Improve and Implement a ML-Based GitHub WAF project Locally -- 2
Budget: $50 – $100 USD
Hello, I need someone who can improve and set up the following project on Jupyter Notebook. This is the link to the project details, you will be able to find the GitHub link on the article itself. (https://www.kdnuggets.com/2017/02/machine-learning-driven-firewall.html) On GitHub, there are some forks available; you can go ahead with a fork too as this one is pretty old.
Following are the improvements needed:
1. You have to implement it, which means you need to make a simple index.html file using Django/Flask so I can test the actual requests being blocked. (Local project)
2. You have to improve the datasets and also introduce an ASN-based IP address blacklist. This way, if an IP address belongs to a datacenter IP address, it blocks it automatically. (I can provide you with the ASN block list.)
3. You can use any algorithmic enhancements and mention it.
Important Note: Clear Documentation on Jupyter notebook is very important.
When bidding, please be specific about your approach as that will help me to pick the most suitable person. Thanks.
Deadline: April 15th.
Budget: $100
Following are the improvements needed:
1. You have to implement it, which means you need to make a simple index.html file using Django/Flask so I can test the actual requests being blocked. (Local project)
2. You have to improve the datasets and also introduce an ASN-based IP address blacklist. This way, if an IP address belongs to a datacenter IP address, it blocks it automatically. (I can provide you with the ASN block list.)
3. You can use any algorithmic enhancements and mention it.
Important Note: Clear Documentation on Jupyter notebook is very important.
When bidding, please be specific about your approach as that will help me to pick the most suitable person. Thanks.
Deadline: April 15th.
Budget: $100