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Microsystem Technologies
Erschienen in: Microsystem Technologies 4/2017

24.02.2016 | Technical Paper

Fuzzy min–max neural network and particle swarm optimization based intrusion detection system

verfasst von: Chandrashekhar Azad, Vijay Kumar Jha

Erschienen in: Microsystem Technologies | Ausgabe 4/2017

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Abstract

To maintain the integrity, availability, reliability of the data and services available on web requires a strong network security framework, in such consequence IDS based on data mining are the best solution. In this paper we proposed an intrusion detection system which is based on the fuzzy min max neural network and the particle swarm optimization. The proposed system is tested with the help of preprocessed KDD CUP data set. Classification accuracy and classification error are taken as a performance evaluation parameter to test the effectiveness of the system. The proposed system is compared with the some of the well-known methods, the results shows that the proposed system performed well as compared to the other systems.
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Literatur
Abadeh MS, Mohamadi H, Habibi J (2011) Design and analysis of genetic fuzzy systems for intrusion detection in computer networks. Expert Syst Appl 38(6):7067–7075CrossRef
Alcala-Fdez J et al (2009) KEEL: a software tool to assess evolutionary algorithms for data mining problems. Soft Comput 13(3):307–318CrossRef
Altwaijry H (2013) Bayesian based intrusion detection system. In: Kim HK et al (eds) IAENG transactions on engineering technologies, Lecture Notes in Electrical Engineering, vol 170. Springer, Netherlands. doi:10.​1007/​978-94-007-4786-9_​3
Anderson JP (1980) Computer security threat monitoring and surveillance. Technical report, James P. Anderson Company, Fort Washington, PA
Anming Z (2012) An intrusion detection algorithm based on NFPA. Phys Proc 33:491–497CrossRef
Aydın MA, Zaim AH, Ceylan KG (2009) A hybrid intrusion detection system design for computer network security. Comput Electr Eng 35(3):517–526CrossRefMATH
Azad C, Jha VK (2013) Data mining in intrusion detection: a comparative study of methods, types and data sets. Int J Inf Technol Comput Sci 5(8):75–90
Azad C, Jha VK (2014) Data mining based hybrid intrusion detection system. Indian J Sci Technol 7(6):781–789
Balajinath B, Raghavan SV (2001) Intrusion detection through learning behavior model. Comput Commun 24(12):1202–1212CrossRef
Barbara D, Jajodia S (2002) Applications of data mining in computer security. Springer Science & Business Media, Berlin, p 6CrossRefMATH
Barbará D, Couto J, Jajodia S, Wu N (2001) ADAM: a testbed for exploring the use of data mining in intrusion detection. ACM Sigmod Record 30(4):15–24CrossRef
Bazan JG, Nguyen HS, Nguyen SH, Synak P, Wróblewski J (2000) Rough set algorithms in classification problem. In: Rough set methods and applications, Physica-Verlag HD, pp 49–88
Boulaiche A, Bouzayani H, Adi K (2012) A quantitative approach for intrusions detection and prevention based on statistical n-gram models. In: Proceedings of the 3rd international conference on ambient systems, networks and technologies (ANT), procedia computer science, vol 10, pp 450–457
Brauckhoff D, Dimitropoulos X, Wagner A, Salamatian K (2012) Anomaly extraction in backbone networks using association rules. IEEE/ACM Trans Netw 20(6):1788–1799CrossRef
Carvalho DR, Freitas AA (2004) A hybrid decision tree/genetic algorithm method for data mining. Inf Sci 163(1):13–35CrossRef
Casas P, Mazel J, Owezarski P (2012) Unsupervised network intrusion detection systems: detecting the unknown without knowledge. Comput Commun 35(7):772–783CrossRef
Chari SN, Cheng PC (2003) BlueBox: a policy-driven, host-based intrusion detection system. ACM Trans Inf Syst Secur 6(2):173–200CrossRef
Chirag Modi et al (2013) A survey of intrusion detection techniques in cloud. J Netw Comput Appl 36(1):42–57CrossRef
