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Journal ArticleDOI

Thwarting DDoS attacks in grid using information divergence

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TLDR
A five-fold DDoS Defense Mechanism using an Information Divergence scheme that detects the attacker and discards the adversary's packets for a fixed amount of time in an organized manner is proposed.
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This article is published in Future Generation Computer Systems.The article was published on 2013-01-01. It has received 29 citations till now. The article focuses on the topics: Application layer DDoS attack & Trinoo.

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Citations
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Journal ArticleDOI

An Effective DOS Attack Detection Model in Cloud Using Artificial Bee Colony Optimization

TL;DR: A cloud-based DOS attack detection model (CDOSD) which is setup through key feature selection using a new binary version of Artificial bee colony optimization (BABCO) and decision tree (DT) classifier which detects DOS attack on cloud host with high accuracy and a very low false positive rate.
Journal ArticleDOI

A Virtual Firewall Mechanism Using Army Nodes to Protect Cloud Infrastructure from DDoS Attacks

TL;DR: This paper introduces a novel mechanism to protect and prevent the cloud from the spurious packets targeting the depletion of server resources called CDAP, installed at the cloud server farm/ Datacenter (DC).
Journal ArticleDOI

C2DF: High Rate DDOS filtering method in Cloud Computing

TL;DR: A data mining and neural network technique, trained to detect and filter DDOS attacks is offered, and it is visible that the algorithms achieve high detection accuracy (97%) with fewer false alarms.
Journal ArticleDOI

Coordinated Defense of Distributed Denial of Service Attacks against the Multi-Area Load Frequency Control Services

TL;DR: A co-simulation technology-based platform is utilized to coordinate various layers in the CPPS and provide a unified research tool for the attack-defense test, and OPNET is used to replicate DDoS attacks in the information layer.
Journal ArticleDOI

Systematic review of aspects of DDoS attacks detection

TL;DR: It has been concluded that an adequate analysis of the above aspects of detection of DDoS attacks can make a useful contribution to designing an appropriate strategy for neutralizing the attacks.
References
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Journal ArticleDOI

The Anatomy of the Grid: Enabling Scalable Virtual Organizations

TL;DR: The authors present an extensible and open Grid architecture, in which protocols, services, application programming interfaces, and software development kits are categorized according to their roles in enabling resource sharing.
Journal ArticleDOI

A taxonomy of DDoS attack and DDoS defense mechanisms

TL;DR: This paper presents two taxonomies for classifying attacks and defenses in distributed denial-of-service (DDoS) and provides researchers with a better understanding of the problem and the current solution space.
Book ChapterDOI

Anomalous Payload-Based Network Intrusion Detection

TL;DR: A payload-based anomaly detector, called PAYL, for intrusion detection that demonstrates the surprising effectiveness of the method on the 1999 DARPA IDS dataset and a live dataset the authors collected on the Columbia CS department network.
Proceedings Article

Intrusion Detection with Neural Networks

TL;DR: A backpropagation neural network called NNID (Neural Network Intrusion Detector) was trained in the identification task and tested experimentally on a system of 10 users, suggesting that learning user profiles is an effective way for detecting intrusions.
Journal ArticleDOI

Defense against spoofed IP traffic using hop-count filtering

TL;DR: A novel filtering technique, called Hop-Count Filtering (HCF), is presented-which builds an accurate IP-to-hop-count (IP2HC) mapping table-to detect and discard spoofed IP packets.
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