A Novel Intrusion Detection Method

نویسندگان

  • Shengyi Jiang
  • Qinghua Li
  • Hui Wang
چکیده

It is an important issue for the security of network that how to detect new intrusions attack. This paper investigates unsupervised intrusion detection method. A distance definition for mixed attributes, a simple method calculating cluster radius threshold, a outlier factor measured deviating degree of a cluster, and a novel intrusion detection method are proposed in this paper. The experimental results show that the method has promising performance with high detection rate and low false alarm rate, also can detect new intrusion.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

تولید خودکار الگوهای نفوذ جدید با استفاده از طبقه‌بندهای تک کلاسی و روش‌های یادگیری استقرایی

In this paper, we propose an approach for automatic generation of novel intrusion signatures. This approach can be used in the signature-based Network Intrusion Detection Systems (NIDSs) and for the automation of the process of intrusion detection in these systems. In the proposed approach, first, by using several one-class classifiers, the profile of the normal network traffic is established. ...

متن کامل

Intrusion Detection based on a Novel Hybrid Learning Approach

Information security and Intrusion Detection System (IDS) plays a critical role in the Internet. IDS is an essential tool for detecting different kinds of attacks in a network and maintaining data integrity, confidentiality and system availability against possible threats. In this paper, a hybrid approach towards achieving high performance is proposed. In fact, the important goal of this paper ...

متن کامل

A Novel Intrusion Detection Systems based on Genetic Algorithms-suggested Features by the Means of Different Permutations of Labels’ Orders

Intrusion detection systems (IDS) by exploiting Machine learning techniques are able to diagnose attack traffics behaviors. Because of relatively large numbers of features in IDS standard benchmark dataset, like KDD CUP 99 and NSL_KDD, features selection methods play an important role. Optimization algorithms like Genetic algorithms (GA) are capable of finding near-optimum combination of the fe...

متن کامل

Entropy Based Fuzzy Rule Weighting for Hierarchical Intrusion Detection

Predicting different behaviors in computer networks is the subject of many data mining researches. Providing a balanced Intrusion Detection System (IDS) that directly addresses the trade-off between the ability to detect new attack types and providing low false detection rate is a fundamental challenge. Many of the proposed methods perform well in one of the two aspects, and concentrate on a su...

متن کامل

A 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 کامل

Moving 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 کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004