Cybersecurity tools used in data centers are getting smarter as vendors roll out more machine learning capabilities. It can help with everything from identifying new types of malware to flagging malicious behavior.
Training machine learning models does require large amounts of data to make accurate predictions, but this isn’t a problem in cybersecurity, where security teams are burdened by the problem of too much data — too many security alerts, too many anomalies, too many potential problems — rather than too little.
“The real problem is how to correctly use, interpret, and make the right conclusions from it,” Nick Bilogorskiy, cybersecurity strategist at Juniper Networks, said. “As it stands today, this is something we still very much need a human subject matter expert to do.”
The new tools do put a lot more power into the hands of individual security professionals. According to Jerry Gamblin, principal security engineer at Kenna Security, the number of assets any security team is responsible for has increased exponentially. Last year, for example, an average of 40 new vulnerabilities were discovered every day, he said.
Read full article at Data Center Knowledge.
