Analyzing Intrusion Detection Using Machine Learning Adaboost Algorithm: An Observations Study

Journal Title: INTERNATIONAL JOURNAL OF ENGINEERING TRENDS AND TECHNOLOGY - Year 2013, Vol 4, Issue 6

Abstract

 The current approaches for intrusion detection have some problems that adversely affect the effectiveness of the Intrusion Detection System. Current approaches often suffer from relatively high falsealarm rates. As most network behaviors are normal, resources are wasted on checking a large number of alarms that turn out to be false. Secondly their computational complexities are oppressively high.The adaboost algorithm gives better results for intrusion detection in this respect. The paper here mainly has its focus on these results.

Authors and Affiliations

Ms. S. S. Kazi

Keywords

Related Articles

 Re-Dispatch Approach for Congestion Relief in Deregulated Power Systems

 In the competitive power market environment, congestion is an indicator for the need of transmission system reconfiguration by compensation devices or its expansion with new lines erection. Due to economic consider...

 Elimination of Harmonics Using Active Power Filter Based on DQ Reference Frame Theory

 Active power filters have the following multiple functions; harmonic filtering, damping, isolation and termination, reactive-power control for power factor correction and voltage regulation, load balancing, volta...

 Application of Bacterial Foraging Optimisation as a De-noising filter

 De-noising of image still a concerned for researchers working in this area. It is further challenging in case of medical images mainly images of the internal organs. Various digital filters have been developed and...

 Manufacturing System: Flexibility Perspective

 Manufacturing, Planning and Control systems are one of the key that determine development of modern production systems. The article presents the importance of flexibility factor in the process of manufacturing, pla...

 Embedded System Of A Wireless-Based Theft Monitoring

 -ZigBee is a new global standard for wireless communications with the characteristics of low-cost, low power consumption, and low data rate. The design and implementation of a ZigBee-based wireless theft monitoring...

Download PDF file
  • EP ID EP109448
  • DOI -
  • Views 109
  • Downloads 0

How To Cite

Ms. S. S. Kazi (2013).  Analyzing Intrusion Detection Using Machine Learning Adaboost Algorithm: An Observations Study. INTERNATIONAL JOURNAL OF ENGINEERING TRENDS AND TECHNOLOGY, 4(6), 2302-2304. https://europub.co.uk/articles/-A-109448