Introducing a Two-step Strategy based on Deep Learning Enhance the Accuracy of Intrusion Detection Systems in the Network

Subject Areas : Majlesi Journal of Telecommunication Devices

Ali Bahmani ¹ , Amirhassan Monajemi ²

1 - Islamic Azad University Isfahan
2 -

Received: 2019-03-06 Accepted : 2019-03-13 Published : 2019-03-01

Keywords:

References:

1. Rhodes-Ousley M. Information security: the complete reference: McGraw Hill Education; 2013.

2. McClure S, Shah S, Shah S. Web hacking: Attacks and defense: Addison-Wesley Longman Publishing Co., Inc.; 2002.

3. Liao H-J, Lin C-HR, Lin Y-C, Tung K-Y. Intrusion detection system: A comprehensive review. Journal of Network and Computer Applications. 2013;36(1):16-24.

4. Kumar V, Chauhan H, Panwar D. K-means clustering approach to analyze NSL-KDD intrusion detection dataset. International Journal of Soft. 2013.

5. LeCun Y, Bengio Y, Hinton G. Deep learning. nature. 2015;521(7553):436.

6. Kemmerer RA, Vigna G. Intrusion detection: a brief history and overview. Computer. 2002;35(4):supl27-supl30.

7. Lee W, Stolfo SJ, Mok KW, editors. Mining Audit Data to Build Intrusion Detection Models. KDD; 1998.

8. Kabiri P, Ghorbani AA. Research on intrusion detection and response: A survey. IJ Network Security. 2005;1(2):84-102.

9. Chung YY, Wahid N. A hybrid network intrusion detection system using simplified swarm optimization (SSO). Applied Soft Computing. 2012;12(9):3014-22.

10. Zbeel BM. Using Genetic Algorithm for Network Intrusion Detection. kufa studies center journal. 2013;1(29):209-24.

11. Horng S-J, Su M-Y, Chen Y-H, Kao T-W, Chen R-J, Lai J-L, et al. A novel intrusion detection system based on hierarchical clustering and support vector machines. Expert systems with Applications. 2011;38(1):306-13.

12. Chen C-M, Guan D-J, Huang Y-Z, Ou Y-H. Anomaly network intrusion detection using hidden Markov model. Int J Innov Comput Inform Control. 2016;12:569-80.

13. Ashfaq RAR, Wang X-Z, Huang JZ, Abbas H, He Y-L. Fuzziness based semi-supervised learning approach for intrusion detection system. Information Sciences. 2017;378:484-97.

14. Dash T. A study on intrusion detection using neural networks trained with evolutionary algorithms. Soft Computing. 2017;21(10):2687-700.

15. Chen M-H, Chang P-C, Wu J-L. A population-based incremental learning approach with artificial immune system for network intrusion detection. Engineering Applications of Artificial Intelligence. 2016;51:171-81.