Grupoed2kMagazine<p>Real-time botnet detection on large network bandwidths using machine learning</p><p><a href="https://tkz.one/tags/Botnets" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Botnets</span></a> are one of the most harmful <a href="https://tkz.one/tags/cyberthreats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>cyberthreats</span></a>, that can perform many types of <a href="https://tkz.one/tags/cyberattacks" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>cyberattacks</span></a> and cause billionaire losses to the global economy. Nowadays, vast amounts of network traffic are generated every second, hence manual analysis is impossible. To be effective, automatic botnet detection should be done as fast as possible, but carrying this out is difficult in large bandwidths. To handle this problem, we propose an approach that is capable of carrying out an ultra-fast network analysis (i.e. on windows of one second),</p><p>Article<br>Open access<br>Published: 15 March 2023</p><p><a href="https://tkz.one/tags/ComputationalScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalScience</span></a> </p><p><a href="https://tkz.one/tags/Share" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Share</span></a> this article <br>Anyone you share the following link with will be able to read this content:</p><p><a href="https://rdcu.be/exVLd" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">rdcu.be/exVLd</span><span class="invisible"></span></a></p><p>Download PDF<br><a href="https://www.nature.com/articles/s41598-023-31260-0.pdf" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">nature.com/articles/s41598-023</span><span class="invisible">-31260-0.pdf</span></a></p>