A survey on anomaly based intrusion detection system

Author:

Daniya T.,Suresh Kumar K.,Santhosh Kumar B.,Sekhar Kolli Chandra

Publisher

Elsevier BV

Subject

General Medicine

Reference23 articles.

1. “Network Security” from https://www.tutorialspoint.com/information¬ security cyber law/ network_security.htm.

2. Ramp loss K-support vector classification-regression; a robust and sparse multi-class approach to the intrusion detection problem;Hosseini Bamakan;Knowl.-Based Syst.,2017

3. A systematic study of image forgery detection;Kumar;J. Comput. Theor. Nanosci. (Scopus),2018

4. Rana Aamir Raza Ashfaq, Xi-Zhao Wang, Joshua Zhexue Huang, Haider Abbas, Yu-lin He, “Method of intrusion detection using deep neural network, ” Proc. Inf. Sci. 2016 pp. 313-316.

5. El Mostapha Chakir, Youness Idrissi Khamlichi, Mohamed Moughit, “Handling Alerts for Intrusion Detection System Using Stateful Pattern Matching,” in Proceedings of 2016 4th IEEE International Colloquium on Information Science and Technology (CiSt), pp.139-144, 24-26 Oct, Tangier Morocco, 2016.

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