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MaliciousPivotingDetection

Python application to detect and analyze pivoting activities given network flows from NProbe. It relies on the following IEEE paper: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8078189&tag=1

The application takes as input: parameters.py, configuration file MaliciousIP.json, list of malicious IP suspected of reconnaissance activities or anomalous data transfer. Input, folder with Nprobe data, linked in folders by /Year/Month/Day/Hours/minutes.tar.gz

The application creates as output: GraphImages, every graph image created, vector image JSON outputs, containing json data

Configuration: ValidCIDR, list of valid CIDR, subnet considered ConsiderExternal, True if we want to consider also flows coming from IPs outside the valid CIDR norm_ports, ports whitelist maliciousIP_filename, filename of JSON input file OnlyPivots, True to show only pivoting activities or False to show every flow. filter_ports, ports to filter FilterPorts, True if we eant to filter the previous configuration value ports. ByteMin, minimum byte exchange to consider flow part of pivoting activities PivotLengthMin & PivotLengthMax, nodes involved to consider pivoting activities FlowDurationMin, minimum duration to consider flow part of pivoting activities Year, Month, Day, HourStart, MinuteStart, HourEnd, MinuteEnd, to specify time interval to check

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Python application to detect and analyze pivoting activities given network flows from NProbe

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