Description: Our international panel will examine some of the key questions organizations face regarding cybersecurity breaches, cloud computing, compliance, privacy (including GDPR), and AI. How will AI help identify data breach risks? How will cloud issues affect AI? How will AI impact compliance and privacy requirements? After attending this webinar, attendees will able to answer the following questions: -Where does AI contribute to cybersecurity, such as in threat intelligence production and enrichment? Threat intelligence consumption? AI and compliance efforts? Also, where does AI play a role in risk identification, risk mitigation, and breach detection? Cybersecurity is a growing concern, with third-party vendors responsible for 63% of data breaches. What are the main challenges in today’s changing cyber landscape? -How can businesses manage cyber risks posed by third-party vendors? How can AI models be responsibly trained and validated using datasets correctly classified by sensitivity levels—such as Public, Private, Confidential, Secret, and Restricted—and what technical and procedural safeguards ensure that misclassified or mislabeled data does not inadvertently expose sensitive or protected information during processing, storage, or model inference? -When combining data from multiple sources for AI model training, what technical controls, governance frameworks, and validation processes are in place to ensure secure data integration that: Prevents data leakage and unauthorized access, maintains data integrity across systems, Furthermore, does it adhere to regulatory and compliance obligations such as HIPAA, GDPR, FISMA, FedRAMP, CCPA, NYDPA, SOX, GLBA, FERPA, DoD Cybersecurity Maturity Model Certification (CMMC), and other applicable state, federal, and industry-specific standards? How are these mechanisms evaluated and updated as data sources or AI models evolve? -What are the ethical and security concerns of using AI-generated synthetic data instead of real-world data, and how can organizations ensure that fabricated data doesn't inadvertently resemble or expose real individuals' identities? Speakers: Ulf Mattsson, CTO, UlfMattsson.com John C. Checco, DSc. C|CISO, CISSP, CCSK, Board Certified QTE, Chapter President, ISSA NY Metro Ariel Evans, CEO and Co-Founder, RiskQ Inc. Dr. Daniel O’Connell, EdD, MS, CDPSE, ITIL, HDPCA, Principal/Founder & CEO, DocLogical, LLC & Quinnipiac University Claude Baudoin, Co-Chair, Owner and Principal Consultant, OMG Cloud Working Group, cébé IT & Knowledge Management Archived until: 12:00pm CT on 3 March 2027
Description: Our international panel will examine some of the key questions organizations face regarding cybersecurity breaches, cloud computing, compliance, privacy (including GDPR), and AI. How will AI help identify data breach risks? How will cloud issues affect AI? How will AI impact compliance and privacy requirements? After attending this webinar, attendees will able to answer the following questions: -Where does AI contribute to cybersecurity, such as in threat intelligence production and enrichment? Threat intelligence consumption? AI and compliance efforts? Also, where does AI play a role in risk identification, risk mitigation, and breach detection? Cybersecurity is a growing concern, with third-party vendors responsible for 63% of data breaches. What are the main challenges in today’s changing cyber landscape? -How can businesses manage cyber risks posed by third-party vendors? How can AI models be responsibly trained and validated using datasets correctly classified by sensitivity levels—such as Public, Private, Confidential, Secret, and Restricted—and what technical and procedural safeguards ensure that misclassified or mislabeled data does not inadvertently expose sensitive or protected information during processing, storage, or model inference? -When combining data from multiple sources for AI model training, what technical controls, governance frameworks, and validation processes are in place to ensure secure data integration that: Prevents data leakage and unauthorized access, maintains data integrity across systems, Furthermore, does it adhere to regulatory and compliance obligations such as HIPAA, GDPR, FISMA, FedRAMP, CCPA, NYDPA, SOX, GLBA, FERPA, DoD Cybersecurity Maturity Model Certification (CMMC), and other applicable state, federal, and industry-specific standards? How are these mechanisms evaluated and updated as data sources or AI models evolve? -What are the ethical and security concerns of using AI-generated synthetic data instead of real-world data, and how can organizations ensure that fabricated data doesn't inadvertently resemble or expose real individuals' identities? Speakers: Ulf Mattsson, CTO, UlfMattsson.com John C. Checco, DSc. C|CISO, CISSP, CCSK, Board Certified QTE, Chapter President, ISSA NY Metro Ariel Evans, CEO and Co-Founder, RiskQ Inc. Dr. Daniel O’Connell, EdD, MS, CDPSE, ITIL, HDPCA, Principal/Founder & CEO, DocLogical, LLC & Quinnipiac University Claude Baudoin, Co-Chair, Owner and Principal Consultant, OMG Cloud Working Group, cébé IT & Knowledge Management Archived until: 12:00pm CT on 3 March 2027