Denning DE (1987) An intrusion-detection model. IEEE Trans Softw Eng 13(2):222–232CrossRef
Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH (2009) The WEKA data mining software: an update. ACM SIGKDD Explor Newsl 11(1):10–18CrossRef
Joo D, Hong T, Han I (2003) The neural network models for IDS based on the asymmetric costs of false negative errors and false positive errors. Expert Syst Appl 25(1):69–75CrossRef
Kenkre PS, Pai A, Colaco L (2015) Real time intrusion detection and prevention system. In: Proceedings of the 3rd international conference on frontiers of intelligent computing: theory and applications (FICTA). Springer International Publishing, pp 405–411
Kennedy J (2010) Particle swarm optimization. In: Encyclopedia of machine learning. Springer, USA, pp 760–766
Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks. Piscataway, NJ, pp 1942–1948
Lei JZ, Ghorbani AA (2012) Improved competitive learning neural networks for network intrusion and fraud detection. Neurocomputing 75(1):135–145CrossRef
Levin I (2000) KDD-99, classifier learning contest: LLSoft’s results overview. SIGKDD Explor 1(2):67–75CrossRef
Linda O, Vollmer T, Manic M (2009) Neural network based intrusion detection system for critical infrastructures. In: Neural networks, IJCNN 2009. International Joint Conference on 2009. IEEE. pp 1827–1834
Lunt TF, Jagannathan R, Lee R, Listgarten S, Edwards DL, Neumann PG, Javitz HS, Valdes A (1988) Ides: the enhanced prototype-a real-time intrusion-detection expert system. In: SRI International, 333 Ravenswood Avenue, Menlo Park
Onwubiko C (2012) Situational awareness in computer network defense: principles, methods and applications. IGI Global, Hershey, PACrossRef
Panchev C, Dobrev P, Nicholson J (2014) Detecting port scans against mobile devices with neural networks and decision trees. In: Engineering applications of neural networks. Springer International Publishing, pp 175-182
Pfahringer B (2000) Winning the KDD99 classification cup: bagged boosting. ACM SIGKDD Explor Newsl 1(2):65–66CrossRef
Sangeetha S et al (2015) Signature based semantic intrusion detection system on cloud. Information systems design and intelligent applications. Springer, India, pp 657–666
Sarasamma ST, Zhu Q, Huff J (2005) Hierarchical Kohonenen net for anomaly detection in network security. IEEE Trans Syst Man Cybern B Cybern 35(2):302–312CrossRef
Shun J, Malki H (2008) Network intrusion detection system using neural networks. In: Natural computation, 2008. ICNC’08. Fourth International Conference on 2008, vol 5, IEEE. pp 242–246
Simpson PK (1992) Fuzzy min-max neural networks. I. Classification. IEEE Trans Neural Netw 5:776–786CrossRef
Sindhu SS, Geetha S, Kannan A (2012) Decision tree based light weight intrusion detection using a wrapper approach. Expert Syst Appl 39(1):129–141CrossRef
Tong X, Wang Z, Yu H (2009) A research using hybrid RBF/Elman neural networks for intrusion detection system secure model. Comput Phys Commun 180(10):1795–1801CrossRef
Vasilomanolakis E, Karuppayah S, Mühlhäuser M, Fischer M (2015) Taxonomy and survey of collaborative intrusion detection. ACM Comput Surv (CSUR) 47(4):55CrossRef
Wang G, Hao J, Ma J, Huang L (2010) A new approach to intrusion detection using Artificial Neural Networks and fuzzy clustering. Expert Syst Appl 37(9):6225–6232CrossRef
Wei M, Xia L, Jin J, Chen C (2014) Research of intrusion detection based on clustering analysis. In: Proceedings of the 2012 international conference on cybernetics and informatics. pp 1973–1979
Metadaten
Titel
Fuzzy min–max neural network and particle swarm optimization based intrusion detection system
verfasst von
Chandrashekhar Azad
Vijay Kumar Jha
Publikationsdatum
24.02.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Microsystem Technologies / Ausgabe 4/2017
Print ISSN: 0946-7076
Elektronische ISSN: 1432-1858
DOI
https://doi.org/10.1007/s00542-016-2873-8

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