Distributed detection/localization of change-points in high-dimensional network traffic data
نویسندگان
چکیده
منابع مشابه
Distributed detection/localization of change-points in high-dimensional network traffic data
We propose a novel approach for distributed statistical detection of change-points in highvolume network traffic. We consider more specifically the task of detecting and identifying the targets of Distributed Denial of Service (DDoS) attacks. The proposed algorithm, called DTopRank, performs distributed network anomaly detection by aggregating the partial information gathered in a set of networ...
متن کاملDetection and Localization of Change - Points in High - Dimensional Network Traffic Data
We propose a novel and efficient method, that we shall call TopRank in the following paper, for detecting change-points in high-dimensional data. This issue is of growing concern to the network security community since network anomalies such as Denial of Service (DoS) attacks lead to changes in Internet traffic. Our method consists of a data reduction stage based on record filtering, followed b...
متن کاملanalysis of power in the network society
اندیشمندان و صاحب نظران علوم اجتماعی بر این باورند که مرحله تازه ای در تاریخ جوامع بشری اغاز شده است. ویژگیهای این جامعه نو را می توان پدیده هایی از جمله اقتصاد اطلاعاتی جهانی ، هندسه متغیر شبکه ای، فرهنگ مجاز واقعی ، توسعه حیرت انگیز فناوری های دیجیتال، خدمات پیوسته و نیز فشردگی زمان و مکان برشمرد. از سوی دیگر قدرت به عنوان موضوع اصلی علم سیاست جایگاه مهمی در روابط انسانی دارد، قدرت و بازتولید...
15 صفحه اولNetwork performance implications of multi- dimensional variability in data traffic
WWW traffic will dominate network traffic for the foreseeable future. Accurate predictions of network performance can only be achieved if network models reflect WWW traffic statistics. Through analysis of usage logs at a range of caches we confirm that WWW traffic is not a Poisson arrival process, and that it shows significant levels of self-similarity. We show for the first time that the self-...
متن کاملApproximated Clustering of Distributed High-Dimensional Data
In many modern application ranges high-dimensional feature vectors are used to model complex real-world objects. Often these objects reside on different local sites. In this paper, we present a general approach for extracting knowledge out of distributed data sets without transmitting all data from the local clients to a server site. In order to keep the transmission cost low, we first determin...
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: Statistics and Computing
سال: 2011
ISSN: 0960-3174,1573-1375
DOI: 10.1007/s11222-011-9240-5