View Proposal
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Proposer
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Kayvan Karim
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Title
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Network Intrusion Detection System using Netflow Data and Machine Learning
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Goal
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To detect different types of attacks using NetFlow data using available datasets
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Description
- The project applies machine learning algorithms to analyze the attack patterns within Netflow data, distinguishing benign network behaviour from potential cyber threats. The Netflow data can be aggregated using the NTFA tool and then build machine learning models to detect the attacks.
- Resources
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Background
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Url
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External Link
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Difficulty Level
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Moderate
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Ethical Approval
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None
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Number Of Students
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3
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Supervisor
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Kayvan Karim
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Keywords
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nids, network intrusion detection, machine learning
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Degrees
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Bachelor of Science in Computer Science
Master of Science in Computer Science for Cyber Security