Francesco ORCIUOLI | COGNITIVE METHODS FOR CYBER INTELLIGENCE
Francesco ORCIUOLI COGNITIVE METHODS FOR CYBER INTELLIGENCE
cod. 0222700026
COGNITIVE METHODS FOR CYBER INTELLIGENCE
| 0222700026 | |
| DEPARTMENT OF MANAGEMENT & INNOVATION SYSTEMS | |
| EQF7 | |
| DATA SCIENCE AND INNOVATION MANAGEMENT | |
| 2021/2022 |
| OBBLIGATORIO | |
| YEAR OF COURSE 2 | |
| YEAR OF DIDACTIC SYSTEM 2020 | |
| SPRING SEMESTER |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| INF/01 | 6 | 42 | LESSONS | |
| INF/01 | 3 | 21 | LAB |
| Objectives | |
|---|---|
| THE COURSE WILL DEAL WITH COMPUTATIONAL METHODS AND TECHNOLOGIES BASED ON COGNITIVE APPROACHES FOR DEFINING DECISION-MAKING SYSTEMS IN THE CONTEXT OF INTELLIGENCE. IN PARTICULAR, THE COURSE REFERS TO THE STUDY OF COMPUTER TECHNIQUES FOR DATA ANALYSIS (ALSO CONSIDERING BIG DATA) TO SUPPORT THE DECISION MAKER TO IDENTIFY AND ANALYZE POSSIBLE THREATS, HOW THEY CAN OCCUR AND THE DAMAGE THAT THEY CAN PROCURE, IN ORDER TO TIMELY PROVIDE EFFECTIVE PREVENTION AND ADEQUATE INTERVENTION MEASURES. STUDENTS WILL LEARN CONCEPTS RELATED TO COGNITIVE COMPUTING, GRANULAR COMPUTING AND SEMANTIC TECHNOLOGIES, ACQUIRE KNOWLEDGE ON DECISION THEORY AND ON COMPUTATIONAL METHODS SUCH AS FORMAL CONCEPT ANALYSIS, ROUGH SET THEORY, THREE-WAY DECISIONS, FUZZY CONSENSUS MODEL AND, LASTLY, ADDRESS THE STUDY OF COGNITIVE SERVICES PROVIDED BY THE MOST IMPORTANT TECHNOLOGY PLAYERS. AT THE END OF THE COURSE, STUDENTS WILL BE ABLE TO APPLY THE STUDIED METHODS AND TECHNOLOGIES IN ORDER TO SUPPORT (CYBER) INTELLIGENCE AND (COGNITIVE) DEFENSE METHODOLOGIES, AS WELL AS THE ABILITY TO DESIGN AND IMPLEMENT DECISION SUPPORT SYSTEMS IN THE AFOREMENTIONED AREAS BY USING SPECIFIC PROGRAMMING LANGUAGES AND LIBRARIES. THE LESSONS WILL ALLOW STUDENTS TO DEVELOP SKILLS USEFUL FOR UNDERSTANDING A DECISION-MAKING PROBLEM (ESPECIALLY IN THE FIELD OF INTELLIGENCE), ANALYZING IT AND DESIGNING EFFECTIVE AND EFFICIENT SOLUTIONS. |
| Prerequisites | |
|---|---|
| IN ORDER TO ADEQUATELY DEAL WITH THE COURSE CONTENT, IT IS DESIRABLE THAT STUDENTS HAVE THE FOLLOWING KNOWLEDGE/SKILLS: SITUATION AWARENESS AND COMPUTER PROGRAMMING. |
| Contents | |
|---|---|
| WITH RESPECT TO THE CONTENT, THE COURSE IS DIVIDED INTO FOUR PARTS: I – PART 1 (20 HOURS) I.A INTELLIGENCE CYCLE, DECISION MAKING AND DECISION SUPPORT SYSTEMS I.B COGNTIVE COMPUTING AND THREE-WAY DECISIONS I.C ROUGH SET THEORY I.D GRANULAR COMPUTING BASICS II – PART 2 (10 HOURS) II.A MODELLING RELATIONS WITH GRAPHS II.B MODELLING BEHAVIORS WITH FUZZY SIGNATURES II.C CASE STUDIES: MARITIME SURVEILLANCE, PANDEMIC MANAGEMENT, ETC. III – PART 3 (21 HOURS) III.A PYTHON FOR SUPPORTING DECISION-MAKING IN THE INTELLIGENCE CYCLE III.B PYTHON LIBRARIES: NUMPY/PANDAS, NETWORKX, MATPLOTLIB/PLOTLY, ETC. III.C HANDS-ON LAB IV – PART 4 – POSSIBLE EXTRAS – (12 HOURS) IV.A INCREMENTAL METHODS FOR APPROXIMATE REASONING IV.B SEQUENTIAL THREE-WAY CLASSIFIERS IV.C COGNITIVE SERVICES IV.D SEMANTIC TECHNOLOGIES IV.E DECISION THEORY IV.F FUZZY CONSENSUS MODEL IV.G FORMAL CONCEPT ANALYSIS |
| Teaching Methods | |
|---|---|
| THE TEACHING ACTIVITIES (63 HOURS AND 9 ECTS) WILL BE DIVIDED INTO LECTURES AIDED BY MULTIMEDIA MATERIAL (42 HOURS) AND LABORATORY LESSONS (21 HOURS). ACTIVITY-BASED LEARNING WILL BE THE MAIN EMPLOYED METHOD. STUDENTS WILL BE INVOLVED IN GROUP OR INDIVIDUAL PROJECT WORKS. |
| Verification of learning | |
|---|---|
| THE EVALUATION WILL BE CARRIED OUT BY MEANS OF A 40 MINUTES DISCUSSION (FOR EACH STUDENT) ABOUT BOTH ALL THE TOPICS OF THE COURSE AND THE ASSIGNED PROJECT WORK (PRESENTATION AND Q/A SESSION). STUDENTS WILL BE EVALUATED BY USING A SCALE OF 30. |
| Texts | |
|---|---|
| MAIN TEXTBOOKS: - LIRONG JIAN, SIFENG LIU, YI LIN – HYBRID ROUGH SETS AND APPLICATIONS IN UNCERTAIN DECISION-MAKING – CRC PRESS - M. PETERSON – AN INTRODUCTION TO DECISION THEORY – 2ND EDITION, CAMBRIDGE UNIVERSITY PRESS, 2017 - G-H TZENG, J-J HUANG - MULTIPLE ATTRIBUTE DECISION MAKING: METHODS AND APPLICATIONS - 1ST EDITION, CRC PRESS, 2011 - R. SHARDA, D. DELEN, E. TURBAN – BUSINESS INTELLIGENCE AND ANALYTICS: SYSTEMS FOR DECISION SUPPORT – 10TH EDITION, PEARSON, 2013 - V.L. SAUTER – DECISION SUPPORT SYSTEMS FOR BUSINESS INTELLIGENCE – 2ND EDITION, WILEY, 2011 - G. ANTONIOU, P. GROTH, F. VAN HARMELEN – A SEMANTIC WEB PRIMER – 3RD EDITION, MIT PRESS, 2012 - M. LUTZ – LEARNING PYTHON – 5TH EDITION, O’REILLY, 2013 - C.R. SEVERANCE - PYTHON FOR EVERYBODY: EXPLORING DATA USING PYTHON 3 (FREE WEB RESOURCE) |
| More Information | |
|---|---|
| ADDITIONAL LEARNING RESOURCES WILL BE PROVIDED BY THE TEACHER. |
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