ForChaos: Real Time Application DDoS detection using Forecasting and Chaos Theory in Smart Home IoT Network

Recently, D/DoS attacks have been launched by zombie IoT devices in smart home networks. They pose a great threat to to network systems with Application Layer DDoS attacks being especially hard to detect due to their stealth and seemingly legitimacy. In this paper, we propose we propose ForChaos, a lightweight detection algorithm for IoT devices, that is based on forecasting and chaos theory to identify flooding and DDoS attacks. For every time-series behaviour collected, a forecasting-technique prediction is generated, based on a number of features, and the error between the two values is calcualted. In order to assess the error of the forecasting from the actual value, the lyapunov exponent is used to detect potential malicious behaviour. In NS-3 we evaluate our detection algorithm through a series of experiments in Flooding and Slow-Rate DDoS attacks. The results are presented and discussed in detail and compared with related studies, demonstrating its effectiveness and robustness

TCP-SYN Flooding Attack in Wireless Networks

This paper concerns the TCP (Transmission Control Protocol) vulnerabilities which gives space for a DoS (Denial of Service) attacks called TCP-SYN flooding which is well-known to the community for several years. The paper shows this attack in wireless as well as wired networks using perl synflood script, Wireshark network analyzer server, Windows 2008 server, and OPNET simulation environment. Using these tools an effects of this attack are shown. Finally, some effective practical mitigation techniques against SYN flooding attack for Linux and Windows systems are explained

Analysis of the SYN Flood DoS Attack

The paper analyzes systems vulnerability targeted by TCP (Transmission Control Protocol) segments when SYN flag is ON, which gives space for a DoS (Denial of Service) attack called SYN flooding attack or more often referred as a SYN flood attack. The effects of this type of attack are analyzed and presented in OPNET simulation environment. Furthermore, the paper presents two anomaly detection algorithms as an effective mechanism against this type of attack. Finally, practical approaches against SYN flood attack for Linux and Windows environment are shown