Automation of Security Tasks and Data Analytics

Automate cybersecurity tasks using Python, enhancing efficiency in threat detection and analysis.

Key Details

This module is delivered in hybrid format, as a combination of online, in-person and self-learning activities. The module uses innovative hybrid learning methods that combine live (synchronous) and self-paced (asynchronous) activities, with particular focus on practical activities and real-world scenarios connected to cybersecurity. Expert tutors guide students through the material, ensuring a comprehensive learning experience.

This module aims to equip participants with the skills and knowledge to develop, implement, and manage automated cybersecurity workflows using Python and related tools. Toward this goal the module employs periodic quizzes, in-class participation and assignments.

Time commitment:

• Online activities: 7 hours
• In-person activities: 7 hours
• Self-learning: 28 hours
• Individual, team and guided projects and activities: 58 hours
• Total: 100 hours

Credit points: 4 ECTS

Grading:

• Lecture quizzes: 10%
• Seminar work: 10%
• Assignments: 30%
• Exam: 50% (scenario essay, practical exam)

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Subjects covered

Introduction to Python and Cybersecurity

Automating Reconnaissance

Threat Intelligence Fundamentals

Data Analysis and Visualization for Threat Intelligence

Automating Log Analysis and Monitoring

Network Traffic Analysis

Incident Detection and Response Automation

Threat Hunting Automation

Vulnerability Management and Exploitation

Advanced Web Scraping for Threat Intelligence

Automating AI Models for Threat Intelligence

Integrating and Automating Security Tools

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Learning objectives

Implement Python scripts to perform reconnaissance activities, open-source intelligence gathering, and network scanning using appropriate libraries.

Develop automated scripts for threat intelligence collection, data analysis, visualization, and log monitoring applying Python data manipulation libraries.

Create scripts for automating incident detection, response workflows, vulnerability assessments, and exploitation tasks, using system and network libraries.

Design advanced web scraping and data extraction routines, incorporating browser automation tools, while respecting legal and ethical considerations.

Build and configure integrated automation solutions using Docker, Ansible, and other orchestration tools to improve security operations.

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Module leaders

Bogdan-Costel MOCANU is an Assistant Professor at the Faculty of Automatic Control and Computers, Department of Computer and Information Technology of the National University of Science and Technology POLITEHNICA Bucharest. He earned his Ph.D. in 2019 and continuously demonstrated remarkable growth and improvement in his expertise and contributions in multiple research areas, including Peer-to-Peer systems, Distributed systems, Cloud computing, Big Data, Real-time scheduling, and Information security.

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