View Proposal

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Proposer

Hani Ragab

Title

Machine Learning for Linux Malware Detection

Goal

Investigate the application of machine learning to Linux Malware

Description

This project will review existing works for Linux malware detection. It will then investigate how to apply machine learning techniques to it. This will include identifying possible features that can characterise malware (e.g. subsets of binary code) then applying suitable techniques to them. The following books are in the library, you might want to have a look at them beforehand: - https://www.nostarch.com/malware, - https://www.packtpub.com/networking-and-servers/learning-linux-binary-analysis, - https://www.packtpub.com/big-data-and-business-intelligence/building-machine-learning-systems-python-second-edition

Resources

https://www.nostarch.com/malware, https://www.packtpub.com/networking-and-servers/learning-linux-binary-analysis

Background

Good understanding of how Linux works.

Url

Difficulty Level

Variable

Ethical Approval

None

Number Of Students

2

Supervisor

Hani Ragab

Keywords

Degrees

Bachelor of Science in Computer Science
Master of Science in Artificial Intelligence
Master of Science in Computer Science for Cyber Security
Master of Science in Data Science
Master of Science in Software Engineering
Postgraduate Diploma in Artificial Intelligence
Bachelor of Science in Statistical Data Science
BSc Data Sciences
MSc Applied Cyber Security