<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Open Data at CIRCL on CIRCL</title>
    <link>https://new.circl.lu/opendata/</link>
    <description>Recent content in Open Data at CIRCL on CIRCL</description>
    <generator>Hugo</generator>
    <language>en-us</language>
    <atom:link href="https://new.circl.lu/opendata/rss.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>CIRCL Images AIL Dataset - Open Data at CIRCL</title>
      <link>https://new.circl.lu/opendata/circl-ail-dataset-01/</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://new.circl.lu/opendata/circl-ail-dataset-01/</guid>
      <description>&lt;h2 id=&#34;introduction&#34;&gt;Introduction&lt;/h2&gt;&#xA;&lt;p&gt;CERTs such as CIRCL and security teams collect and process content such as images (at large from photos, screenshots of websites or screenshots of sandboxes).&#xA;Datasets become larger - e.g. on average 10000 screenshots of onion domains websites are scrapped each day in &lt;a href=&#34;https://github.com/ail-project/ail-framework&#34;&gt;AIL - Analysis Information Leak framework&lt;/a&gt;, an analysis tool of information leak - and analysts need to classify, search and correlate through all the images.&lt;/p&gt;&#xA;&lt;p&gt;Automatic tools can help them in this task. Less research about image matching and image classification seems to have been conducted  exclusively on websites screenshots. However, a classification of this kind of pictures needs to be addressed.&lt;/p&gt;</description>
    </item>
    <item>
      <title>CIRCL Images Phishing Dataset - Open Data at CIRCL</title>
      <link>https://new.circl.lu/opendata/circl-phishing-dataset-01/</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://new.circl.lu/opendata/circl-phishing-dataset-01/</guid>
      <description>&lt;h2 id=&#34;introduction&#34;&gt;Introduction&lt;/h2&gt;&#xA;&lt;p&gt;CERTs such as CIRCL and security teams collect and process content such as images (at large from photos, screenshots of websites or screenshots of sandboxes).&#xA;Datasets become larger - e.g. on average 10000 screenshots of onion domains websites are scrapped each day in &lt;a href=&#34;https://github.com/ail-project/ail-framework&#34;&gt;AIL - Analysis Information Leak framework&lt;/a&gt;, an analysis tool of information leak - and analysts need to classify, search and correlate through all the images.&lt;/p&gt;&#xA;&lt;p&gt;Automatic tools can help them in this task. Less research about image matching and image classification seems to have been conducted  exclusively on websites screenshots. However, a classification of this kind of pictures needs to be addressed.&lt;/p&gt;</description>
    </item>
  </channel>
</rss>
