Large-scale IP network data analysis for anomalies detection thanks to SVM
نویسندگان
چکیده
منابع مشابه
Visual analysis of large-scale network anomalies
The amount of information flowing across communication networks has rapidly increased. The highly dynamic and complex networks, represented as large graphs, make the analysis of such networks increasingly challenging. In this paper, we provide a brief overview of several useful visualization techniques for the analysis of spatiotemporal anomalies in large-scale networks. We make use of communit...
متن کاملLarge Scale Experiments Data Analysis for Estimation of Hydrodynamic Force Coefficients Part 1: Time Domain Analysis
This paper describes various time-domain methods useful for analyzing the experimental data obtained from a circular cylinder force in terms of both wave and current for estimation of the drag and inertia coefficients applicable to the Morison’s equation. An additional approach, weighted least squares method is also introduced. A set of data obtained from experiments on heavily roughened circul...
متن کاملConfigurable IP-space maps for large-scale, multi-source network data visual analysis and correlation
The need to scale visualization of cyber (IP-space) data sets and analytic results as well as to support a variety of data sources and missions have proved challenging requirements for the development of a cyber common operating picture. Typical methods of visualizing IP-space data require unreliable domain conversions such as IP geolocation, network topology that is difficult to discover, or d...
متن کاملLarge Scale Experiments Data Analysis for Estimation of Hydrodynamic Force Coefficients
This paper describes the various frequency domain methods which may be used to analyze experiments data on the force experienced by a circular cylinder in wave and current to estimate drag and inertia coefficients for use in Morison’s equation. An additional approach, system identification techniques (SIT) is also introduced. A set of data obtained from experiments on heavily roughened circular...
متن کاملSequential Learning with LS-SVM for Large-Scale Data Sets
We present a subspace-based variant of LS-SVMs (i.e. regularization networks) that sequentially processes the data and is hence especially suited for online learning tasks. The algorithm works by selecting from the data set a small subset of basis functions that is subsequently used to approximate the full kernel on arbitrary points. This subset is identified online from the data stream. We imp...
متن کاملذخیره 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: International Journal of Design & Nature and Ecodynamics
سال: 2016
ISSN: 1755-7437,1755-7445
DOI: 10.2495/dne-v11-n3-376-386