Machine Learning (ML) has become the shiny new object for security and is the foundational pillar of products such as Next-Generation Antivirus (NGAV) and User and Entity Behavior Analytics (UEBA). While most of these products have promised to be a “silver bullet” against malware, complete protection remains elusive. In fact, ML is more likely to detect and cure cancer than to stop all of today’s advanced threats for a number of reasons:
- The past doesn’t predict the future
- Nothing will keep the bad guys out
- The harder you try the more you fail
- You can’t always be connected
- It’s a black box
Join our webinar to learn more!
Fortunately, you can get more value out of your ML-based security with a complimentary OS-Centric Positive Security solution that uncovers new, never-seen-before and fileless malware threats that ML can miss.
On Feb. 27 at 3 EST, Shahid Shah and Rene Kolga will discuss the role of machine learning and OS-Centric Positive Security in endpoint protection.
Click here to register.
- Hakin9 is a monthly magazine dedicated to hacking and cybersecurity. In every edition, we try to focus on different approaches to show various techniques - defensive and offensive. This knowledge will help you understand how most popular attacks are performed and how to protect your data from them. Our tutorials, case studies and online courses will prepare you for the upcoming, potential threats in the cyber security world. We collaborate with many individuals and universities and public institutions, but also with companies such as Xento Systems, CATO Networks, EY, CIPHER Intelligence LAB, redBorder, TSG, and others.
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