machine-learning project sift
Machine-Learning Project Sifts Through Big Security Data
As an information-security consultant, Alexandre Pinto spent 12 years helping companies set up difficult-to-configure systems to cull security intelligence from logs and security events. Yet configuring the systems required months of work and even then needed constant maintenance to enable them to detect the latest threats and pinpoint likely malicious traffic. He realized that while companies may want to monitor their networks for threats, they typically have too few security people to work through data from far too many logs -- a problem that will only get worse as companies seek to sift through more operational data to detect threats. Big data could be the downfall of security if companies don't find better ways of dealing with the growing volumes, he says. "What chance do we have: We can't find the needle in the haystack as it is now, and now the haystack is 100,000 times larger," he says.