Invention Grant
- Patent Title: In-situ trainable intrusion detection system
- Patent Title (中): 现场可入侵入侵检测系统
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Application No.: US14468000Application Date: 2014-08-25
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Publication No.: US09497204B2Publication Date: 2016-11-15
- Inventor: Christopher T. Symons , Justin M. Beaver , Rob Gillen , Thomas E. Potok
- Applicant: UT Battelle, LLC
- Applicant Address: US TN Oak Ridge
- Assignee: UT-Battelle, LLC
- Current Assignee: UT-Battelle, LLC
- Current Assignee Address: US TN Oak Ridge
- Agency: Brinks Gilson & Lione
- Main IPC: H04L29/06
- IPC: H04L29/06 ; G06N99/00 ; G06N5/04

Abstract:
A computer implemented method detects intrusions using a computer by analyzing network traffic. The method includes a semi-supervised learning module connected to a network node. The learning module uses labeled and unlabeled data to train a semi-supervised machine learning sensor. The method records events that include a feature set made up of unauthorized intrusions and benign computer requests. The method identifies at least some of the benign computer requests that occur during the recording of the events while treating the remainder of the data as unlabeled. The method trains the semi-supervised learning module at the network node in-situ, such that the semi-supervised learning modules may identify malicious traffic without relying on specific rules, signatures, or anomaly detection.
Public/Granted literature
- US20150067857A1 IN-SITU TRAINABLE INTRUSION DETECTION SYSTEM Public/Granted day:2015-03-05
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