Python for Cyber Security
Python for Cyber Security
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Topic 4.3 of Network Traffic Analysis with Python
The STD code: an IP address's range reveals an approximate location the same way an old landline number's area code did. Correlating every source in a capture with a place turns a bare list of addresses into a map of where traffic is actually coming from.
By the end of this topic, you will
Quadrant 1 · e-Tutorial
Video lesson
Quadrant 2 · e-Content
Quadrant 3 · Web Resources
Quadrant 4 · Self-Assessment
Network Traffic Analysis with Python
Twenty questions on Unit 4, Network Traffic Analysis with Python. Questions cover packet captures and DPKT parsing, GeoIP correlation, denial-of-service traffic families including volumetric floods and IRC-based command and control, sliding-window flood detection, and signature-based and anomaly-based intrusion detection rules.
Python for Cyber Security: Complete Assessment
Comprehensive 100-question assessment covering all five units of Python for Cyber Security: Python and networking foundations, building security tools, digital forensics, network traffic analysis, and integrating cyber security tools, twenty questions pulled from every unit.