Lightweight De-authentication DoS Attack Detection Methodology for 802.11 Networks Using Sniffer

Abstract

Wireless networks are prone to many types of attacks. The open access of wireless technology puts the whole wireless environment into a threat. The new wireless technologies like wireless sensor networks (WSN) and the Internet of Things (IoT) face the challenges of security. The Internet of Things is yet to be standardized because of the unavailability of security solutions to certain wireless threats. Internet of Things uses different technologies for communication such as Bluetooth, Wi-Fi, Li-Fi, and 6LoPAN. Of all, Wi-Fi is mainly preferred. But Wi-Fi itself possesses certain security issues. One of the issues of Wi-Fi is the nature of Management Frames in its 802.11 standard. The Management Frames in 802.11 standard are unencrypted, hence easily interpretable. This very nature of Wi-Fi leads to many attacks like De-authentication attacks and Dis-association attacks. This paper provides an approach to detect De-authentication DoS attacks in Wi-Fi-based IoT networks, using the sniffing concept. For network sniffing, a Python-based tool known as Scapy is used. Attacks and Detection are done in a real-time environment. We used Kali Linux tools and Scapy for real-time attacks. The De-authentication DoS attacks are performed on a Wi-Fi-based IoT network, and the detections are triggered on a Scapy-based Sniffer program. Our algorithm also detects spoofed De-authentication DoS attacks.