Publication Type : Conference Paper
Publisher : IEEE
Source : 2023 International Conference on Advances in Electronics, Communication, Computing and Intelligent Information Systems (ICAECIS)
Url : https://doi.org/10.1109/icaecis58353.2023.10170470
Campus : Chennai
School : School of Computing
Department : Computer Science and Engineering
Year : 2023
Abstract :
IEEE 802.11 generally known as the Wi-Fi network, is our backbone of the present communication system delivering the best effort service to the end users. Access control in wireless network is an intrinsic security problem which creates possibilities for malevolent manipulation by third parties. Hackers make the use of free software to easily execute wireless attacks to create denial of service (DOS) and man in the middle attack and thereby the existing defense becomes passive for new types of network attacks. The paper proposes a self-defending network that can quickly identify the attackers, prevent them from doing further damage and then get itself adapt to the threat behavior. To implement the mechanism a pre-connection attack is performed by targeting a network and analyzing the packets. The proposed work demonstrates how a hacker gains access to a Wi-Fi network by cracking different types of encryptions like Wired Equivalent Privacy (WEP), Wireless Protected Access (WPA)/WPA2 using a simple wireless network adapter. Our proposed adaptive threat defense model identifies the hacker and creates a diverse strategy for self-defense. The proposed model would be effective against dynamic network configuration like Wi-Fi and further prevents hijacking.
Cite this Research Publication : Datta Sai Manikanta Narayana, Sai Bharadwaj Nookala, Shraddha Chopra, Udhayakumar Shanmugam, An Adaptive Threat Defence Mechanism Through Self Defending Network to Prevent Hijacking in WiFi Network, 2023 International Conference on Advances in Electronics, Communication, Computing and Intelligent Information Systems (ICAECIS), IEEE, 2023, https://doi.org/10.1109/icaecis58353.2023.10170470