• Hashmat Fida
• Tayeed Ahmad Hajam
• Dr. K. Suresh Joseph

As internet architecture has undergone a drastic change due to the emerging technologies. It is very difficult to implement the improved and updated security models and make the network more secure. The future technologies must offer additional and better security over current networks.Attacks such as alteration, spoofing and DDoS are unconditionally directed in NDN architecture. Moreover, some specific DDoS attacks are only meant for NDN. DDoS attacks in NDN are generally incorporated with the help of interest flooding. A distributed denial-of-service (DDoS) attack is an attempt, rather a destructive aim to distort the usual traffic of a selected server, network or service by overpowering the target or its corresponding systems or infrastructure with a spate of internet traffic. This attack has various disadvantages over the security of the network. This paper thrives a framework which uses a machine learning technique to mitigate DDoS. Firstly, we choose a training data set to describe the characteristics of the traffic. Then as per our survey, we found TF-IDF technique to transform the data set into matric form. To reduce the dimensions of the features and time complexity, we discovered that LDA algorithm is more feasible for our work. Also, RNN Algorithm was found useful and suitable for our work as a detection model. LDA reduces the prediction time significantly. For real data set, LDA can achieve a remarkable performance in terms of accuracy, sensitivity etc. compared to other detection models ofDDoS.

, LDA, Interest Flooding, Alteration, Spoofing, RNN, PIT, FIB, DGEA

"A Framework for Mitigating DDoS Attacks in Named Data Networking Using Machine Learning Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.684-689, June 2019, Available :http://www.jetir.org/papers/JETIR1908A50.pdf

"A Framework for Mitigating DDoS Attacks in Named Data Networking Using Machine Learning Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp684-689, June 2019, Available at : http://www.jetir.org/papers/JETIR1908A50.pdf