Mirnal Kanti Ghose

Work place: Sikkim University, Sikkim, India

E-mail: mkghose@cus.ac.in

Website:

Research Interests: Computer systems and computational processes, Autonomic Computing, Distributed Computing, Data Structures and Algorithms

Biography

Prof.(Dr.) Mrinal Kanti Ghose, is currently working as a visiting faculty at Sikkim University, Sikkim, India. He was a former Dean (Academics), Professor & HOD at CSE Department Sikkim Manipal Institute of Technology, Majhitar, Sikkim. Prior to his academic career he was formerly a Sr. Scientist at Vikram Sarabhai Space Centre & RRSSC (E), ISRO, India.

Author Articles
Deep Learning Approach on Network Intrusion Detection System using NSL-KDD Dataset

By Sandeep Gurung Mirnal Kanti Ghose Aroj Subedi

DOI: https://doi.org/10.5815/ijcnis.2019.03.02, Pub. Date: 8 Mar. 2019

The network infrastructure of any organization is always under constant threat to a variety of attacks; namely, break-ins, security breach or system misuse. The Network Intrusion Detection System (NIDS) employed in a network detects such penetration attacks and intrusions within a network. Known classes of attacks can be detected easily by performing pattern matching while the unknown attacks are harder to detect. An attempt has been made to design a system using a deep learning approach for intrusion detection that not only learns but also adjusts itself to the patterns not defined earlier. Sparse auto-encoder has been used for unsupervised feature learning. Logistic classifier is then utilized for classification on NSL-KDD dataset. The performance of the system has been measured with respect to accuracy, precision and recall and the results have been found to be very promising for future use and modifications.

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