# machine_learning_security

**Repository Path**: LightInfection/machine_learning_security

## Basic Information

- **Project Name**: machine_learning_security
- **Description**: Source code about machine learning and security.
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-02-25
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Machine Learning and Security
Source codes about machine learning and security.

## Line up.
 * [Cyber security and Machine Learning course](https://github.com/13o-bbr-bbq/machine_learning_security/tree/master/Security_and_MachineLearning)  
 The elementary training course of Machine learning for security engineer.  
 * [Vulnerabilties of Machine Learning](https://github.com/13o-bbr-bbq/machine_learning_security/blob/master/Vulnerabilities_of_ML/)  
 Summary of Machine Learning vulnerability.  
 * [Analytics](https://github.com/13o-bbr-bbq/machine_learning_security/tree/master/Analytics)  
 Analyzing packet capture data using k-means.  
 * [CNN_test](https://github.com/13o-bbr-bbq/machine_learning_security/tree/master/CNN_test)  
 Generate adversarial example against CNN.  
 * [Deep Exploit](https://github.com/13o-bbr-bbq/machine_learning_security/tree/master/DeepExploit)  
 Fully automatic penetration test tool using Machine Learning.  
 Deep Exploit was presented at **[Black Hat USA 2018 Arsenal](https://www.blackhat.com/us-18/arsenal/schedule/index.html#deep-exploit-11908)** and **[DEF CON 26! AI Village](https://aivillage.org/posts/accepted-talks/)**.  
* [GyoiThon](https://github.com/gyoisamurai/GyoiThon)  
 Next generation penetration test tool.  
 GyoiThon was presented at **[Black Hat ASIA 2018 Arsenal](https://www.blackhat.com/asia-18/arsenal/schedule/index.html#gyoithon-9651)** and **[DEF CON 26! Demo Labs](https://www.defcon.org/html/defcon-26/dc-26-demolabs.html)**.  
 * [Generator](https://github.com/13o-bbr-bbq/machine_learning_security/tree/master/Generator)  
 Fully automatically generate numerous injection codes for web application assessment.
 * [Recommender](https://github.com/13o-bbr-bbq/machine_learning_security/tree/master/Recommender)  
 Recommend optimal injection code for detecting web app vulnerabilities.
 * [SAIVS (Spider Artificial Intelligence Vulnerability Scanner)](https://github.com/13o-bbr-bbq/machine_learning_security/tree/master/Saivs)  
 SAIVS is an artificial intelligence to find vulnerabilities in Web applications.  
 SAIVS was presented at **[Black Hat ASIA 2016 Arsenal](http://www.blackhat.com/asia-16/arsenal.html#saivs-spider-artificial-intelligence-vulnerability-scanner)**.  

## Contact us

Isao Takaesu  
takaesu235@gmail.com  
[https://twitter.com/bbr_bbq](https://twitter.com/bbr_bbq)