Track 5: Security, Trust & Governance

There are numerous well-founded concerns around transparency, biases, regulatory compliance, security threats, and ethics associated with AI. The growing scale of models (especially GenAI models) means that are often viewed as black boxes with limited transparency – this limitation is especially important when the outcomes of the model have major human consequences, whether being turned down for a loan or given an assessment of the likelihood of cancer. The outcry for better trust and governance has led to a push for explainable solutions and an emphasis on human-in-the-loop augmentation, rather than pure unsupervised automation for high risk use cases. This track will cover the technologies and strategies required to mitigate the range of risks associated with AI. 

Key Themes:

1. Adaptive Threat Detection: Explore the realm of AI-powered adaptive threat detection. Learn about advanced techniques for identifying and responding to cyber threats in real-time, leveraging AI's analytical prowess.
2. AI in Malware Defense: Dive into the frontlines of defense against malware and cyberattacks. Uncover how AI can rapidly identify and neutralize malware threats, securing networks and data.
3. AI-Enhanced Security Analytics: Discover the power of AI in enhancing security analytics. Explore how machine learning and data analysis can extract actionable insights from vast datasets, facilitating proactive cybersecurity measures.
4. AI-Driven Incident Response: Learn about AI's transformative role in incident response. Explore automated incident handling, threat hunting, and AI-driven decision support systems for effective responses to security incidents.
5. Securing IoT with AI: Examine the convergence of AI and the Internet of Things (IoT) in the context of cybersecurity. Understand how AI safeguards IoT devices, networks, and ecosystems from vulnerabilities.
6. Ethical Hacking and AI: Delve into the ethical hacking domain enriched by AI. Discover how AI is utilized to conduct penetration testing, vulnerability assessments, and security audits to identify weaknesses before malicious actors do.
7. AI-Powered Identity and Access Management: Explore the future of identity verification and access control using AI-driven biometrics, behavior analysis, and adaptive authentication methods.
8. AI in Threat Intelligence: Stay ahead of cyber threats with AI-driven threat intelligence. Learn how machine learning and natural language processing transform threat data into actionable insights for decision-makers.

Who Should Attend:

• Cybersecurity professionals and experts
• AI and machine learning practitioners
• Security analysts
• Incident responders
• IoT security specialists
• Ethical hackers and penetration testers
• Identity and access management professionals
• Decision-makers and policymakers in the cybersecurity landscape

Join us in the Security, Trust & Governance track to explore the synergistic relationship between AI and cybersecurity, share knowledge, and collaborate with industry leaders. Together, we'll fortify the digital realm and shape a more secure cyber landscape.