Performance and Security Challenges in Next-Gen Networks: SDN Using FFNN as a DDoS Mitigation Solution
Vaidehi Shah, Pranay Yadav · 2025
In recent years, there has been a proliferation in the development of next-generation networks, specifically SDN (software defined networks) and IoT (the Internet of Things). However, this proliferation has also led to detrimental growth in cyber terrorism, particularly in the form of various types of DDoS attacks. This research paper evaluates the efficacy of FFNN based back propagation algorithm and Gradient Descent (GD by comparing their performance. We performed a deep analysis of this algorithm and proposed the performance evolution of DDoS attack detection in data set, such as CICIDS2019. We analyze the training, testing, and validation processes of these algorithms using Matrix Laboratory (MATLAB) R2020B. We compare these methods based on various performance parameters like accuracy, precision, recall,$\mathbf{F}-1$score, and time complexity analysis. We use the big$\mathbf{O}$notation to analyze the time complexity of the optimization algorithm. The GD method provides a linear big$\mathbf{O}$notation,$\mathbf{n}$(o), which is superior to that of other algorithms. A detailed analysis of performance analysis is discussed in the result analysis of the proposed work. A detailed performance analysis is discussed in result section. The proposed assistance aims to identify an improved optimization algorithm for distinguish and mitigating DDoS attacks in the SDN network.