1 |
G.C. Tjhai, S.M. Furnell, M. Papadaki, N.L. Clarke, A preliminary two-stage alarm correlation and filtering system using som neural network and k -means algo- rithm, Comput. Security 29 (6) (2010) 712-723. http://dx.doi.org/10.1016/j.cose.2010.02.001.
DOI
|
2 |
Somasundaram, A. and Reddy, U.S., 2017, June. Modelling a stable classifier for handling large scale data with noise and imbalance. In 2017 International Conference on Computational Intelligence in Data Science (ICCIDS) (pp. 1-6). IEEE.
|
3 |
Akila, S. and Reddy, U.S., 2016. Data imbalance: effects and solutions for classification of large and highly imbalanced data. Proceedings of ICRECT, 16, pp.28-34.
|
4 |
Chellammal, P., and Sheba Kezia PD Malarchelvi. "Real-time anomaly detection using parallelized intrusion detection architecture for streaming data." concurrency and computation-practice & experience 32, no. 4 (2020).
|
5 |
Intrusion Detection in Computer Networks using Lazy Learning Algorithm
|
6 |
Samuel Marchal, Xiuyan Jiangz, Radu State, Thomas Engel (2014) "A Big Data Architecture for Large Scale Security Monitoring" , Springer.
|
7 |
G. Liu, F. Hu, W. Chen, A neural network ensemble based method for detecting computer virus, in: 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, Vol. 1, Aug 2010, pp. 391-393.
|
8 |
J.Wu, D. Peng, Z. Li, L. Zhao, H. Ling, Network intrusion detection based on a general regression neural network optimized by an improved artificial immune algorithm, PLOS ONE 10 (3) (2015) 1-13.
|
9 |
Kumar, V. D., & Radhakrishnan, S. (2014, April). Intrusion detection in MANET using self organizing map (SOM). In Recent Trends in Information Technology (ICRTIT), 2014 International Conference on (pp. 1-8). IEEE.
|
10 |
X.-S. Yang,"Firefly algorithm, Levy flights and global optimization", in: Research and Development in Intelligent Systems XXVI (Eds M. Bramer, R. Ellis, M. Petridis), Springer London, pp. 209-218 (2010)
|
11 |
S. Revathi and A. Malathi, "Data Preprocessing for Intrusion Detection System using Swarm Intelligence Techniques," International Journal of Computer Applications , Volume 75- No.6, August 2013
|
12 |
Kalita, D.J., Singh, V.P. and Kumar, V., 2020. SVM Hyper-Parameters Optimization using Multi-PSO for Intrusion Detection. In Social Networking and Computational Intelligence (pp. 227-241). Springer, Singapore.
|
13 |
Point Biserial Coefficient (Keith Calkins, 2005)
|
14 |
Sung-Hwan Ahn, Nam-Uk Kim,Tai-Myoung Chung (2014) "Big Data Analysis System Concept for Detecting Unknown Attacks", IEEE.
|
15 |
B. Luo, J. Xia, A novel intrusion detection system based on feature generation with visualization strategy, Expert Syst. Appl. 41 (9) (2014) 4139-4147. http://dx.doi.org/10.1016/j.eswa.2013.12.048.
DOI
|
16 |
Network Intrusion Detection in Big Dataset Using Spark
|
17 |
Intelligent intrusion detection systems using artificial neural networks
|
18 |
Dimensionality Reduction with IG-PCA and Ensemble Classifier for Network Intrusion Detection
|
19 |
Firefly algorithm based Feature Selection for Network Intrusion Detection
|
20 |
Jiang, H., He, Z., Ye, G. and Zhang, H., 2020. Network Intrusion Detection Based on PSO-Xgboost Model. IEEE Access.
|
21 |
Unsupervised intrusion detection through skip-gram models of network behavior
|
22 |
An effective intrusion detection framework based on SVM with feature augmentation
|
23 |
C.F. Tsai, Y.F. Hsu, C.Y. Lin, W.Y. Lin, Intrusion detection by machine learning: a review, Expert Syst. Appl. Int. J. 36 (10) (2009) 11994-12000. http://dx.doi.org/10.1016/j.eswa.2009.05.029.
DOI
|
24 |
H.J. Liao, C.H.R. Lin, Y.C. Lin, K.Y. Tung, Intrusion detection system: a compre- hensive review, J. Netw. Comput. Appl. 36 (1) (2013) 16-24. http://dx.doi.org/10.1016/j.jnca.2012.09.004.
DOI
|