Attacks over the internet have become an increasing menace in recent time which tries to hack or illegally tamper with the data available over the networks. On the other hand, there has been an increase in volume in research contributions to effectively counter attack these attacks and implement a strong defence mechanism. There have been numerous algorithms and frameworks implemented in recent times which are intelligent and soft computing based. These evolution based algorithms play a vital role in self adapting the system under attack towards increasing and new types of attacks which are increasing day by day. One such area of soft computing algorithms investigated in this chapter is the artificial neural network or popularly known as ANNs. They work analogous to the biological neurons in the human body. The chapter is organized in a systematic manner to give an insight in to ANN based network models to counter attack DDoS attacks which has been the primary focus of this thesis, architecture and implementation of ANNs, the experimental investigations and findings which help in drawing an inference of ANN based defence models.
CITATION STYLE
Rasheed, B. H., Sivaram, M., Yuvaraj, D., & Mohamed Uvaze Ahamed, A. (2019). An improved novel ANN model for detection of DDoS attacks on networks. International Journal of Advanced Trends in Computer Science and Engineering, 8(14), 9–16. https://doi.org/10.30534/ijatcse/2019/0281.42019
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