Catching malware outbreaks early keeps users, communities, enterprises, and governments safe. But if malware samples are scarce, can machine learning help analyze, detect, and end an outbreak?
Fileless threats aren’t as visible compared to traditional malware and employ a variety of techniques to stay persistent. Here's a closer look at how fileless malware work and what can be done to thwart them.
Here’s a closer look at the challenges enterprises are confronted with when adopting a more robust cybersecurity strategy, and how managed detection and response can help address them.
Threat data — enough of it — is critical to a machine learning system’s success in cybersecurity solutions. But is data quantity the be-all and end-all of effective machine learning?
Addressing the need for a more efficient way to defend against spam in the early 2000s, the antispam industry turned to machine learning. The effect: Overall cyberdefense was enhanced to catch approximately 95 percent of spam.
Here are some considerations and best practices that developers, IT operations professionals, and system administrators should take into account in securing the infrastructures that power the applications they use.
While the GDPR will require businesses to comply with rules that will ultimately protect customer data, concerns have been raised regarding how it will tackle automation in data analytics as the market for artificial intelligence (AI) continues to grow.
