Cybersecurity

Become an indispensable expert in defending digital infrastructures!

KBS Academy offers cybersecurity training tailored to the current needs of businesses and professionals. Our courses cover system security principles, risk management, data protection, as well as the latest practices and tools to counter cyber threats. Whether you’re a beginner or an expert, our training will help you enhance your skills to effectively protect IT infrastructures and secure digital environments.

Protect your systems against tomorrow’s threats—enroll today in our cybersecurity training and become an indispensable expert in defending digital infrastructures!

Formation Cybersecurity

Objectifs Spécifiques : A la fin de cette formation, (1) Vous saurez à quoi ressemble un véritable projet ML, (2) Vous apprendrez les algorithmes les plus connus du ML, (3) Vous apprendrez à implémenter plusieurs projets d’apprentissage automatique, (4) Vous serez en mesure d’inclure ces études de cas dans votre CV, (5) Vous serez en mesure de mieux vous vendre en tant que spécialiste ML, (6) Vous vous sentirez en confiance lors d’un entretien en ML.

Module Descriptions:

Module 01: General Introduction to Cybersecurity

Context of cybersecurity: current threats, challenges, and key definitions.
Types of threats and attack vectors.
Main legislative frameworks and security standards.

Module 02: System Hardening

Linux Hardening:
- Basic configuration: updates, permission management, network configurations.
- Securing services and deploying access control policies.
- Monitoring and auditing logs, using tools like SELinux and AppArmor.
Windows Hardening:
- Local security policy and Group Policy Objects (GPO).
- Configuring firewalls, encryption, and access management.
- Hardening tools and advanced configurations like BitLocker and AppLocker.

Module 03: Digital Forensics

Basic concepts: identification, preservation, collection, and analysis of evidence.
Key forensic tools for Windows and Linux.
Analysis of artifacts and maintaining the chain of custody.
Advanced techniques: memory analysis, event logs, and network analysis.

Module 04: Cybersecurity Crisis Management

Identifying and activating the incident response plan.
Coordinating security teams and communication during a crisis.
Business continuity and disaster recovery planning (BCP/DRP).
Incident simulation exercises and lessons learned.

Module 05: Security Management According to ISO 27001

Introduction to ISO 27001 requirements and Information Security Management Systems (ISMS).
Structuring and implementing a security policy.
Documentation management, compliance audits, and handling non-conformities.
PDCA cycle (Plan-Do-Check-Act) for continuous improvement.

Module 06: Risk Management with the EBIOS Method

Overview of the EBIOS method and its steps.
Identifying and assessing risks: threat mapping, vulnerabilities, impacts.
Risk analysis and treatment using risk matrices.
Developing and validating the risk treatment plan.

Module 07: Role of the Cybersecurity Consultant

Understanding the role and responsibilities of a cybersecurity consultant.
Techniques for client communication and needs assessment.
Structuring recommendations and presenting deliverables.
Professional ethics and confidentiality.

Module 08: Python for Cybersecurity

Python - Introduction:
- Python basics: syntax, control structures, module and package management.
- Data manipulation, file handling, and task automation.
- Using standard libraries useful for security (e.g., os, sys, socket)
Python for Pentesting
- Using Python for port scans, packet analysis, and vulnerability detection
- Developing scripts for penetration testing
- Advanced libraries (Scapy, Requests, Nmap) and automating pentesting tasks

Module 09: IT Network Overview

Fundamentals of Networking (TCP/IP, OSI, Ethernet)
Routing, Switching, and Network Equipment Configurations
Network Security: Firewalls, VPN, and Secure Protocols (SSL/TLS)
Essential Network Commands and Traffic Analysis

Module 10: Security Operations Center (SOC)

Role and Functioning of a SOC in an Organization
Threat Monitoring and Log Analysis
Setting Up Alerts and Incident Responses
Tools Used in SOCs: SIEM, IDS/IPS, EDR

Module 11: Advanced Hacking Techniques

Advanced Concepts in Penetration Testing: Reconnaissance, Scanning, Exploitation
Techniques of Pivoting, Privilege Escalation, and Lateral Movements
Analysis of Vulnerabilities Specific to Web Applications and Networks
Advanced Pentesting Tools (Metasploit, Burp Suite, Cobalt Strike)

Domaine :

Intelligence Artificielle, Développement, Data

Niveau :

Débutant et Intermédiaire

Public cible

Profil des Participants : Les passionnés de science des données et intelligence artificielle et toute personne ayant des connaissances en intelligence artificielle et en Python.
Prérequis : Notions de base des mathématiques et statistiques, et fondamentaux du Language de programmation Python.

Durée de la Formation

Nombre de Modules : Trois modules.
Durée Totale Estimée : 3 ou 4 jours.

Méthodologie Pédagogique

La formation combinera entre deux méthodes pédagogiques :

La méthode affirmative pour expliquer les fondamentaux du Machine Learning.
La méthode applicative / démonstrative pour réaliser des exercices, des études de cas et des cas pratiques avec des projets.

Evaluation et Certification

Modalités d’Évaluation : Quizz, tests, examen final.
Critères de Validation : Score minimum de 80 %.
Type de Certification : Certificat de participation, attestation de compétences

Matériel et Ressources

Outils et Logiciels Nécessaires : Python, Anaconda, Jupyter notebook.

Environnement Lab

Dans cette formation, les apprenants utiliseront Jupyter Notebook pour réaliser leurs travaux.