• Dr.R.BASHEER MOHAMED
• M.SHAHEDA BEGUM
• S.RUMANA FIDOSE
• A.HARIPRIYA
• J.K.SUPRIYA

Attacks on the internet have been a growing threat in recent years, with hackers attempting to hack or illegally tamper with data available across networks. On the other side, the number of research contributions to effectively counter these attacks and develop a strong defense mechanism has increased. In recent years, a slew of intelligent and soft computing-based algorithms and frameworks have been established. These evolution-based algorithms play a critical role in self-adapting the system under assault to the ever-increasing number of different sorts of attacks. The artificial neural network, also known as ANNs, is one of the soft computing algorithms examined in this . They function in the same way that organic neurons do in the human body. The chapter is organized in a systematic manner to provide an understanding of ANN-based network models to counter DDoS attacks, which is the paper's main focus, as well as the architecture and implementation of ANNs, as well as experimental investigations and findings that aid in drawing inferences about ANN-based defense models.

Network attacks, distributed denial of service attacks, ANN, training and confusion matrix.

"DETECTION OF DDoS ATTACKS ON NETWORKS USING AN IMPROVED NOVEL ANN MODEL", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 12, page no.c426-c435, December-2021, Available :http://www.jetir.org/papers/JETIR2112255.pdf

"DETECTION OF DDoS ATTACKS ON NETWORKS USING AN IMPROVED NOVEL ANN MODEL", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 12, page no. ppc426-c435, December-2021, Available at : http://www.jetir.org/papers/JETIR2112255.pdf