Automate Threat hunting With Security Analytics & Machine Learning

Presented by

Ryan Stolte, CTO and co-founder, Bay Dynamics

About this talk

Multi-stage attacks use diverse and distributed methods to circumvent existing defenses and evade detection - spanning endpoints, networks, email and other vectors in an attempt to land and expand. Meanwhile, individual tools including DLP, EDR, CASBs, email security and advanced threat protection are only designed to identify individual elements of a campaign, putting the onus on human analysts to piece together the bigger picture - when time and resources allow. Today's advanced security analytics platforms combine data from numerous security solutions to eliminate blind spots, visualize multi-stage threats and provide the detailed context necessary to enact targeted response. By using behavioral analytics and applying dedicated machine learning, these platforms automate critical threat hunting capabilities, so analysts at all levels can pinpoint advanced attacks, drive remediation and continuously refine investigation. Register for this webinar and learn about: -Visualizing multi-stage threats and compromised users; -Investigating and hunting within and across stages; -Maximizing human talent using Machine Learning. -Addressing DLP, EDR and Email Security use cases;

Related topics:

More from this channel

Upcoming talks (0)
On-demand talks (20)
Subscribers (5870)
Bay Dynamics® is the market leader in cyber risk predictive analytics providing actionable visibility into organizations’ cybersecurity blind spots, complete with business risks and threats. The company’s purpose-built Risk Fabric® platform assembles and correlates relevant data from existing tools in a novel patented way to provide actionable cyber risk insights, before it’s too late. Bay Dynamics enables some of the world’s largest organizations to understand the state of their cybersecurity posture, including contextual awareness of what their insiders, vendors and bad actors are doing, which is key to effective cyber risk management