A hybrid multiobjective RBF-PSO method for mitigating DoS attacks in Named Data Networking

Named Data Networking (NDN) is a promising network architecture being considered as a possible replacement for the current IP-based (host-centric) Internet infrastructure. NDN can overcome the fundamental limitations of the current Internet, in particular, Denial-of-Service (DoS) attacks. However, N...

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Vydáno v:Neurocomputing (Amsterdam) Ročník 151; s. 1262 - 1282
Hlavní autoři: Karami, Amin, Guerrero-Zapata, Manel
Médium: Journal Article Publikace
Jazyk:angličtina
Vydáno: Elsevier B.V 03.03.2015
Témata:
Adaptive algorithms
Algorismes genètics
Algorithms
Arquitectura de computadors
Computer networks
Computer simulation
Denial of service attacks
DoS attacks
Genetic algorithms
Hybrid systems
Informàtica
Intelligent hybrid algorithm
Internet
Mesures de seguretat
Named Data Networking
Networks
Neural networks
NSGA II
Ordinadors, Xarxes d
Particle Swarm Optimization
RBF neural networks
Security measures
Àrees temàtiques de la UPC
DoS attacks
RBF neural networks
Intelligent hybrid algorithm
Particle Swarm Optimization
Named Data Networking
NSGA II
ISSN:0925-2312, 1872-8286
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Shrnutí:Named Data Networking (NDN) is a promising network architecture being considered as a possible replacement for the current IP-based (host-centric) Internet infrastructure. NDN can overcome the fundamental limitations of the current Internet, in particular, Denial-of-Service (DoS) attacks. However, NDN can be subject to new type of DoS attacks namely Interest flooding attacks and content poisoning. These types of attacks exploit key architectural features of NDN. This paper presents a new intelligent hybrid algorithm for proactive detection of DoS attacks and adaptive mitigation reaction in NDN. In the detection phase, a combination of multiobjective evolutionary optimization algorithm with PSO in the context of the RBF neural network has been applied in order to improve the accuracy of DoS attack prediction. Performance of the proposed hybrid approach is also evaluated successfully by some benchmark problems. In the adaptive reaction phase, we introduced a framework for mitigating DoS attacks based on the misbehaving type of network nodes. The evaluation through simulations shows that the proposed intelligent hybrid algorithm (proactive detection and adaptive reaction) can quickly and effectively respond and mitigate DoS attacks in adverse conditions in terms of the applied performance criteria.
Bibliografie:ObjectType-Article-1
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ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2014.11.003