BOTNET EARLY DETECTION USING HYBRID HIDDEN MARKOV MODEL ALGORITHM

Patent №

US 8,307,459

Granted

2012-11-06

Filed 2010

Owner

NATIONAL TAIWAN UNIVERSITY OF SCIENCE & TECHNOLOGY

Lab

AI components

3

ml · vision · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

12726272

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.

AI classification

Machine learning1.00
AI hardware0.98
Vision0.73
Knowledge representation0.17
Planning0.05
Natural language0.00
Speech0.00
Evolutionary computation0.00

Ownership

NATIONAL TAIWAN UNIVERSITY OF SCIENCE & TECHNOLOGY

assignment · 241120167

Assignors

LEE, HAHN-MING, MAO, CHING-HAO, CHEN, YU-JIE, WANG, YI-HSUN, YEH, JEROME, CHEN, TSU-HAN

On an employer assignment, the assignors are typically the inventors.

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