Data Mining Techniques for Network Intrusion Detection and Prevention Systems

Nareshkumar D. Harale; Dr. B. B. Meshram

doi:10.21276/ijircst.2016.4.6.3

Abstract

The main purpose of Intrusion Detection Systems(IDS) and Intrusion protection Systems(IPS) for data mining is to discover patterns of program and user activity, and determine what set of events indicate an attack. In the last years, the networking revolution has finally come of age. More than ever before, we see that the Internet is changing computing as we know it. The possibilities and opportunities are limitless; unfortunately, so too are the risks and chances of malicious intrusions. In Network Security, intrusion detection and prevention system is the act of detecting activity or action that attempt to compromise the confidentiality, integrity or availability of a resource. Intrusion prevention techniques, such as user authentication avoiding programming errors, and information protection (e.g., encryption) have been used to protect computer systems is act as first line of defense. We focus on issues related to deploying a data mining-based IDS in a real time of networking environment. To improve accuracy and security, data mining programs are used to analyze audit data and extract features that can distinguish normal activities from intrusions. In this paper presents an intrusion detection system architecture consisting of network sensors, detectors, a data warehouse, and model generation components and we can identify network attack and which type of attack on databases being take place.

Keywords

Data Mining, Network IDS, Network IPS, Network Security

References

[1] J.P Anderson “Computer Security Threat Monitoring and Surveillance. Technical report”

[2] Bradley, T. (n.d.). ,”Introduction to Intrusion Detection Systems (IDS”) [Online] Available on http://netsecurity.about.com/cs/hackertools/a/aa030504.html.

[3] “Network Intrusion Detection System (NIDS) Using Data Mining Techniques” [Online] Available on http://etrx.spit.ac.in/ieee_colloquium/Information_Security/spit265.pdf.

[4] Intrusion Detection and Prevention Scorecard [Online] Available on http://www.strategy2act.com/solutions/scorecardreports/bsc_intrusion_prevention.html.

[5] What is an IDS? [Online] Available on http://www.idstutorial.com/what-is-ids.php.

[6]” A Data Mining Framework for Building Intrusion Detection Models1”.[Online] Available on, http://citeseerx.ist.psu.edu/viewdoc/download.

[7] “. Network intrusion detection (IDS) and intrusion protection system (IPS)” [Online] Available on http://www.cdacbangalore.in/design/corporate_site/override/pdfdoc/projects/GYN.pdf.

[8] Available on http://www.securityfocus.com/news/2445.

[9] Eric Bloedorn, Alan D. Christiansen, William Hill,Clement Skorupka, Lisa M. Talbot, Jonathan TivelThe MITRE Corporation.”Data Mining for Network Intrusion Detection: How to Get Started”

[10] Data Mining Techniques for (Network) Intrusion Detection Systems Theodoros Lappas and Konstantinos Pelechrinis [Online] Available on http://www.mendeley.com/research/datawarehousing-and-data-mining-techniques-for-intrusion-detectionsystems/

[11] Mohammad hossein haratian ” An architectural design for a hybrid intrusion detection system for data base “,. [Online] Available on www.citeseerx.ist.psu.edu/viewdoc/download.

[12]” A Data Mining Framework for Constructing Features and Models for Intrusion DetectionSystems”.,Wenke Lee,[Online] Available on http://portal.acm.org/citation.cfm?id=929987&dl=GUIDE&coll=G UIDE.

[13]Bhavna Dharamkar, Rajni Ranjan Singh,“A Review of Cyber Attack Classification Technique Based on Data Mining and Neural Network Approach “, International Journal of Computer Trends and Technology (IJCTT) – volume 7 number 2– Jan 2014 ( ISSN: 2231-2803)

[14]Usman Asghar Sandhu, Sajjad Haider, Salman Naseer, Obaid Ullah Ateeb , “A Survey of Intrusion Detection & Prevention Techniques “,”2011 International Conference on Information Communication and Management”, IPCSIT vol.16 (2011) © (2011) IACSIT Press, Singapore.

[14]Jamal Raiyn ,” A survey of Cyber Attack Detection Strategies “International Journal of Security and Its Applications Vol.8, No.1 (2014), pp.247-256 http://dx.doi.org/10.14257/ijsia.2014.8.1.23.

[15]Onwubiko† and A. P. Lenaghan, “Managing Security Threats and Vulnerabilities for Small to Medium Enterprises “, IEEE International Conference on Intelligence and Security Informatics 2007. http://hackmageddon.com/tag/cyber-warfare/ [Cyber Attack Statist]

Cites this article as

N. D. Harale, D. B. B. Meshram, "Data Mining Techniques for Network Intrusion Detection and Prevention Systems ", International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-4, Issue-6, Page No-175-180, 2016. Available from: https://doi.org/10.21276/ijircst.2016.4.6.3

Corresponding Author

Nareshkumar D. Harale

Research Scholar at SGB Amravati University , Amravati, Maharashtra, India

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