Intelligent Defense and Filtration Platform for Network Traffic

Mehrnoosh Monshizadeh (Inventor), Kimmo Hätönen (Inventor), Vikramajeet Khatri (Inventor)

    Research output: Patent

    Abstract

    Systems and methods for detecting and preventing cyber-attacks on communication networks provide a hybrid anomaly detection module (HADM) that uses a combination of linear algorithms and learning algorithms. The linear algorithms filter and extract distinctive attributes and features of the cyber-attacks and the learning algorithms use these attributes and features to identify new types of cyber-attacks. The learning algorithms, which may be algorithms that employ Artificial Neural Networks (ANN), Genetic Algorithm (GA), Extreme Learning Machines (ELM), Self-Organizing Map (SOM), Multi-Layer Perceptron (MLP), or Swarm intelligence (SI)and the like, have better detection accuracy when they are used along with linear algorithms, such as algorithms that employ Decision Tree,Support Vector Machine,or Fuzzy Ruleand the like. The use of linear algorithms in conjunction with learning algorithms allows the HADM to achieve improved cyber-attack detection over existing solutions.

    Original languageEnglish
    Patent numberWO2019129915
    IPCG06N 99/ 00 A I
    Priority date29/12/2017
    Publication statusSubmitted - 4 Jul 2019
    MoE publication typeH1 Granted patent

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