AI in Cyber Online schedule

• Exploring real-world examples of how AI technologies are transforming cybersecurity landscape
• Showcasing successful case studies across different sectors, emphasizing innovation and measurable outcomes
• Navigating evolving cyber threats in real time with AI-driven cybersecurity systems

Like all technology, AI/ML can be used for good and bad. In this session we will explore a few use cases of how the adversaries are leveraging AI/ML and demonstrate how the defenders are leveraging this technology to protect against such AI/ML powered attacks. In conclusion, we will leave the audience with suggested next steps and use-cases for enabling the safe use of Generative AI and discuss the core capabilities required to do so.

• Examining collaborative efforts between government agencies, industries, and academia
• Discussing how these partnerships are driving innovation in cybersecurity research, development, and implementation
• Understanding the role of public-private partnership to foster effective collaboration in implementing intelligent cybersecurity solution

Panellists:

• Saiful Bakhtiar Osman, Head of IT, Shared Services, PNB Commercial
• Indra Adillah, Head of ICT, AirAsia Indonesia
• Phil Ross, CISO, Air New Zealand

As technology advances, both cybersecurity measures and cyber threats evolve in tandem. The integration of artificial intelligence (AI) into cybersecurity strategies has brought about new challenges and opportunities. This topic explores the dual nature of AI in cybersecurity, focusing on how adversaries leverage AI-driven tactics and techniques to orchestrate sophisticated attacks, while also examining defensive strategies aimed at thwarting such malicious activities. By addressing both the offensive and defensive aspects of AI in cybersecurity, this topic provides insights into the ongoing arms race between cybercriminals and defenders, highlighting the importance of staying vigilant and adaptive in the face of evolving cyber threats

• Adversarial AI Tactics: Delve into how malicious actors harness AI to enhance the efficacy of cyber attacks, including the use of AI-powered malware, phishing campaigns, and automated evasion techniques. Machine Learning in Attack Scenarios: Explore real-world examples of how machine learning algorithms are exploited by cybercriminals to bypass traditional security measures, such as intrusion detection systems and anti-virus software
• Generative Adversarial Networks (GANs): Investigate the role of GANs in generating convincing fake data, enabling adversaries to craft realistic phishing emails, deepfake videos, and other deceptive content to manipulate victims
• Defending Against Adversarial AI: Discuss proactive defense strategies and countermeasures that organizations can employ to mitigate the risks posed by AI-driven cyber threats, including the use of AI-powered defense systems, anomaly detection algorithms, and adversarial training techniques. 
• Ethical and Regulatory Considerations: Examine the ethical implications of using AI in cybersecurity, such as ensuring transparency, accountability, and fairness in AI-powered defense systems. Additionally, discuss regulatory frameworks and best practices for promoting responsible AI usage in cybersecurity operations.

• Focusing on the unique challenges and opportunities in securing critical infrastructure using AI technologies
• Discussing case studies, strategies, and best practices for leveraging AI to protect essential services in APAC

• Examining the use of AI-powered behavioural analytics to detect and prevent insider threats
• Discussing how machine learning algorithms can analyse user behaviour patterns, identify anomalies
• Enhancing the ability to pre-emptively address potential insider risks in organizations