Visible to the public A Network IDS Model Based on Improved Artificial Immune Algorithm

TitleA Network IDS Model Based on Improved Artificial Immune Algorithm
Publication TypeConference Paper
Year of Publication2016
AuthorsTang, H.
Conference Name2016 International Conference on Intelligent Transportation, Big Data Smart City (ICITBS)
Date PublishedDec. 2016
PublisherIEEE
ISBN Number978-1-5090-6061-0
Keywordsartificial immune systems, autologous, Big Data, clone, composability, computer network security, continuous bit matching algorithm, controllable variation, detection rate, detector tolerance module, dynamic clonal selection algorithm, dynamic demotion, IDS, IDS system, immune mechanism, Immune system, improved artificial immune algorithm, intrusion tolerance, key modules, mathematical knowledge, network IDS model, network intrusion detection problem domain, novel artificial immune algorithm, novel IDS detection model, pubcrawl, random variation, Resiliency, smart cities, Transportation
Abstract

The network intrusion detection problem domain is described with mathematical knowledge in this paper, and a novel IDS detection model based on immune mechanism is designed. We study the key modules of IDS system, detector tolerance module and the algorithms of IDS detection intensively. Then, the continuous bit matching algorithm for computing affinity is improved by further analysis. At the same time, we adopt controllable variation and random variation, as well as dynamic demotion to improve the dynamic clonal selection algorithm. Finally the experimental simulations verify that the novel artificial immune algorithm has better detection rate and lower noise factor.

URLhttps://ieeexplore.ieee.org/document/8047102/
DOI10.1109/ICITBS.2016.82
Citation Keytang_network_2016