A technology solution that leverages artificial intelligence, machine learning and big data-based profiling methodologies to fight advanced persistent threats (APTs) has been released by Rohde & Schwarz Cybersecurity and Saint Security, a vendor of network protection solutions.
The solution identifies and blocks various types of malware that cannot be detected by off-the-shelf security solutions.
The DPI engine R&S PACE 2 serves as the key enabling feature by extracting file content and metadata to identify potentially dangerous executables caused by APTs.
"The ability of extracting file content extended the functionality of the network-based advanced malware response solution MNX to analyse all network traffic, services and protocols across all ports with an extremely fine granularity," says Kihong KIM, CEO of Saint Security. "The extracted information is key to better identify and investigate multi-stage, advanced persistent threats such as malicious emails or ransomware. This enormously enhanced our product’s quality and our customers can now rely on a sophisticated security solution that even detects previously unknown or unseen threats," adds KIM. Saint Security’s network protection solution intercepts possible APTs at any point in a network.
In order to fingerprint malicious activity and to unlock the full potential of their AI-based analysis methodologies, they decided to embed the DPI engine R&S PACE 2 from Rohde & Schwarz Cybersecurity to get a deep understanding of the observed network traffic. R&S PACE 2 extracts file content and metadata such as files attached to emails (e.g. .pdf, .exe or .doc) or sent through files transfers from within the traffic in real time.
This enables Saint Security to identify potentially dangerous executables caused by APTs and set up advanced security and traffic management policies. Machine learning and AI are critical to network security as cybercriminals around the world incessantly release new malware types that can morph and look like harmless files.
It is almost impossible for antivirus engines to detect these threats as they can bypass legacy security approaches, gain hold within a network and make organisations vulnerable to data breaches.