Visible to the public SYN Flood Attack Detection based on Bayes Estimator (SFADBE) For MANET

TitleSYN Flood Attack Detection based on Bayes Estimator (SFADBE) For MANET
Publication TypeConference Paper
Year of Publication2019
AuthorsHussain, K., Hussain, S. J., Jhanjhi, N., Humayun, M.
Conference Name2019 International Conference on Computer and Information Sciences (ICCIS)
Keywordsartificial intelligence, Bay Estimator, Clustering algorithms, composability, Firewalls (computing), Floods, MANET, MANET Attack Detection, Metrics, mobile ad hoc networks, Monitoring, probability, pubcrawl, Resiliency, Routing, Servers, SYN flood attack
Abstract

SYN flood attack is a very serious cause for disturbing the normal traffic in MANET. SYN flood attack takes advantage of the congestion caused by populating a specific route with unwanted traffic that results in the denial of services. In this paper, we proposed an Adaptive Detection Mechanism using Artificial Intelligence technique named as SYN Flood Attack Detection Based on Bayes Estimator (SFADBE) for Mobile ad hoc Network (MANET). In SFADBE, every node will gather the current information of the available channel and the secure and congested free (Best Path) channel for the traffic is selected. Due to constant congestion, the availability of the data path can be the cause of SYN Flood attack. By using this AI technique, we experienced the SYN Flood detection probability more than the others did. Simulation results show that our proposed SFADBE algorithm is low cost and robust as compared to the other existing approaches.

URLhttps://ieeexplore.ieee.org/document/8716416
DOI10.1109/ICCISci.2019.8716416
Citation Keyhussain_syn_2019