Virtual Summit: Cybersecurity Implications of AI

This session will explore how AI can be utilized to enhance organizational resilience, while addressing the associated challenges in threat detection, response, and human involvement.

Purk will discuss the evolution of AI-driven security measures to counter emerging cyber threats and consider the interplay between human factors and algorithmic precision. The discussion will offer practical insights into responsibly leveraging AI for sustainable digital security, addressing risks of automation and maintaining human trust.

Key takeaways:

• AI’s Role in Strengthening Cyber Defenses: How AI can provide scalable, proactive threat detection while maintaining the agility to adapt to new attack methods.
• Human Impact and AI in Security: The role of human oversight in managing AI-driven security and how organizations can mitigate human-centric vulnerabilities.
• Navigating Ethical and Operational Challenges: Balancing AI’s potential with the ethical and security implications of automated decisions within critical infrastructure.
• Foundations for an AI-Resilient Security Strategy: Key strategies for developing a security framework that integrates AI responsibly, upholds trust, and builds adaptability.

In this session, Dr. Anton Chuvakin of Google Cloud shares insights on:

• The AI security issues we should be discussing in 2025: Emerging threats and defense mechanisms.
• Lessons learned over the past three years: Key takeaways from AI security advancements and setbacks.
• Today’s practical and effective AI use cases: Real-world applications for improving cybersecurity.

Join Tim Morris for an engaging fireside chat on the transformative role of AI in modern security strategies. From AI-driven threats like deepfake phishing and adaptive malware to groundbreaking innovations in real-time visibility and continuous compliance, this session will explore how organizations can stay ahead in the battle between attackers and defenders.

The session will share insights into closing the external discovery gap, leveraging AI to move from reactionary incident response to proactive crisis management, and addressing ethical challenges like automation bias and AI governance. Walk away with actionable strategies to fortify your defenses, harness AI responsibly, and prepare for the future of cybersecurity. Whether you’re an IT leader, security professional, or innovator, this is a must-attend session to navigate AI’s transformative impact on information security.

The potential for bias in AI algorithms, often stemming from training data, can lead to discriminatory or unfair outcomes, such as biased profiling or misclassification of threats. The opaque “black box” nature of many AI systems complicates these issues, making it difficult to understand how decisions are made, which can erode trust and hinder accountability. This session will explore the critical ethical considerations of deploying AI in cybersecurity and provide strategies to develop and implement AI systems that are fair, transparent, and trustworthy. 

You Will Learn: 

• Identifying and Mitigating Bias: Recognize how bias can infiltrate AI systems, leading to unfair outcomes in cybersecurity, and learn practical methods to identify and mitigate these biases to ensure fairness. 
• Enhancing Transparency: Understand the importance of transparency in AI models and how to implement practices that make AI decision-making processes more interpretable and accountable. 
• Balancing Privacy and Security: Explore the ethical balance between robust cybersecurity measures and protecting individual privacy, ensuring that AI systems do not overstep boundaries and infringe on personal rights. 
• Establishing Accountability Frameworks: Learn how to create and implement accountability frameworks that define responsibility for AI-driven decisions, ensuring ethical practices are maintained throughout your organization. 

It is a sophisticated weapon that is difficult to detect because proliferation of AI tools that are weaponized to create fake voice, content and profiles.

This fireside chat will delve on the use of AI tools used to developed deepfakes, how we can detect and control and the role of both private and public sector to combat these ever evolving issue.

The session will discuss:  

• How to build your defense strategy against AI’s weaponization;
• Developing a proactive crisis response to manage deepfake incidents;
• Using AI to assess deepfakes risks;
• Assessing the compatibility of the business privacy calculus framework with evolving technological landscapes and anticipate future privacy risks and opportunities

AI’s ability to mimic biometrics and exploit identity proofing tools is driving a rise in identity-related suspicious activity, accounting for nearly 75% of suspicious activity reports filed by banks. While AI presents new risks, it also offers promising defenses, such as AI-powered liveness detection for biometrics and risk analytics. Yet, these tools alone will not suffice in combating increasingly sophisticated AI-driven attacks. 

This session will explore the urgent need for financial services firms to embrace public key cryptography and digitally signed credentials, such as mobile driver’s licenses (mDLs), to enhance identity verification and thwart AI-enabled adversaries. We’ll discuss the role of phishing-resistant authentication solutions rooted in public key cryptography, along with recent government initiatives to accelerate the adoption of secure, privacy-preserving digital identities. Attendees will gain actionable insights on how to pair cryptographic defenses with biometric authentication, ensuring robust protection even as AI threats evolve.

Key Takeaways: 

• Combating AI-Driven Fraud: Strengthen identity verification systems to defend against AI-powered fraud by incorporating advanced authentication methods.
• Leveraging Public Key Cryptography: Implement digitally signed credentials, such as mobile driver’s licenses, to ensure secure, AI-resistant identity proofing. 
• Enhancing AI-Powered Defenses: Continuously update and refine liveness detection and risk analytics tools to stay ahead of increasingly sophisticated attacks.
• Fostering Government-Industry Collaboration: Advocate for partnerships to modernize legacy identity infrastructure and accelerate the adoption of AI-resistant solutions.

