A bot traffic detection system detects scripted network traffic. The bot traffic detection system may use a one-sided unsupervised machine learning technique to estimate distributions for human, non-scripted traffic (clean distributions). The clean distributions may be dynamically updated based on the latest traffic patterns. To estimate the clean distributions the bot traffic detection system may identify, for a certain subset of network traffic, feature values of the certain subset of network traffic that do not include bot traffic (clean buckets). Using clean traffic may provide more robust and stable behavior that can be tracked over time. Using the clean distributions, the bot traffic detection system may generate a rules table that indicates a likelihood that network traffic with a given combination of feature values is scripted network traffic. The bot traffic detection system may apply the rules table in real time to identify scripted network traffic.


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    Title :

    METHOD AND APPARATUS TO DETECT SCRIPTED NETWORK TRAFFIC


    Contributors:
    HERLEY CORMAC (author) / TU FANG (author) / CAO CHENG (author) / PILLAI JAYADEV (author)

    Publication date :

    2021-12-23


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English



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