IDS in Telecommunication Network Using PCA

作者: A. M. Mohamed , T. K. Abdelhamid , Mohamed Faisal Elrawy

DOI:

关键词: Host-based intrusion detection systemIntrusion prevention systemWeb threatAnomaly detectionComputer securityIntrusion detection systemComputer networkComputer scienceAnomaly-based intrusion detection systemData securityTelecommunications networkInformation system

摘要: Data Security has become a very serious part of any organizational information system. Internet threats have more intelligent so it can deceive the basic security solutions such as firewalls and antivirus scanners. To enhance overall network an additional layer intrusion detection system (IDS) to be added. The anomaly IDS is type that differentiate between normal abnormal in data monitored. This paper proposes two types IDS, one them used (NIDS) with success (0.9161) high rate (0.9288) other also host (HIDS) (0.8493) (0.9628) using NSL-KDD set.

参考文章(16)
Noelia Sánchez-Maroño, Beatriz Pérez-Sánchez, Amparo Alonso-Betanzos, Juan A. Suárez-Romero, Félix M. Carballal-Fortes, Classification of computer intrusions using functional networks. A comparative study. the european symposium on artificial neural networks. pp. 579- 584 ,(2007)
Kanoksri Sarinnapakorn, Mei-Ling Shyu, Shu-Ching Chen, LiWu Chang, A Novel Anomaly Detection Scheme Based on Principal Component Classifier international conference on data mining. pp. 172- 179 ,(2003)
Basabi Chakraborty, Feature Subset Selection by Neuro-rough Hybridization Lecture Notes in Computer Science. pp. 519- 526 ,(2000) , 10.1007/3-540-45554-X_64
Gholam Reza Zargar, Tania Baghaie, Category-Based Intrusion Detection Using PCA Journal of Information Security. ,vol. 3, pp. 259- 271 ,(2012) , 10.4236/JIS.2012.34033
Christos Boutsidis, Michael W. Mahoney, Petros Drineas, Unsupervised feature selection for principal components analysis Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD 08. pp. 61- 69 ,(2008) , 10.1145/1401890.1401903
Mahbod Tavallaee, Ebrahim Bagheri, Wei Lu, Ali A. Ghorbani, A detailed analysis of the KDD CUP 99 data set computational intelligence and security. pp. 53- 58 ,(2009) , 10.1109/CISDA.2009.5356528
Srilatha Chebrolu, Ajith Abraham, Johnson P Thomas, None, Feature deduction and ensemble design of intrusion detection systems Computers & Security. ,vol. 24, pp. 295- 307 ,(2005) , 10.1016/J.COSE.2004.09.008
K. Ilgun, R.A. Kemmerer, P.A. Porras, State transition analysis: a rule-based intrusion detection approach IEEE Transactions on Software Engineering. ,vol. 21, pp. 181- 199 ,(1995) , 10.1109/32.372146
Isabelle Guyon, André Elisseeff, An introduction to variable and feature selection Journal of Machine Learning Research. ,vol. 3, pp. 1157- 1182 ,(2003) , 10.1162/153244303322753616
A.H. Sung, S. Mukkamala, Identifying important features for intrusion detection using support vector machines and neural networks symposium on applications and the internet. pp. 209- 216 ,(2003) , 10.1109/SAINT.2003.1183050