Intrusion Detection System using Binary Classifier Algorithm

Jeya S*, T. John Jeya Singh**
* Professor & Head M.C.A. Department, Dayananda Sagar Academy of Technology and Management, Bangalore, India.
** Assistant Professor, MCA Department, Sambhram Academy of Management studies, Bangalore, India.
Periodicity:January - March'2013
DOI : https://doi.org/10.26634/jse.7.3.2171

Abstract

An intrusion detection system (IDS) is a security layer used to detect ongoing intrusive activities in information systems. Traditionally, intrusion detection relies on extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, various data-mining and machine learning techniques have been deployed for intrusion detection. An IDS is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current systems depends on the system operators in working out the tuning solution and in integrating it into the detection model. In this paper, an automatically tuning IDS (ATIDS) is presented. The proposed system will automatically tune the detection model on-the-fly according to the feedback provided by the system operator when false predictions are encountered. The system is evaluated using the KDDCup’99 intrusion detection dataset.

Keywords

Attack Detection Model, Classification, Data Mining, Intrusion Detection, Artificial Intelligence.

How to Cite this Article?

Jeya., and Singh, J. J. T. (2013). Intrusion Detection System using Binary Classifier Algorithm. i-manager’s Journal on Software Engineering, 7(3), 21-23. https://doi.org/10.26634/jse.7.3.2171

References

[1]. Ashish Kamra and Elisa Bertino, (2011). “Design and Implementation of an Intrusion Response System for Relational Databases”, IEEE Transactions On Knowledge And Data Engineering, Pg.No.875-888, Vol. 23, No. 6, June 2011.
[2]. M. Brian Blake, and Michael F. Nowlan, (2011) “Knowledge Discovery in Services (KDS): Aggregating Software Services to Discover Enterprise Mashups”, IEEE Transactions On Knowledge And Data Engineering, Pg.No.889-901, Vol. 23, No. 6, June 2011.
[3]. Domenico Ficara, Andrea Di Pietro, Stefano Giordano, Gregorio Procissi, Fabio Vitucci, and Gianni Antichi, (2011). “Differential Encoding of DFAs for Fast Regular Expression Matching”, IEEE/ACM Transactions On Networking, Pg.No.683-694, Vol. 19, No. 3, June 2011.
[4]. Dominik Fisch, Thiemo Gruber, and Bernhard Sick, (2011). “SwiftRule: Mining Comprehensible Classification Rules for Time Series Analysis”, IEEE Transactions On Knowledge And Data Engineering, Vol. 23, No. 5, May 2011.
[5]. Elhadi M. Shakshuki, Nan Kang, and Tarek R. Sheltami, (2013). “A Secure Intrusion-Detection System For Manets”, IEEE Transactions On Industrial Electronics, Vol. 60, No. 3, March 2013.
[6]. Emilio Miguela, Pedro, Keith E. Brown, Yvan R. Petillot, and David M. Lane, (2011). “Semantic Knowledge-Based Framework to Improve the Situation Awareness of Autonomous Underwater Vehicles”, IEEE Transactions On Knowledge And Data Engineering, Pg.No.759-773, Vol. 23, No. 5, May 2011.
[7]. Eric Hsueh-Chan Lu, Vincent S. Tseng, Member, IEEE, and Philip S. Yu, (2011). “Mining Cluster-Based Temporal Mobile Sequential Patterns in Location-Based Service Environments”, IEEE Transactions On Knowledge And Data Engineering, Pg.No.914-927, Vol. 23, No. 6, June 2011.
[8]. Haoyu Song, and Jonathan S. Turner, (2013). “ACMABC: Adaptive Binary Cuttings for Multidimensional Packet Classification”, IEEE/ACM Transactions On Networking, Vol. 21, No. 1, February 2013.
[9]. Hua Lu, and Man Lung Yiu, (2011). “On Computing Farthest Dominated Locations”, IEEE Transactions On Knowledge And Data Engineering, Vol. 23, No. 6, June 2011.
[10]. Ioannis Hatzilygeroudis, and Jim Prentzas, (2010). “Integrated Rule-Based Learning and Inference”, IEEE Transactions On Knowledge And Data Engineering, Pg.No. 1549-1563, Vol. 22, No. 11, November 2010.
[11]. Irem Y. Tumer, and Carol S. Smidts, (2011). “Integrated Design-Stage Failure Analysis of Software-Driven Hardware Systems”, IEEE Transactions On Computers, Pg. No.1072- 1084, Vol. 60, No. 8, August 2011.
[12]. Javier Carretero, Xavier Vera, Pedro Chaparro, and Jaume Abella, (2010). “Microarchitectural Online Testing for Failure Detection in Memory Order Buffers”, IEEE Transactions On Computers, Pg.No. 623-637, Vol. 59, No. 5, May 2010.
[13]. Mahesh Balakrishnan, Tudor Marian, Kenneth P. Birman, Hakim Weatherspoon, and Lakshmi Ganesh, (2011). “Maelstrom: Transparent Error Correction for Communication Between Data Centers”, IEEE/ACM Transactions On Networking, Pg.No.617-629, Vol. 19, No. 3, June 2011.
[14]. Matt Duckham, Doron Nussbaum, (2011). “Efficient, Decentralized Computation of the Topology of Spatial Regions”, IEEE Transactions On Computers, Pg.No.1100- 1113, Vol. 60, No. 8, August 2011.
[15]. Mehran Mozaffari-Kermani and Arash Reyhani- Masoleh, (2010). “Concurrent Structure-Independent Fault Detection Schemes for the Advanced Encryption Standard”, IEEE Transactions On Computers, Pg.No.608- 623, Vol. 59, No. 5, May 2010.
[16]. Mohammad M. Masud, Jing Gao, Latifur Khan, Jiawei Han, and Bhavani Thuraisingham, (2011). “Classification and Novel Class Detection in Concept- Drifting Data Streams under Time Constraints”, IEEE Transactions On Knowledge And Data Engineering, Pg.No.859-874 , Vol. 23, No. 6, June 2011.
[17]. Panagiotis Papadimitriou and Hector Garcia- Molina, (2011). “Data Leakage Detection”, IEEE Transactions On Knowledge And Data Engineering, Pg.No.51-64, Vol. 23, No. 1, January 2011.
[18]. Rachid Hadjidj and Hanifa Boucheneb, (2011). “Efficient Reachability Analysis for Time Petri Nets”, IEEE Transactions on Computers, Vol. 60, No. 8, August 2011.
[19]. Yu-Wei Eric Sung, Xin Sun, Sanjay G. Rao, Geoffrey G. Xie, and David A. Maltz, “Towards Systematic Design of Enterprise Networks”, IEEE/ACM Transactions On Networking,
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Pdf 35 35 200 20
Online 35 35 200 15
Pdf & Online 35 35 400 25

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.