Machine and Deep Learning in Cybersecurity
This module focuses on applying machine learning and deep learning techniques to cybersecurity challenges such as anomaly and malware detection
Detection and classification of cybersecurity topcs with machine learning
This module focuses on applying machine learning and deep learning techniques to cybersecurity challenges such as anomaly and malware detection, fraud detection, and spam classification. Students will explore various machine learning algorithms, analyze their performance, and design appropriate models for specific cybersecurity tasks.
Module Information
As part of this module, students will explore various machine learning algorithms, analyze their performance, and design appropriate models for specific cybersecurity tasks. The module also covers explainability issues in AI-driven cybersecurity, alongside hands-on labs using Python and popular libraries like Scikit-learn, TensorFlow, and PyTorch.
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 focuses on applying machine learning and deep learning techniques to cybersecurity challenges such as anomaly and malware detection, fraud detection, and spam classification. Toward this goal the module employs periodic quizzes and assignments.
Time commitment:
- Online activities: 14 hours
- In-person activities: 14 hours
- Self-learning: 28 hours
- Individual, team and guided projects and activities: 69 hours
- Total: 125 hours
Credit points: 5 ECTS
Grading:
- Lecture Quizzes: 10%
- Assignments: 40%
- Exam: 50%
Subjects covered
Ethical hacking fundamentals (history & main concepts)
Operating systems vulnerabilities & attack vectors
Network vulnerabilities & attack vectors (IT, IoT, OT)
Web vulnerabilities & attack vectors
Cloud vulnerabilities & attack vectors
Pentesting methodologies
Footprinting and reconnaissance
Vulnerability analysis and exploitation tools
Ethics and legislation in ethical hacking
Ethical Hacking certification roadmap
Apply nowLearning objectives
Identify threats and attack methodologies during the develop of and ethical Hacking audit.
Analyse the security posture of systems by identifying vulnerabilities and distinguishing between different types of cyber-attacks.
Manage the technical and executive reports for taking decisions level.
Manage ethical hacking audit processes by selecting specific attacks according to the results we need to obtain.
Plann and manage the ethical hacking process.
Elaborate results reports after Ethical Hacking process, for the taking decision level
Apply nowModule leaders
Alexandru Văduva is a Lecturer in the Department of Computer Science and Engineering at the National University of Science and Technology POLITEHNICA Bucharest (UNSTPB). He obtained his Ph.D. in 2020, with a specialization in Security in Automotive Linux, focusing on the security of vehicle internal architectures.
His research interests include automotive cybersecurity, host intrusion detection systems, source code and binary analysis, embedded devices, and operating systems. He has contributed to national and international research projects such as POCU/993/6/13-153178: Research Performance and Digital Twins for Complex Infrastructures and Urban Ecosystems.
He has professional experience in the automotive and telecommunications industries, having worked for companies such as Luxoft, Enea, Mentor Graphics, and Siemens. These roles enabled him to stay closely connected with cutting-edge technologies and to collaborate with major automotive OEMs.
His teaching portfolio includes courses on operating systems, computer networks, microcontroller design, computer engineering, embedded systems, and embedded systems security. He is the author of over 15 scientific articles presented at national and international conferences, two books, and is actively involved in open-source initiatives focused on standardizing secure Linux integration in automotive environments.
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Our digital world is under constant attack. Master the advanced skills to defend critical data and infrastructure. Become a sought-after expert in one of today’s most vital and in-demand career fields.
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