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DC Field | Value | Language |
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dc.contributor.author | Gupta, Gautam | - |
dc.contributor.author | Gupta, Deepak [Guided by] | - |
dc.date.accessioned | 2023-09-13T04:55:57Z | - |
dc.date.available | 2023-09-13T04:55:57Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9971 | - |
dc.description | Enrollment No. 191311 | en_US |
dc.description.abstract | Malware poses a significant threat to today's infrastructure. Malware is a computer code designed to gain unauthorized access, exploit vulnerabilities and cause overall harm to digital systems all around the world. Today, malware poses a big threat to any country's critical infrastructure such as banks, defense systems, stock markets, etc. Although working in the digital space, the consequences of its actions can reflect in the physical world too. In order to detect and prevent malware from affecting infra, many techniques such as signature-based detection are used but with the advancements in technology, these old strategies are rendered obsolete by ever-evolving malware threats. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Jaypee University of Information Technology, Solan, H.P. | en_US |
dc.subject | Malware detection | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Numpy | en_US |
dc.subject | K- nearest neighbors | en_US |
dc.title | Malware Analysis using Machine Learning | en_US |
dc.type | Project Report | en_US |
Appears in Collections: | B.Tech. Project Reports |
Files in This Item:
File | Description | Size | Format | |
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Malware Analysis using Machine Learning.pdf | 994.01 kB | Adobe PDF | View/Open |
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