Cato Networks’ new deep learning algorithms are designed to identify malware command and control domains and block them more quickly than traditional systems based on domain reputation, thanks to extensive training on the company’s own data sets.
Cato, a SASE provider based in Tel Aviv, announced the new algorithmic security system today. The system is predicated on the idea that domain reputation tracking is insufficient to quickly identify the command servers used to remotely control malware. That’s because most modern malware uses a domain generation algorithm (DGA) to rapidly generate pseudorandom domain names — which the deployed malware also has a copy of.
To read this article in full, please click here
http://dlvr.it/SrJnVV
Langganan:
Posting Komentar (Atom)
Versa extends SASE platform to the LAN edge
Versa Networks has bumped up its secure access service edge (SASE) software with a variety of features, including AI to help customers bette...
-
As connectivity to cloud-based resources grows, cybercriminals are using valid, compromised credentials to access enterprise resources at an...
-
Redundancy is essential for dealing with both planned and unplanned outages, and that includes having redundant dynamic host-configuration p...
-
Attacks related to Domain Name System infrastructure – such as DNS hijacking, DNS tunneling and DNS amplification attacks – are on the rise,...

Tidak ada komentar:
Posting Komentar