RiskSense to Present Offensive Approach for Cyber Resilience at Federal IT Security Conference (FITSC)

RiskSense®, Inc., the pioneer and market leader in cyber risk management, today announced that Daniel Culpepper, the company’s director of systems engineering and a leading expert in security architectures will present at the Federal IT Security Conference (FITSC) in Columbia, MD on November 14, 2017.


Daniel Culpepper is director of sales engineering for RiskSense, and a hands-on expert in helping government agencies and enterprises implement cyber risk management infrastructures. He has served as a lead manager for Information Security at Freddie Mac and managed audit and enterprise risk consulting projects for Deloitte.


By using artificial intelligence (A.I.), hackers can very quickly identify vulnerabilities in their target’s infrastructure and launch exploits at tremendous scale. In this session, Daniel Culpepper will use a case study to illustrate the magnitude of the “malevolent A.I.” threat and present a new approach that governments and enterprises can use to go on the offensive, called Human Expertise + A.I. He will explain how it enables security operations teams to quickly acquire an “attacker’s view” of their entire attack surface, e.g., networks, endpoints, applications, cloud services, mobile and IoT devices, and industrial control systems. Culpepper will also discuss how Human Expertise + AI can be used to determine attack susceptibility, validate exploitable vulnerabilities, test the efficacy of existing security controls, and focus remediation efforts based on asset criticality.


Tuesday, Nov. 14, 2017 from 3:45 pm-5:00 pm EST.


Phoenix TS, 10420 Little Patuxent Parkway, Suite 500, Columbia, MD 21044.


To schedule a conversation with RiskSense, contact Marc Gendron at marc@mgpr.net or +1 781.237.0341.  For more information or to register visit: http://www.fitsi.org/conference2017/.

RiskSense Platform Overview: http://bit.ly/2yIJ1YE
White Paper on Operationalizing Cyber Risk: http://bit.ly/2gaurSX
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