Presentation

The main characteristic of the master's degree, which makes it unique, is that it uses Data Science and Machine Learning models to study in depth the most current Cybersecurity incidents, deducing from this analysis the most introduced Protection Architectures in the sector.

We train future Cybersecurity Architects in the most demanded protection techniques, such as Zero Trust Architectures, applying Data Science models in their design, in validating the robustness of architectures and in identifying the attacks that cause the most losses. are causing in the industry.

We are organized into five modules. You can take them in one year or several. The two initial modules are Introduction to Cybersecurity and Python programming focused on data. The following three modules focus, on the one hand, on the architectural and technological aspects of Cybersecurity (NIST 800 Model) and on the analysis models of the most current attack techniques such as Cyber ​​Kill Chain and MITER ATT&CK. To this we add the practical application of Data Science and Machine Learning (Python fundamentally) to identify anomalies in the behavior of systems and people, which allow us to react quickly to an attack.

As you finish each of the modules, you obtain the corresponding Higher University Degree. At the end of the five modules and the Final Master's Project, the Master's degree is issued. You can take it whether you have a university degree or if you have experience in the world of Computer Science.

We are in the URJC building in the Plaza de Manuel Becerra in Madrid. Given the current situation, for the 20/21 academic year, classes can be followed in person or via streaming. Let's broadcast all classes!!!

Objectives

Training in the main protection techniques against attacks and threats in operating systems, networks, application software, Web systems, databases and machine learning.

Competences

GENERAL COMPETENCIES

• Ability to search for specific information related to the different subjects of the Master from all available sources.
• Ability to propose and develop reports.
• Ability to interpret technical documents.
• Ability to work in a team, in an interdisciplinary environment.
• Resource management: organization and ability to set priorities at work.
• Flexibility to adapt during the development of a project, ability to rethink.
• Critical reasoning: analysis, synthesis and evaluation of different alternatives.
• Ability for effective written and oral communication.
• Information management: collection of information, organization, etc.
• Responsibility and capacity for self-learning.

 SPECIFIC COMPETENCES

• The student will learn how the various encryption algorithms and techniques work and their benefits and limitations.
• You will learn the various systems and types of authentication, as well as the difference between authentication and authorization.
• The student will be trained to assess potential risks and recommend ways to reduce it.
• The student will get to know the Python programming language, getting a general vision of the language and managing to build complex programs.
• You will become familiar with the fundamental concepts of the treatment of variables, the development of algorithms and their programming.
• The student will learn a comprehensive vision of cybersecurity technologies and techniques.
• You will learn new methods of encrypted data computing, network security and protocol design
• You will know the most effective Machine Learning techniques.
• You will learn the differences and compatibility between Octave and MATLAB.
• You will know the difference between graphic models and network models.
• You will know how to differentiate predictions on temporal data from other types of data.

In addition, the following will be guaranteed Basic skills:

• Possess and understand knowledge that provides a foundation or opportunity to be original in the development and/or application of ideas, often in a research context.
• That students know how to apply the knowledge acquired and their ability to solve problems in new or little-known environments within broader (or multidisciplinary) contexts related to their area of ​​study;
• That students are able to integrate knowledge and face the complexity of formulating judgments based on incomplete or limited information
• That students know how to communicate their conclusions –and the knowledge and ultimate reasons that support them– to specialized and non-specialized audiences in a clear and unambiguous way;
• That students have the learning skills that allow them to continue studying in a way that will be largely self-directed or autonomous.
• That students are able to establish the relevant interrelationships between the various disciplines that make up the Master.
• That students have oral and written communication skills in the dissemination of manufacturing and design knowledge.
• That they have the capacity for synthesis and analysis in the presentation of the contents.
• That students are able to apply critical judgment in the domain of generic and specific bibliography related to the field of related studies.