This channel features presentations by leading experts in the field of information security. From application, computer, network and Internet security to access control management, data privacy and other hot topics, you will walk away with practical advice for your strategic and tactical information security initiatives.

Zero Trust Architectures (ZTA) have become a cornerstone of modern security strategies in the era of sophisticated cyber threats and ever-expanding and morphing attack surfaces. But how can organizations ensure their zero trust frameworks stay adaptive, intelligent, and resilient? Enter artificial intelligence (AI) and machine learning (ML)—the ultimate dynamic duo for elevating zero trust to the next level.

 This session delves into the powerful synergy between AI and ML and their role in strengthening zero trust principles. From real-time user behavior analysis and anomaly detection to predictive threat modeling and dynamic policy enforcement, AI and ML are transforming the way organizations approach security. Attendees will gain insights into practical use cases, including automating access controls, enhancing endpoint security, and optimizing network segmentation. Discover how these technologies can help your organization build a zero trust architecture that evolves with the threat landscape and ensures robust protection for your critical assets.

AI and ML: The Dynamic Duo for Strengthening Zero Trust Architecture

The evolving threat landscape requires security operations (SecOps) to move beyond traditional methods and embrace cutting-edge innovations. Generative AI is emerging as a game-changer, enabling security teams to automate and enhance threat intelligence processes with unprecedented speed and accuracy.

In this session, we will explore how generative AI tools transform SecOps by automating tasks such as malware analysis, threat report generation, and contextual threat modeling. Attendees will learn how to integrate generative AI into their SecOps workflows to improve detection, decision-making, and response times while reducing the burden on human analysts.

Generative AI in SecOps: Automating the Art of Threat Intelligence

As organizations race to adopt AI technologies, many overlook the complex -- and often vulnerable -- supply chains that power them. From open-source libraries and training data to model hosting and deployment pipelines, every layer introduces potential risk. 

This talk from industry thought leader Yesenia Yser will unpack the anatomy of the AI supply chain and expose the weak points most commonly exploited by threat actors, including prompt injection, model poisoning, and malicious dependencies. She’ll examine real-world examples that illustrate how these risks manifest and offer practical strategies to fortify your AI stack -- from secure development practices and component validation to continuous monitoring and governance. 

Whether you're an AI engineer, cybersecurity professional, or technical leader, this session will provide the insights and tools needed to secure your AI systems against emerging threats and maintain trust in open-source intelligence.

Unpacking the AI Supply Chain: Strategies to Fortify Open Source Intelligence

In the ever-evolving landscape of DevOps, the paradigm is now shifting - where security is taking the central stage. With vast surface areas including containers, cloud, repositories and third-party components, cyber threats became more prominent than ever before in DevOps.

This presentation will delve into the evolution from traditional DevOps to the advanced usage of artificial intelligence (AI) technologies to automate and optimize the software development and delivery processes. This includes automating code scanning, testing and deployment processes while eliminating the threats in each possible way in the cycle.

In this session, join Jyotirmayee Pradeep Kumar (Vice President - Cloud DevOps at a well-known global bank) as she unravels the stages of integration of AI at each phase of DevOps. Topics for discussion include:
- Types of AI used in DevOps.
- Benefits of using AI in DevOps.
- Implementation of AI in DevOps.
- Best practices for using AI in DevOps.
- Eliminating security threats using AI in DevOps.

Security Risks to Consider with AI Integration: AI in DevOps

Traditional penetration tests often miss the mark, failing to replicate the real-world tactics of today's sophisticated threat actors. In this session, Alex Holden, CISO of Hold Security, cuts through the noise and reveals how to transform your pen testing program with actionable threat intelligence.

You'll discover the latest attack trends and learn practical methods to simulate realistic cyber threats against your own defenses. From vulnerability exploitation to ransomware and social engineering, this session provides a hands-on guide to assessing your security readiness against the attacks that matter most right now. Leave with a clear roadmap to build a more resilient and threat-informed security posture.

Key Takeaways

- Understand the limitations of traditional pen testing and why threat intelligence is crucial
- Learn practical techniques for incorporating real-world attack simulations into your security assessments
- Gain a framework for building a more resilient and proactive security posture based on actionable threat intelligence

Smarter Pen Testing with Threat Intel

From data breaches to ransomware attacks, the cost of cybercrime is skyrocketing, demanding a new approach to security. Playing defense is no longer enough. Organizations need to anticipate threats and build resilience into their systems.  

CISOs and security leaders face immense pressure to stay ahead of the curve and build resilient organizations capable of withstanding and recovering quickly from security breaches. A product-led approach offers a proactive, data-driven solution for incident response, transforming security events into opportunities for continuous improvement. 

In this session, Oksana Denesiuk, product lead for billing and payments at Kaiser Permanente and ISSA Advisory Board Member, explores how cybersecurity teams can adopt a product mindset to enhance incident response, leveraging agile methodologies, iterative learning, and customer-centric thinking. 

Key Takeaways
- Embrace a product-centric approach to incident response, treating security incidents as valuable data points for continuous improvement.
- Integrate automated threat detection, secure coding practices, and incident learnings into the product roadmap.
- Use post-incident analytics, telemetry, and threat intelligence to refine security controls, enhance detection capabilities, and reduce the attack surface.
- Implement AI-driven detection, automated remediation workflows, and security orchestration (SOAR) to improve MTTR and MTTD.

