2021 Machine Learning Security Evasion Competition

Related tags

Machine Learning 2021-Machine-Learning-Security-Evasion-Competition
Overview

2021 Machine Learning Security Evasion Competition

This repository contains code samples for the 2021 Machine Learning Security Evasion Competition. Participants must register at https://mlsec.io and accept the terms of service in order to participate.

IMPORTANT: OUR 2021 TRAINED MODEL CAN BE DOWNLOADED HERE.

Dates

Challenge Start Date End Date
defender Jun 15, 2021 (AoE) Jul 23, 2021 (AoE)
attacker Aug 6, 2021 (AoE) Sep 17, 2021 (AoE)

*start and end times are Anywhere on Earth (AoE)

Contents

Outline the file contents of the repository. It helps users navigate the codebase, build configuration and any related assets.

File/folder Description
defender Sample source code for the defender challenge.
attacker Sample source code for the attacker challenge.
README.md This README file.
LICENSE The license for the sample code.
CODE_OF_CONDUCT.md Microsoft's open source code of conduct.
SECURITY.md Reporting security issues.

Contributing

This project welcomes contributions and suggestions, during or after the competition. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

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Owner
Fabrício Ceschin
Computer Science Master @ UFPR. PhD Student @ UFPR. Machine Learning & Cyber Security Scientist and Researcher.
Fabrício Ceschin
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