• Anuj Kulkarni
• Himansshu Mita
• Prajakta Memane
• Atul Kathole

In today’s world the anomaly-based network intrusion detection techniques have become very efficient in identifying the both known and unknown types of network intrusions, in this paper we have implemented the anomaly-based technique with the help of feed forward neural network in deep learning, the dataset used for the model building was CICIDS2017 Dataset which is updated with attacks type of today's world. We were very successful in detection of intrusion types in 14 groups with very high accuracy.

Anomaly Based Network Intrusion Identification System; Artificial Intelligence; Deep Learning; Sequential Model.

"Network Intrusion Identification System using Artificial Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.251-255, May-2019, Available :http://www.jetir.org/papers/JETIRBO06047.pdf

"Network Intrusion Identification System using Artificial Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp251-255, May-2019, Available at : http://www.jetir.org/papers/JETIRBO06047.pdf