Showing 5 open source projects for "artificial"

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    RogueKiller

    RogueKiller

    The next generation virus killer. Remove unknown malware

    ...Thanks to its powerful engine RogueKiller is able to find known and unknown malware, of all kind. Search and clean viruses, ransomware, trojans and other malware. Powered with innovative Artificial Intelligence and Cloud signatures engine, RogueKiller is the best virus removal tool. Try our free virus cleaner now for free ! RogueKiller antimalware software is shipped with state-of-the-art malware protection. The real time protection stops infected programs before they execute. Don't let malicious software setup, stop them before they do harmful actions! ...
    Downloads: 35 This Week
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  • 2
    Malware Analysis Network in Taiwan <Man in Taiwan, MiT> Welcome to contact us (TonTon@TWMAN.ORG) if you are interested in collaborating with us. This project is open source and distributed under the GNU General Public License version 3. Please feel free to add to or modify this source and propose changes or new converters. Developer & Copyrighted by : TonTon Hsien-De Huang Prompter: Jazz Yao-Tsung Wang, Figaro Chen-Ho Yang | Logo Desinger:Temaki Guo Community on...
    Downloads: 0 This Week
    Last Update:
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  • 3

    Virtual Botmaster

    Simulate Botnet NetFlow traffic for research analysis

    Simulate Botnet NetFlow traffic for research analysis
    Downloads: 0 This Week
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  • 4

    Botnet Detectors Comparer

    Compares botnet detection methods

    Compares botnet detection methods by computing the error metrics by reading the labels on a NetFlow file. The original NetFlow should have a new column for the ground-truth label, and a new column with the prediction label for each botnet detection method. This program computes all the error metrics (TPR, TNR, FPR, FNR, Precision, Accuracy, ErrorRate, FMeasure1, FMeasure2, FMeasure0.5) and output the comparison results. It also ouputs a png plot. The program can compare in a...
    Downloads: 0 This Week
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  • 5
    A packet dissector driven by machine learning algorithms. You train it to recognize specific types of packets by showing it examples and counterexamples of some packet type, and it will figure out which bits in the packet define it as the type you seek.
    Downloads: 0 This Week
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