A hybrid multi-layer intrusion detection system in cloud

  • M. Manickam
  • S. P. Rajagopalan


Cloud computing being the representation of the technology makes use of the infrastructure for computing in an efficient manner. This type of a computing offers a large amount of potential in improving the productivity which reduces the costs and also ensures that this can handle the risks. The intrusion detection systems (IDS) are all widely used for malicious detection in the network of communication and also its host. The IDS system used currently has one set of rules with several patterns of attach which get stored inside the various databases and the whole traffic of network will be duly matched against this for the purpose of avoiding any other illegal or also unauthorized activities. Therefore, in this work, this structure has optimized multi-layer artificial neural network is based on the IDS in case of the cloud which has been presented. This hybrid glow swarm optimization (GSO)–tabu search (TS) is called the GSO–TS has been used for the optimization of the structure and also for the purpose of reduction of convergence time and for solving old problems, trapping of local optima and their premature convergence. The results have proved to have better performance.


Intrusion detection systems (IDS) Cloud computing Artificial neural network (ANN) Glow swarm optimization (GSO) and tabu search (TS) 


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.GKM College of Engineering and TechnologyChennaiIndia
  2. 2.Department of Computer Science and EngineeringGKM College of Engineering and TechnologyChennaiIndia

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