HackerPapers

arXiv:1812.07858cs.LG

Machine Learning in Cyber-Security - Problems, Challenges and Data Sets

Idan Amit, John Matherly, William Hewlett, Zhi Xu, Yinnon Meshi, Yigal Weinberger

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

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.

arXiv comments
Journal reference
The AAAI-19 Workshop on Engineering Dependable and Secure Machine Learning Systems, 2019. [[REF](https://sites.google.com/view/edsmls2019/home)]
DOI
Subjects
cs.LGMachine Learning cs.CRCryptography and Security stat.MLMachine Learning (Statistics)

On Hacker News

Linked by 1 identifiable commenter in 1 comment across 1 thread, from Jan 2019 to Jan 2019.

Comments linking this paper, per year.

Discussed in comments1 thread

  1. Ask HN: Does ML research ever get translated to industry? 1 comment

    • I think that an important obstacle is that the industry and academy have different goals and therefore different motivations. We (researchers from Palo Alto Networks and Shodan), recently published a paper on machine learning challenges in cyber security, aiming to the academy.…

      idan_panView on HNParent context

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.