LIVE TRAINING
SAVE THE DATE: June 7th, 2023 1 PM ET
LIVE TRAINING: Introduction to PYTHON for ProgrammingÂ
October 12th @12 PM EST
Price: $147
Regular price $210, discounted 10%
4 hour immersive session
Hands-on training with Q&A
Recording available on-demand
Certification of Completion
30% Discount Ends in:
Subscribe and get an additional 10% to 35% off ALL live training session
Pricing: $99
Price: $75 with Annual Ai+ Premium Subscription
- Purchase Annual Premium Subscription and this live training for $75
Includes:
- Access to all on-demand Ai+ Sessions (more than 100)
- Previous ODSC Conference recordings
- $200 credit for upcoming ODSC Conferences
- Machine Learning Certification
- Deep Learning Bootcamp
Price: $99Â (price already includes 30% discount)
- Purchase this ticket by 06/07/2023 to redeem 30% discount
Includes:
- Hands-on training with QA
- Certification of Completion
30% Discount Ends in:
Meet Your Instructor
Howard Poston
Howard Poston is a cybersecurity researcher with a background in blockchain, cryptography and malware analysis. He has a master’s degree in Cyber Operations from the Air Force Institute of Technology and two years of experience in cybersecurity research and development at Sandia National Labs. He currently works as a freelance consultant providing training and content creation for cyber and blockchain security.
Course Overview
What’s the plan?Â
Network traffic data can be a rich source of information for cybersecurity and IT management. Malware is delivered and performs command and control communications over the network, and software sends and receives a wealth of data over the network.
The course provides an introduction to analyzing network traffic data with Python. Python is an ideal tool for this task because it is freely available and has numerous modules that support network traffic analysis, data science, and other tasks.
This course will build familiarity and skills in network traffic analysis via a series of hands-on exercises and examples. By examining, modifying, and building custom scripts for network traffic analysis, you’ll how to access and select network traffic data, analyze it, and interpret the results.
Learning Objectives
Understand how to analyze network traffic, including what features to extract and how to analyze them
Use Python and Scapy to analyze network traffic in packet capture files and live captures
Develop custom Python scripts to answer questions with network traffic data
Why Enroll?
Learn about LLMs, one of the hottest areas in AI today
Learn how ChatGPT was built / what makes it possible
Learn which use cases LLMs could solve
Learn how LLMs are being used across finance, healthcare, legal, and education
Learn practical advice on using LLMs in production
Learning Objectives
What are the benefits of LLM?
What are the challenges?
What tasks can large language models perform?
Applying LLMs to use cases and apps across different industries (including the future possibilities)
Case study in finance
Case study in healthcare
Case study in legal
Case study in education
Course Outline
What’s the plan?Â
Matt Harrison has been working with Python and data since 2000. He has a computer science degree from Stanford. He has worked at many amazing companies, created cool products, wrote a couple books, and taught thousands Python and Data Science. Currently, he is working as a corporate trainer, author, and consultant through his company Metasnake, which provides consulting and teaches corporations how to be effective with Python and data science.
Course Overview
Python is a powerful tools that XXX
Join the live session with Howard Poston
SAVE 30%Course Outline
Module 1:
Getting Started with Network Traffic Analysis in Python
- Â Setting up the development environment (libraries, packet capture files, etc.)
- Â Looking at a packet capture in Wireshark (provides better visualizations)
- Getting started with Scapy
- Loading a packet capture into Scapy
- Viewing capture contents
- Accessing fields of a traffic capture
Module 2:
Feature Selection for Network Traffic Analysis
- Â Explore the structure of a network packet in Wireshark/Scapy
- Identify the fields that would be useful/useless for network traffic analysis (for example, server ports are useful, while client ports are not since they are random)
- Write code that extracts features of interest for further analysis
- Â Perform basic analysis of traffic (i.e. clustering, etc.) using extracted features
Module 3:
Level Traffic Analysis
- Discuss the concept of network flows (i.e. high-level header data with no packet contents)
- Write code to convert a packet capture or live traffic capture to flow data
- Generate a network map with flow data
- Classify systems based on role in the organization (end-user systems, various types of servers, etc.)
- Identify potential data exfiltration with flow data
- Identify anomalous sessions for future analysis (i.e. differentiating a successful login attempt from a failed one, etc.)
Module 4:
Packet-Level Traffic Analysis
- Discuss the pros and cons of packet-level analysis
- Write code to extract packet payloads, HTTP headers, and other features of interest
- Extract credentials and other sensitive data from unencrypted communications
- Identify encoded and encrypted data within packet contents
- Extract potential indicators of compromise (IoCs) to identify malicious traffic
- Carve files from network traffic for further analysis
🗝️Key Details
DATE
TIME:
DURATION:
LEVEL:
June 7th, 2023
1PM ET, 10 AM PT
3 HOURS
BEGINNER
Prerequisites
- Knowledge of Python, Network Traffic Analysis, and Data Science is helpful but not required
- Python (and various Python libraries), Wireshark
Upcoming Live Training
XXth
XXX
XXX.