

Chapter Summary and Recommendations

DDoS Detection

Modules of a DDoS Defense Solution

Types of DDoS Defense Solutions

DDoS Detection Techniques

Chapter Summary

DDoS Prevention

DDoS Prevention Techniques

Chapter Summary

DDoS Reaction and Tolerance

Intrusion Response System (IRS)

DDoS Tolerance Approaches and Methods

Chapter Summary

Tools and Systems


Types of Network Security Tools


TUCANNON+: DDoS Attack-Generation and Monitoring Tool

TUCannon Architecture

TUMonitor: Traffic Monitoring Module in TUCANNON+

DDoS Defense Systems

Chapter Summary

Research Challenges and Recommendations


Research Challenges

About the Authors

Dhruba Kumar Bhattacharyya is a professor in computer science and engineering at Tezpur University, where he earned his PhD degree in cryptography and error-control coding in 1999. His research areas include network security, data mining, and bioinformatics. He has published more than 200 research articles in leading international journals and peer-reviewed conference proceedings. Dr. Bhattacharyya has authored three technical reference books and edited eight technical volumes. Under his guidance, thirteen students have received their PhD degrees in the areas of machine learning, bioinformatics, and network security. He is on the editorial board of several international journals.

Jugal Kumar Kalita teaches computer science at the University of Colorado, Colorado Springs. He earned his MS and PhD degrees in computer and information science from the University of Pennsylvania in Philadelphia in 1988 and 1990, respectively. Prior to that, he earned an MSc from the University of Saskatchewan in Saskatoon, Canada, in 1984, and a BTech from the Indian Institute of Technology, Kharagpur, in 1982. His expertise is in the areas of artificial intelligence and machine learning and the application of techniques in machine learning to network security, natural language processing, and bioinformatics.

Subject Categories

BISAC Subject Codes/Headings:
COMPUTERS / Programming / Games
COMPUTERS / Software Development & Engineering / General
COMPUTERS / Security / General
COMPUTERS / Security / Cryptography