Educational guide | ||||||||||||||||||||||||||||||||||||||||
IDENTIFYING DATA | 2019_20 | |||||||||||||||||||||||||||||||||||||||
Subject | CURRENT TRENDS AND EMERGING THREATS IN CYBERSECURITY | Code | 01733112 | |||||||||||||||||||||||||||||||||||||
Study programme |
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Descriptors | Credit. | Type | Year | Period | ||||||||||||||||||||||||||||||||||||
6 | Optional | Second | First |
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Language |
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Prerequisites | ||||||||||||||||||||||||||||||||||||||||
Department | MATEMATICAS |
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Coordinador |
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amunc@unileon.es ncasg@unileon.es asuac@unileon.es |
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Lecturers |
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Web | http:// | |||||||||||||||||||||||||||||||||||||||
General description | ||||||||||||||||||||||||||||||||||||||||
Tribunales de RevisiĆ³n |
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Competencies |
Type A | Code | Competences Specific |
A17093 | ||
Type B | Code | Competences Transversal |
B5220 | ||
B5221 | ||
B5222 | ||
B5223 | ||
B5224 | ||
B5225 | ||
Type C | Code | Competences Nuclear |
C1 | ||
C2 | ||
C3 | ||
C4 | ||
C5 |
Learning aims |
Competences | |||
To Know about the current trends in Cybersecurity. | A17093 |
B5224 B5225 |
C1 C2 C4 C5 |
To be able to communicate their conclusions. | B5220 B5221 B5222 B5223 |
C3 |
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To know and develop Python algorithms | A17093 |
B5223 B5224 B5225 |
C1 C2 C4 C5 |
To identify when a problem can be solve using Machine Learning techniques | A17093 |
B5223 B5224 B5225 |
C1 C2 C4 C5 |
To know the basic models of Machine learning and their mathematical foundations | A17093 |
B5224 B5225 |
C1 C2 C4 C5 |
To implement the basic models in Python and to be able to use the corresponding libraries | A17093 |
B5223 B5224 B5225 |
C1 C2 C4 C5 |
To know and know how to use the main metrics for the model selection | A17093 |
B5223 B5224 B5225 |
C1 C2 C4 C5 |
To identify settings where Big Data can be applied. | A17093 |
B5223 B5224 B5225 |
C1 C2 C4 C5 |
To know the basics about Blockchain technology and its main applications | A17093 |
B5224 B5225 |
C1 C2 C4 C5 |
Know the Scientific method. Ability to find information and relevant references and to write scientific papers. Organize and prepare scientific conferences | |||
Know the legislation regarding intellectual property, research ethics, patents and utility models. Transfer of research results to companies, innovation |
Contents |
Topic | Sub-topic |
1. Introduction to Machine Learning | I: Introduction to Python II: Introduction to Machine Learning applied to Cybersecurity. Supervised learning, error and noise, Overfitting, Regularization, Validation, Introduction to unsupervised learning. |
2. Introduction to Big Data | III: Introduction to Big Data: introduction and technologies. Case studies. |
3. Introduction to Blockchain | IV: Introduction to Blockhain technology and its applications. |
Planning |
Methodologies :: Tests | |||||||||
Class hours | Hours outside the classroom | Total hours | |||||||
Portfolios/Learning folder | 2 | 21 | 23 | ||||||
Laboratory practicals | 19 | 41 | 60 | ||||||
Presentations / expositions | 5 | 20 | 25 | ||||||
Assignments | 2 | 20 | 22 | ||||||
Lecture | 20 | 0 | 20 | ||||||
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. |
Methodologies |
Description | |
Portfolios/Learning folder | Technique for learning how to compile and organize evidence that encourages the student to reflect on his or her progress and demonstrates that he or she has achieved the professional competences which enable him or her to work professionally. |
Laboratory practicals | Computer practices based in the topics covered in the lectures, assisted by the professor. |
Presentations / expositions | Project presentations |
Assignments | Written assignments related to the topics covered in lectures. |
Lecture | Description of the contents of the subject. |
Personalized attention |
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Assessment |
Description | Qualification | ||
Assignments | Written assignments related to the topics covered in lectures. | 45% | |
Portfolios/Learning folder | Technique for learning how to compile and organize evidence that encourages the student to reflect on his or her progress and demonstrates that he or she has achieved the professional competences which enable him or her to work professionally. | 20% | |
Presentations / expositions | Project presentations | 20% | |
Laboratory practicals | Practical application of the theory of a knowledge area in a particular context. Practical exercises using ICTs. | 15% | |
Others | Peer-review activities. Continuous assessment. | 20% | |
Other comments and second call | |||
<p>The grade will be computed attending to two types of assessment: summative and continuous. In order to pass the course, it is necessary to obtain a grade of at least 50%. The final grade will be computed only if the student has a grade of at least 40% in every assignment and test. &nbsp;</p><p>For the continuous assessment, the student will need to create a portfolio, consisting on several assignments to be done along the semester, which will count for 20% of the grade.&nbsp;</p><p>The sumative part will consist on a written final project and two assignments, accounting for 45% of the total grade and their oral presentations, will account for 20% of the grade.&nbsp;</p><p>The grade of the second call will be the graded in the same way. &nbsp;</p><p>At any given time, an explanation / clarification of the documents submitted by the student may be required. Students are supposed to know and accept the Regulations on Plagiarism of the University.</p><p>The use of any electronic device (cell phones, tablets, etc) allowing the student to have communication with other people will be forbidden while doing the tests, as well as any material not explicitly allowed by the professor.&nbsp;</p><p>&nbsp;If a student breaks this rule, he will fail the exam and the Academic Authority of the Center will be informed so that they can follow the procedure approved by the&nbsp;Governing Council of the University on January 29th, 2015.</p><div><br /></div> |
Sources of information |
Access to Recommended Bibliography in the Catalog ULE |
Basic | |
Research papers on the most relevant topics published in the last years. |
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Complementary | |
Recommendations |