An Experimental Evaluation of Bayesian Classifiers Applied to Intrusion Detection

نویسندگان
چکیده

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

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Evaluation of Ensemble Classifiers for Intrusion Detection

One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are ana...

متن کامل

Experimental Evaluation of Qualitative Probability applied to Sensor Fusion and Intrusion Detection/Diagnosis

We experimentally analyze the accuracy of the System Z+ qualitative probability scheme of Goldszmidt and Pearl when used for diagnosis and information fusion. The Intrusion Detection System (IDS) fusion system Scyllarus, and its successor MIFD, use Z+ to assess the likelihood of various cyber attack events based on reports from IDSes. Z+ provides an order of magnitude approximation of conventio...

متن کامل

Bayesian Networks Classifiers Applied to Documents

This paper discusses the use of the bayesian network model for a classification problem related to the document image understanding field. Our application is focused on logical labeling in documents, which consists in assigning logical labels to text blocks. The objective is to map a set of logical tags, composing the document logical structure, to the physical text components. We build a bayes...

متن کامل

From Feature Selection to Building of Bayesian Classifiers: A Network Intrusion Detection Perspective

Problem statement: Implementing a single or multiple classifiers that involve a Bayesian Network (BN) is a rising research interest in network intrusion detection domain. Approach: However, little attention has been given to evaluate the performance of BN classifiers before they could be implemented in a real system. In this research, we proposed a novel approach to select important features by...

متن کامل

A Theoretical and Experimental Evaluation of Augmented Bayesian Classifiers

Naive Bayes is a simple Bayesian network classifier with strong independence assumptions among features. This classifier despite its strong independence assumptions, often performs well in practice. It is believed that relaxing the independence assumptions of naive Bayes may improve the performance of the resulting structure. Augmented Bayesian Classifiers relax the independence assumptions of ...

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

ژورنال

عنوان ژورنال: Indian Journal of Science and Technology

سال: 2016

ISSN: 0974-5645,0974-6846

DOI: 10.17485/ijst/2016/v9i12/86291