AI-based startup MistNet is moving intelligence to the edge of the network in an attempt to speed recognition of malicious and suspicious activity and reduce the amount of data that has to be moved from edge to cloud for analysis, storage, and forensics. This week's closing of a $7 million Series A funding round will help it put that intelligence into the field.
MistNet, founded by a team who met while working at Juniper Networks, dubs the technology "mist computing" and its application in its products "CyberMist." CyberMist uses a distributed analytical mesh that has artificial intelligence (AI)-based analysis occurring at the edge of the network under the control of a central, cloud-based manager.
CyberMist will typically be used to deliver information to security analysts for their work, according to the company. Although integration tools are available to link CyberMist to remediation systems, "We don't want to be the the automation end of a SOAR [security orchestration, automation, and response solution]. We have integrations with the major SOARs, and we can automate do automatic remediation on that basis," says CyberMist president and CEO Geoffrey Mattson.
Mattson says more traditional hub-and-spoke architectures make it more difficult to use data from a wide variety (and large number) of data sensors because of the sheer volume of data that must flow from the sensors to a central processor.
"They usually tap the network and look at the raw network data," Mattson explains. "They often have agents that allow them to look at specific users' behavior, and they tend to focus on that rather than the output of all the various security a ..