Supporting Intrusion Detection by Graph Clustering and Graph Drawing
نویسندگان
چکیده
This paper presents a description of a system supporting the detection of intrusions and network anomalies by analyzing and visualising traffic flows in computer networks. The system supervises the typical communication structure in the network and acts as an anomaly detection component of an Intrusion Detection System. Events are generated in the case of sudden variations of the traffic structure. Visualization of the traffic structure is used to help the security manager to gain an overview on the current traffic structure and to help identifying the type and the location of network anomalies.
منابع مشابه
Real-Time intrusion detection alert correlation and attack scenario extraction based on the prerequisite consequence approach
Alert correlation systems attempt to discover the relations among alerts produced by one or more intrusion detection systems to determine the attack scenarios and their main motivations. In this paper a new IDS alert correlation method is proposed that can be used to detect attack scenarios in real-time. The proposed method is based on a causal approach due to the strength of causal methods in ...
متن کاملFinding Community Base on Web Graph Clustering
Search Pointers organize the main part of the application on the Internet. However, because of Information management hardware, high volume of data and word similarities in different fields the most answers to the user s’ questions aren`t correct. So the web graph clustering and cluster placement in corresponding answers helps user to achieve his or her intended results. Community (web communit...
متن کاملDetecting Overlapping Communities in Social Networks using Deep Learning
In network analysis, a community is typically considered of as a group of nodes with a great density of edges among themselves and a low density of edges relative to other network parts. Detecting a community structure is important in any network analysis task, especially for revealing patterns between specified nodes. There is a variety of approaches presented in the literature for overlapping...
متن کاملGraph Clustering by Hierarchical Singular Value Decomposition with Selectable Range for Number of Clusters Members
Graphs have so many applications in real world problems. When we deal with huge volume of data, analyzing data is difficult or sometimes impossible. In big data problems, clustering data is a useful tool for data analysis. Singular value decomposition(SVD) is one of the best algorithms for clustering graph but we do not have any choice to select the number of clusters and the number of members ...
متن کاملA Graph-Based Clustering Approach to Identify Cell Populations in Single-Cell RNA Sequencing Data
Introduction: The emergence of single-cell RNA-sequencing (scRNA-seq) technology has provided new information about the structure of cells, and provided data with very high resolution of the expression of different genes for each cell at a single time. One of the main uses of scRNA-seq is data clustering based on expressed genes, which sometimes leads to the detection of rare cell populations. ...
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 2000