Performance Enhancement of Intrusion Detection using Neuro - Fuzzy Intelligent System
Journal Title: Indian Journal of Computer Science and Engineering - Year 2014, Vol 5, Issue 5
Abstract
This research work aims at developing hybrid algorithms using data mining techniques for the effective enhancement of anomaly intrusion detection performance. Many proposed algorithms have not addressed their reliability with varying amount of malicious activity or their adaptability for real time use. The study incorporates a theoretical basis for improvement in performance of IDS using K-medoids Algorithm, Fuzzy Set Algorithm, Fuzzy Rule System and Neural Network techniques. Also statistical significance of estimates has been looked into for finalizing the best one using DARPA network traffic datasets.
Authors and Affiliations
Dr. K. S. Anil Kumar , Dr. V. Nanda Mohan
WEB BASED E-LEARNING IN INDIA: THE CUMULATIVE VIEWS OF DIFFERENT ASPECTS
In the presence of great social diversity in India, it is difficult to change the social background of students, parents and their economical conditions. Therefore the only option left for us is to provide uniform or sta...
AN ENCRYPTION ALGORITHM FOR IMPROVING DATABASE SECURITY USING ROT & REA
Database is an organized collection of data, many user wants to store their personal and confidential data’s in such database. Unauthorized persons may try to get the data’s from database and misuse them without the owne...
REGULATED RR-MAC PROTOCOL FOR WIRELESS SENSOR NETWORKS
This paper proposes RR-MAC, a medium-access control (MAC) protocol used for sensor networks. Wireless sensor networks uses battery power to sense the devices. It consists of spatially distributed autonomous sensors to mo...
MOMENT AND DENSITY BASED HADWRITTEN MARATHI NUMERAL RECOGNITION
In this paper, we present an OCR for handwritten Marathi Numerals recognition using two sets of features, namely, density and central moments. Central moments of order 3 and 4 are computed globally for the numeral image...
A literature study on clustering the uncertainty data
Clustering is one of the important topics in data mining. The purpose of clustering is to group the similar data items. Clustering the uncertainty data is not an easy task but an essential task in data mining. Uncertain...