Python for Cyber Security
Python for Cyber Security
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Topic 4.6 of Network Traffic Analysis with Python
The turnstile: catching an attack while it happens means watching the rate of traffic, not the running total. A sliding window built from a deque counts only the last few seconds, and the GitHub attack shows exactly this kind of detector surviving a record-breaking flood.
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.