公开(公告)号：US10425443B2

公开(公告)日：2019-09-24

申请号：US15182331

申请日：2016-06-14

Applicant: Microsoft Technology Licensing, LLC.

Inventor： Royi Ronen ,  Hani Neuvirth-Telem ,  Shai Baruch Nahum ,  Yuri Gabaev ,  Oleg Yanovsky ,  Vlad Korsunsky ,  Tomer Teller ,  Hanan Shteingart

IPC: G06F12/14 ,  H04L29/06 ,  G06F21/56

Abstract: Detecting a volumetric attack on a computer network with fewer false positives and while also requiring fewer processing resources is provided. The systems and methods described herein use observations taken at the network level to observe network traffic to form a predictive model for future traffic. When the network's future traffic sufficiently exceeds the predictive model, the monitoring systems and methods will indicate to the network to take security measures. The traffic to the network may be observed in subsets, corresponding to various groupings of sources, destinations, and protocols so that security measures may be targeted to that subset without affecting other machines in the network.

公开(公告)号：US20170359372A1

公开(公告)日：2017-12-14

申请号：US15182331

申请日：2016-06-14

Applicant: Microsoft Technology Licensing, LLC.

Inventor： Royi Ronen ,  Hani Neuvirth-Telem ,  Shai Baruch Nahum ,  Yuri Gabaev ,  Oleg Yanovsky ,  Vlad Korsunsky ,  Tomer Teller ,  Hanan Shteingart

IPC: H04L29/06

Abstract: Detecting a volumetric attack on a computer network with fewer false positives and while also requiring fewer processing resources is provided. The systems and methods described herein use observations taken at the network level to observe network traffic to form a predictive model for future traffic. When the network's future traffic sufficiently exceeds the predictive model, the monitoring systems and methods will indicate to the network to take security measures. The traffic to the network may be observed in subsets, corresponding to various groupings of sources, destinations, and protocols so that security measures may be targeted to that subset without affecting other machines in the network.