The DDoS attacks are the most destructive attacks that interrupt the safe operation of essential services delivered by the internet community’s different organizations. DDOS stands for Distributed Denial Of Service attacks. These attacks are becoming more complex and expected to expand in number day after day, rendering detecting and combating these threats challenging. Hence, an advanced intrusion detection system (IDS) is required to identify and recognize an- anomalous internet traffic behaviour. Within this article the process is supported on the latest dataset containing the current form of DDoS attacks including (HTTP flood, SIDDoS). This study combines well-known grouping methods such as Naïve Bayes, Multilayer Perceptron (MLP), and SVM, Decision trees.
This study introduces a novel 3-D fractional chaotic system with two quadratic terms and no equilibrium point. Thorough dynamical analysis of the introduced system is done studying Lyapunov dynamics with respect to fractional order and parameter value, Kaplan–Yorke dimension, bifurcation analysis, phase portraits, existence, and uniqueness of solution, dissipative and symmetric character, etc. The novel system is anti-synchronized using the novel technique ‘triple compound combination’ considering uncertainties and disturbances on a parallel system by two methods—nonlinear and adaptive sliding mode control. A proposed application of achieved synchronization in secure communication is presented. A comparative study of obtained results with published literature is also presented.
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