Data Mining Techniques for (Network) Intrusion Detection Systems
نویسندگان
چکیده
In Information Security, intrusion detection is the act of detecting actions that attempt to compromise the confidentiality, integrity or availability of a resource. Intrusion detection does not, in general, include prevention of intrusions. In this paper, we are mostly focused on data mining techniques that are being used for such purposes. We debate on the advantages and disadvantages of these techniques. Finally we present a new idea on how data mining can aid IDSs. General Terms Security, Data mining
منابع مشابه
Overview of Intrusion Detection Techniques in Database
Data is one of the most valuable assets in today's world and is used in the everyday life of every person and organization. This data stores in a database in order to restore and maintain its efficiently. Since there is a database that can be exploited by SQL injection attacks, internal threats, and unknown threats, there are always concerns about the loss or alteration of data by unauthorized ...
متن کاملMoving dispersion method for statistical anomaly detection in intrusion detection systems
A unified method for statistical anomaly detection in intrusion detection systems is theoretically introduced. It is based on estimating a dispersion measure of numerical or symbolic data on successive moving windows in time and finding the times when a relative change of the dispersion measure is significant. Appropriate dispersion measures, relative differences, moving windows, as well as tec...
متن کاملApplication of Data Mining in Network Intrusion Detection System
This paper presents a brief review of the application of various Data Mining techniques and their advances in the design, development and application of Intrusion Detection Systems (IDS) for protecting computer and communication networks from intruders. Data mining techniques are used to monitor and analyze large amount of network data & classify these network data into anomalous and normal dat...
متن کاملA hybridization of evolutionary fuzzy systems and ant Colony optimization for intrusion detection
A hybrid approach for intrusion detection in computer networks is presented in this paper. The proposed approach combines an evolutionary-based fuzzy system with an Ant Colony Optimization procedure to generate high-quality fuzzy-classification rules. We applied our hybrid learning approach to network security and validated it using the DARPA KDD-Cup99 benchmark data set. The results indicate t...
متن کاملA Hybrid Machine Learning Method for Intrusion Detection
Data security is an important area of concern for every computer system owner. An intrusion detection system is a device or software application that monitors a network or systems for malicious activity or policy violations. Already various techniques of artificial intelligence have been used for intrusion detection. The main challenge in this area is the running speed of the available implemen...
متن کاملSecuring Cluster-heads in Wireless Sensor Networks by a Hybrid Intrusion Detection System Based on Data Mining
Cluster-based Wireless Sensor Network (CWSN) is a kind of WSNs that because of avoiding long distance communications, preserve the energy of nodes and so is attractive for related applications. The criticality of most applications of WSNs and also their unattended nature, makes sensor nodes often susceptible to many types of attacks. Based on this fact, it is clear that cluster heads (CHs) are ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2007