Bibliographic Details
| Title: |
Machine Learning in Cyber-Security - Problems, Challenges and Data Sets |
| Authors: |
Amit, Idan, Matherly, John, Hewlett, William, Xu, Zhi, Meshi, Yinnon, Weinberger, Yigal |
| Source: |
The AAAI-19 Workshop on Engineering Dependable and Secure Machine Learning Systems, 2019. [[REF](https://sites.google.com/view/edsmls2019/home)] |
| Publication Year: |
2018 |
| Collection: |
Computer Science
Statistics |
| Subject Terms: |
Computer Science - Machine Learning, Computer Science - Cryptography and Security, Statistics - Machine Learning |
| More Details: |
We present cyber-security problems of high importance. We show that in order to solve these cyber-security problems, one must cope with certain machine learning challenges. We provide novel data sets representing the problems in order to enable the academic community to investigate the problems and suggest methods to cope with the challenges. We also present a method to generate labels via pivoting, providing a solution to common problems of lack of labels in cyber-security. |
| Document Type: |
Working Paper |
| Access URL: |
http://arxiv.org/abs/1812.07858 |
| Accession Number: |
edsarx.1812.07858 |
| Database: |
arXiv |
