Botnet early detection using hybrid hidden markov model algorithm
US8307459B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 17, 2010 |
| Grant date | Nov 6, 2012 |
| Priority date | — |
| Expiry date | Jan 4, 2031 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L2463/144
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
A botnet detection system is provided. A bursty feature extractor receives an Internet Relay Chat (IRC) packet value from a detection object network, and determines a bursty feature accordingly. A Hybrid Hidden Markov Model (HHMM) parameter estimator determines probability parameters for a Hybrid Hidden Markov Model according to the bursty feature. A traffic profile generator establishes a probability sequential model for the Hybrid Hidden Markov Model according to the probability parameters and pre-defined network traffic categories. A dubious state detector determines a traffic state corresponding to a network relaying the IRC packet in response to reception of a new IRC packet, determines whether the IRC packet flow of the object network is dubious by applying the bursty feature to the probability sequential model for the Hybrid Hidden Markov Model, and generates a warning signal when the IRC packet flow is regarded as having a dubious traffic state.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.