Supply chains are growing longer, involving numerous partners, multiple regions and a wide array of products. While these networks offer benefits like cost reduction and global reach, they also introduce significant cybersecurity risks.

Any disruption in the supply chain can have cascading effects, resulting in financial losses, reputational damage, and, in extreme cases, threats to national security. As traditional security measures prove inadequate, organizations are turning to artificial intelligence and machine learning (ML) solutions, though the implementation path remains complex and sometimes unclear.

The session will cover:

• Strategies for implementing AI-driven supply chain visibility and predictive analytics; 
• Methods for early detection and mitigation of supply chain vulnerabilities using AI;
• Frameworks for ensuring accountability and validation in AI-based threat detection systems.

Supercomputing, with its immense computational power, is crucial for training complex AI models and processing enormous amounts of data at unprecedented speeds. This partnership has far-reaching implications, from accelerating scientific research to improving real-time analytics across various sectors. This session will delve into the fusion of AI and supercomputing, offering insights into the latest advancements, strategic advantages, and how to harness this powerful combination for innovation.  

Key Takeaways:

• Supercomputing is pivotal in pushing the boundaries of AI with its ability to facilitate the training of massive models, faster simulations, and sophisticated data analysis, leading to groundbreaking innovations in multiple industries.
• Real-world use cases demonstrate the intersection of AI and supercomputing in areas such as drug discovery, climate modelling, financial forecasting, and autonomous systems, showcasing how this fusion is reshaping entire sectors.  
• We will address the technical and operational obstacles, including infrastructure costs, energy consumption, and the need for specialized expertise, and provide strategies to overcome these barriers.
• Gain insights into the future of AI and supercomputing, including emerging technologies like quantum computing and edge AI

Looking ahead to 2025, the use of AI in threat intelligence and automated response will undergo significant transformations, reshaping the tools, strategies and collaborative efforts aimed at combating advanced, AI-driven cyberattacks. Organizations need to adapt their security approaches to stay ahead of evolving threats while ensuring efficient and effective response mechanisms.

The session will cover:

• How to develop predictive threat intelligence frameworks for proactive defense;
• Methods for integrating AI-powered orchestration across security operations;
• Best practices for implementing and scaling Detection-as-Code solutions.

These AI-enabled cyber threats are not just theoretical; they are already being deployed to automate tasks like vulnerability scanning, phishing, and even bypassing traditional security measures with unprecedented precision. This session will dive into how adversaries are using AI to craft more personalized, adaptive, and stealthy attacks that can outmaneuver conventional defenses. We’ll examine real-world examples of AI-powered attacks an discuss actionable strategies to anticipate and counter these evolving threats. 

The session will cover:

• Identify the New AI Attack Vectors: Gain insight into the latest AI-powered attack vectors, including deepfakes, AI-generated phishing emails, and autonomous malware, and how they differ from traditional cyber threats. 
• Automation in Cybercrime: Understand how AI is automating and accelerating cyber attacks, enabling adversaries to conduct operations at a scale and speed previously unimaginable. 
• Adaptive Defenses: Explore proactive defense strategies, including the integration of AI in threat detection, response, and intelligence gathering, to stay ahead of increasingly sophisticated AI-driven threats. 
• Future-Proofing Security: Learn how to future-proof your organization’s cybersecurity posture by anticipating the next wave of AI-enabled cyber threats and developing resilient, adaptive defenses. 

This session will explore how AI and human expertise can complement each other, creating a more resilient and adaptive security framework. By leveraging AI’s analytical strengths alongside human intuition and contextual understanding, organizations can enhance their threat detection, response, and mitigation strategies. We will dive into best practices for designing workflows that maximize the strengths of both AI and human analysts, ensuring that your security team remains agile and effective. 

You Will Learn: 

• Combining AI and Human Expertise: Understand how to leverage AI’s analytical power and human intuition to enhance threat detection and response capabilities. 
• Optimizing Workflows: Learn how to design workflows that seamlessly integrate AI tools with human expertise, maximizing the strengths of both. 
• Training Your Team: Discover best practices for training and adapting your security team to work effectively alongside AI, fostering a culture of collaboration and continuous learning. 

For the success of Gen AI adoption, organizations must ensure that their IT infrastructure can support AI initiatives, including data management systems, computing power, and integration capabilities. 

The session will delve into the foundational elements required to build and maintain an AI infrastructure that can scale effectively with increasing data volumes, computational demands, and evolving business needs. It will cover the best practices for integrating scalable computing resources, data management systems, and robust architecture frameworks to ensure long-term AI success. 

Key Discussion Points: 

• Assessing the current AI infrastructure for implementing and scaling generative AI.
• Building a robust data architecture, including data storage, processing, and real-time analytics.
• Role of cloud to address the compute resources to support gen AI workloads. 
• Advanced security and compliance measures to protect sensitive data and AI models. 
• Addressing technology integration and change management issues.