Afaq Asif
FAST
· 2021
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i17-0217
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Academic
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Year
2021
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Career
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Skills
NodeJS, Python, Visual Studio Code, Eclipse, Angular, Machine Learning, Hybrid Analysis, Malware Detection
Verbatim text
The exact text the LLM saw on the page (or the booklet text from the old import).
This is what powers semantic search.
RandecII is a ransomware detector which has been made to focus on hybrid analysis. Being implemented with our own four machine learning algorithms, RandecII accepts file uploads and process these files to ultimately classify them as malicious or benign. This enables users to comfortably know if any ransomware even part of the PUP family has been downloaded or installed in their device. Different malicious files that are part of legitimate files can also be tested and be correctly classified. The datasets used in training were taken from VirusTotal and Kaggle. Features include: - Realtime testing of malicious files - Cloud storage and its benefits - Hybrid analysis to ensure that the benefits of static and dynamic malware detection can be achieved. - Detection of obfuscated code. Technology Used: NodeJS, Python, Visual Studio Code, Eclipse, Angular Supervisor Name: Mr. Jawad Hassan Group Members: Usman Ali (i16 - 0164) Afaq Asif (i17 - 0217)
Provenance
Source file: Graduate Directory FAST School of Computing 2021 (1st Final) (1).pdfFrom job #24 page 226
Created: 1778223766