Journal
NEUROCOMPUTING
Volume 172, Issue -, Pages 385-393Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.neucom.2015.04.101
Keywords
DDoS attacks; DDoS detectors; Genuine and DDoS patterns
Categories
Ask authors/readers for more resources
The key objective of a Distributed Denial of Service (DDoS) attack is to compile multiple systems across the Internet with infected zombies/agents and form botnets of networks. Such zombies are designed to attack a particular target or network with different types of packets. The infected systems are remotely controlled either by an attacker or by self-installed Trojans (e.g. roj/Flood-IM) that are programmed to launch packet floods. Within this context, the purpose of this paper is to detect and mitigate known and unknown DDoS attacks in real time environments. We have chosen an Artificial Neural Network (ANN) algorithm to detect DDoS attacks based on specific characteristic features (patterns) that separate DDoS attack traffic from genuine traffic. (C) 2015 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available