Technological changes are evolving at an unprecedented rate – so why aren’t most network detection and response (NDR) solutions? NDR and network performance monitoring and diagnostic tools created 30 years ago can’t keep up with today’s complex, interconnected networks. With each new connection comes a possible vulnerability and a higher risk profile. Cybercriminals are always looking for corporate networks that are complex and filled with security gaps for them to sneak through unnoticed. This security challenge has persisted despite the many efforts of enterprise IT security teams.
The problem is one of pace; neither legacy solutions nor human analysts are able to keep up.
Enterprises need assistance from AI-based solutions to enable full visibility into their network. network detection and response (NDR) solutions derive particular benefit from AI. However, to implement NDR well, organizations need clarity on its key elements, both before and after implementation.
The need for AI assistance
With the increased complexity of networks and the increased volume of data, the reality is that human analysts are incapable of monitoring all of it, alone. To make matters worse, the industry is experiencing an estimated shortage of 2.72 million skilled cybersecurity professionals – there just aren’t enough skilled people to adequately defend organizations’ critical assets. Instead, the industry must learn how to use tools like AI and ML to supplement these skills gaps. The lack of capable and experienced cybersecurity talent can leave networks vulnerable to a myriad of threats.
Continue reading: https://solutionsreview.com/network-monitoring/how-ai-driven-network-detection-and-response-closes-security-gaps/
The problem is one of pace; neither legacy solutions nor human analysts are able to keep up.
Enterprises need assistance from AI-based solutions to enable full visibility into their network. network detection and response (NDR) solutions derive particular benefit from AI. However, to implement NDR well, organizations need clarity on its key elements, both before and after implementation.
The need for AI assistance
With the increased complexity of networks and the increased volume of data, the reality is that human analysts are incapable of monitoring all of it, alone. To make matters worse, the industry is experiencing an estimated shortage of 2.72 million skilled cybersecurity professionals – there just aren’t enough skilled people to adequately defend organizations’ critical assets. Instead, the industry must learn how to use tools like AI and ML to supplement these skills gaps. The lack of capable and experienced cybersecurity talent can leave networks vulnerable to a myriad of threats.
Continue reading: https://solutionsreview.com/network-monitoring/how-ai-driven-network-detection-and-response-closes-security-gaps/
