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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Machine Learning in Cyber-Security - Problems, Challenges and Data Sets · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1812.07858/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1812.07858/feed.xml" rel="self" type="application/rss+xml" /><item><title>Machine Learning in Cyber-Security - Problems, Challenges and Data Sets — mentioned by idan_pan</title><link>https://news.ycombinator.com/item?id=18896217</link><guid isPermaLink="false">urn:hackerpapers:mention:1812.07858:18896217</guid><pubDate>Sun, 13 Jan 2019 11:24:35 GMT</pubDate><description>&lt;p&gt;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. https://arxiv.org/abs/1812.07858 Finding problems that will be of interest to the academy wasn&amp;#x27;t easy. Taking algorithms that will be based on them and turning them into a product will be hard. We explained why textbook machine learning will fail on these problem, what make it interesting academically. We also provide…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1812.07858/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
