Comparison of ML Models for Malware Detection
Budget: ₹600 – ₹1,500 INR
I need a comprehensive research paper that focuses on the comparison of several ML models for malware detection, specifically utilizing API call sequences.
Requirements:
- The primary goal of the paper should be to compare the efficacy of Decision Trees, Neural Networks, Support Vector Machines, siamese and protonet models in detecting malware.
- You must also compare the performance of these models based on the metrics of Accuracy, Precision, and Recall.
Ideal Skills:
- Strong background in machine learning and cybersecurity.
- Proficiency in writing academic research papers.
- Experience in conducting comparative studies of ML models.
- Understanding of API call sequences and their relevance in malware detection would be an advantage.
Please provide a brief overview of your experience and approach to this task in your proposal.
Requirements:
- The primary goal of the paper should be to compare the efficacy of Decision Trees, Neural Networks, Support Vector Machines, siamese and protonet models in detecting malware.
- You must also compare the performance of these models based on the metrics of Accuracy, Precision, and Recall.
Ideal Skills:
- Strong background in machine learning and cybersecurity.
- Proficiency in writing academic research papers.
- Experience in conducting comparative studies of ML models.
- Understanding of API call sequences and their relevance in malware detection would be an advantage.
Please provide a brief overview of your experience and approach to this task in your proposal.
Related categories:
Python
Computer Security
Health & Medicine
Research Writing
Machine Learning (ML)