DataScientest x Michelin

Intrusion Detection & SOC

Bootcamp (4 days)

Prerequisites :

Good knowledge of networks and systems (Windows & Linux)

Good knowledge of IT security

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Upcoming Dates

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Training content

Prerequisites for setting up a logging system
Architecture and design of a logging system
Introduction to security incident detection

Definition and terminology
The objectives of an IDS/IPS
How an IDS/IPS works
NIDS/NIPS in a network architecture
Different IDS/IPS solutions
NIDS/NIPS rules

Definition and terminology
The objectives of a SIEM
How a SIEM works
SIEM rules (Alert, Sigma, etc.)
SIEM in a network architecture
Different SIEM solutions
Case study of a SIEM solution

Definition and terminology
The objectives of an EDR
How an EDR works
EDR rules (Alert, Yara, etc.)
Different EDR solutions
Case study of an EDR solution

Definition and terminology
The objectives of a Honeypot
How a Honeypot works
Different Honeypot solutions
Case study of a Honeypot solution

Objectives of Wireshark
How Wireshark works
Customizing menus
Analysis of malicious traffic

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Data scientist’s goals

The Data Scientist develops complex analysis models to extract information from databases.
These can be used to predict consumer behavior or to identify business or operational risks.

Identify

Identify and understand analysis and detection techniques.

Discover

Discover advanced attack techniques.

Acquire

Acquire the knowledge to deploy intrusion detection tools.

Prevent

Implement prevention solutions.

Understand

Understand the concepts and environment of a SOC.

Key figures of the training

95,6%

Success rate

93,05%

Completion rate

99%

Satisfaction rate

Intrusion Detection & SOC

Training content