Semi-supervised multi-layered clustering model for 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

A Decision-Theoretic, Semi-Supervised Model for Intrusion Detection

In this paper, we develop a model of intrusion detection based on semi-supervised learning. This model attempts to fuse misuse detection with anomaly detection and to exploit strengths of both. In the process of developing this model, we examine different cost functions for the IDS domain and identify two key assumptions that are often implicitly employed in the IDS literature. We demonstrate t...

متن کامل

Model Selection for Semi-Supervised Clustering

Although there is a large and growing literature that tackles the semi-supervised clustering problem (i.e., using some labeled objects or cluster-guiding constraints like “must-link” or “cannot-link”), the evaluation of semi-supervised clustering approaches has rarely been discussed. The application of cross-validation techniques, for example, is far from straightforward in the semi-supervised ...

متن کامل

A Semi-Supervised Learning Algorithm for Multi-Layered Perceptrons

We address the issue of learning multi-layered perceptrons (MLPs) in a discriminative, inductive, multiclass, parametric, and semi-supervised fashion. We introduce a novel objective function that, when optimized, simultaneously encourages 1) accuracy on the labeled points, 2) respect for an underlying graph-represented manifold on all points, 3) smoothness via an entropic regularizer of the cla...

متن کامل

Semi-supervised Random Forest for Intrusion Detection Network

In order to protect valuable computer systems, network data needs to be analyzed and classified so that possible network intrusions can be detected. Machine learning techniques have been used to classify network data. For supervised machine learning methods, they can achieve high accuracy at classifying network data as normal or malicious, but they require the availability of fully labeled data...

متن کامل

Research of Immune Intrusion Detection Algorithm Based on Semi-supervised Clustering

Traditional immune intrusion detection algorithms need lots of labeled training data. However, it is difficult to obtain sufficient labeled data in real situation. In this paper we present a semi-supervised clustering based immune intrusion detection algorithm called SCIID, which can improve the quality of antibodies constantly and enhance the detection rate. Experimental results show that SCII...

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: Digital Communications and Networks

سال: 2018

ISSN: 2352-8648

DOI: 10.1016/j.dcan.2017.09.009