Faculty of Informatics, Vytautas Magnus University
Bachelor studies, study programme “Informatics Systems”
Dmytro Vodianytskyi
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(name, surname)
TERM PAPER (task description)
TITLE:
Computer viruses detection using ML
GOAL:
This study investigates machine learning (ML) algorithms for computer virus detection, , practical applications across
industries, and the potential for improvement. We conduct a comparative analysis of these algorithms, identifying
strengths and weaknesses. The research aims to provide recommendations for enhancing computer virus detection and
explores emerging trends and challenges in the field.
TASKS:
1. What types of viruses exist and how are they detected?
2. Learn how virus detection algorithms can be integrated into AI ecosystems.
3. Review and compare ML algorithms for computer virus detection
4. Develop clear and actionable recommendations for improving virus detection algorithms and utilities.
5. Synthesize the main findings of the analysis and draw implications.
EXPECTED RESULTS:
- for midterm presentation:
o Clear and concise definition of computer viruses and how they are detected
o Discussion of the different types of ML algorithms that can be used for computer virus detection, their
strengths and weaknesses, and how they have been used in practice
o Examples of the practical applications of computer virus detection using ML across industries
- for final presentation:
o Detailed analysis of the strengths and weaknesses of different ML algorithms for computer virus
detection, and how their performance can be improved
o Concrete recommendations for developing and deploying more effective ML-based virus detection
systems
o Discussion of the emerging trends and challenges in the field of computer virus detection using ML,
and their implications for the future
SCHEDULE (expand/reduce table upon need)
Week (or up to the date)
Activities
1
Conduct a literature review on computer viruses and their
detection.
2
Analysis
Results
Identify different types of viruses and
how they are detected. Conduct
preliminary research on computer
virus detection using ML to get a
broad overview. Review and compare
different ML algorithms for computer
virus detection, their strengths and
weaknesses, and how they have been
used in practice.
Analyze the strengths and weaknesses
of different ML algorithms for
computer virus detection, and how
their performance can be improved.
3
Synthesis
4
Write the midterm presentation.
5
Further Research/Improvmet
6
Conclusion and Finalization
Student
Synthesize the main findings of the
analysis and draw implications.
Well prepared midterm presentation in
which present a clear and concise
definition of computer viruses and
how they are detected.
Conduct further research, Improve
performance after midterm
presentation
Finalize your paper, review, and edit
for clarity, coherence, and
consistency.
_________________________________________
(name, surname, signature)
Supervisor
_________________________________________
(title, name, surname, signature)
Study Programme
Coordinator
_________________________________________
(title, name, surname, signature)