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.
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