Turning Incidents into Insights: A Product-Led Approach to Incident Response

As digital transformation accelerates and cloud-native applications become the new norm, application security faces a constantly evolving threat landscape. This session from TD Bank's Pankul Chitrav explores how organizations can adapt their security posture to defend against increasingly sophisticated attacks, from zero-day exploits to API abuse and supply chain vulnerabilities. We’ll outline modern security frameworks, such as DevSecOps and zero trust, and highlight practical strategies to embed security into every stage of the application lifecycle. 

Learn how to future-proof your security architecture and maintain resilience in the face of persistent and emerging threats.

Future-Proof Your Security Architecture Against Today's Persistent Threats

Application security remains one of the most complex challenges in cybersecurity. Unlike traditional infrastructure, applications are difficult to test across all possible attack vectors, and security failures can lead to devastating breaches. 

Tune into this session led by CISO Alex Holden as he explores emerging threats based on insights from the dark web and real-world incident response cases. The webinar will also dive into vulnerabilities of various application environments, flaws in business logic, next-generation penetration testing scenarios, and the evolving risks of AI manipulation by threat actors. 

Join us to uncover how attackers are targeting applications in 2025 -- and how to stay ahead.

Smarter App Security Strategies to Enhance Today’s Cyber Defense

Most organizations operating web and mobile applications focus on identity proofing and authenticating customers. However, as phishing schemes become more advanced, customers also need organizations to better "prove you are you" before they are willing to engage and share sensitive information. 

Tune into this session presented by Lucy Yang and Kaliya Young, partners from Identity Woman in Business, as they speak about experiences interacting with a scam chatbot and the lack of intuitive ways for customers to know whether they are engaging with a legitimate human or AI agent of an application. They’ll also explore organizational identity which has been one area of focus of the EU Digital Identity Wallet Large-Scale Pilots. As standards mature around digital wallets, it is time for organizations at large to think about how an organizational wallet can help you address identity and cybersecurity threats. 

Key Takeaways:
- Understand the business risks caused by not being able to "prove you are you" .
- Learn about the emerging topic of organizational identity and mutual authentication.
- Discover the organizational digital identity wallet and the technical standards that underpin it.

The "Proving You Are You" Problem for Organizations

Threat detection solutions come in many forms; extended detection and response (XDR), endpoint detection and response (EDR) and network detection and response (NDR). When it comes to detecting threats to an organization each of these “DRs” identifies specific elements of an attack path, but they may be lacking visibility into application-specific threats because these solutions see an application as a “black-box”. 

This session covers Application detection and response (ADR) solutions which look for vulnerabilities and exploits within the application itself. 

Key takeaways:
- Understand how ADR observes and analyses applications bringing visibility and context down to the code level. 
- How to contrast ADR with application layer coding verification mechanisms such as RASP, SCA, SAST and DAST.
- Understand how ADR differs from deploying a WAF or CNAPP solution.
- Learn how ADR observations and context can be integrated with the other ”DRs” to build a more complete picture of an attack to ensure an end-to-end response.

About the Speaker
Natalie is a Security and Compliance Consultant that has been involved in security technologies for more than 20 years. Natalie has advisory and engineering experience in multi-vendor network security architecture and deployment, security compliance and governance, security analytics and threat detection and response. Natalie was a former Program Leader for the CCIE Security certification track and has been a keynote speaker at various Cybersecurity events both in the US and Australia.

Natalie is also a three-time Cisco Distinguished Speaker award winner, a published author with Cisco Press and a freelance technical writer and presenter.

ADR: Not Just “Another” Detection and Response Solution

As cyber threats continue to evolve and breach traditional network boundaries, organizations face mounting pressure to adopt zero-trust architecture (ZTA) – not just as a security framework, but as a federal mandate. This paradigm shift recognizes that threat actors can emerge from anywhere – whether inside your trusted network or beyond its boundaries – demanding a complete rethinking of security monitoring strategies. 

While the zero-trust mandate establishes clear objectives for security models and system design principles, many organizations struggle with practical implementation, particularly in network security monitoring (NSM). Traditional NSM tools, designed for perimeter-based security models need to evolve to meet ZTA requirements. This session critically examines popular open-source NSM solutions, evaluating their readiness for ZTA implementation and exploring the necessary evolution of monitoring principles to support a true zero-trust environment. 

Join ESnet/LBNL Security Engineer, Fatema Bannat Wala for an in-depth analysis of the challenges and opportunities in adapting existing NSM tools for ZTA. 

Key Takeaways: 
- Understand the core principles of ZTA and how they fundamentally differ from traditional security monitoring approaches. 
- Evaluate the capabilities and limitations of current open-source NSM tools in supporting zero-trust implementation.
- Learn critical monitoring principles that need to evolve to align with ZTA requirements and federal mandates. 
- Gain practical insights into assessing your organization's readiness for ZTA and identifying necessary technological adaptations.

Zero-Trust Architecture: Bridging the Gap Between Mandate and Implementation

The use of AI or Machine Learning is changing the way people work. 69% of organizations say they can't handle cyber threats without AI help. To best leverage AI's ability to improve threat detection accuracy while reducing false positives requires human-AI collaboration. By combining the ingenuity and experiences of human analysts with the speed and efficiency of AI analytic tools will improve threat intelligence operations.   

The presentation professor and consultant Charles Kolodgy will provide useful insight and information, including examples, on how tailoring your threat intelligence program to leverage the best attributes of man and machine will ensure your program is efficient, strategic, and ethical. 

Join this discussion to learn:
- A quick review of threat intelligence.
- Examples of how AI has been used to enhance threat intelligence analysis.
- Discuss what tools and options are available for leveraging human-AI collaboration for the processing of threat intelligence.
- Provide some examples of how man and machine have been combined to improve threat intelligence.

Using Man and Machine to Improve Threat Intelligence Efficiency

As cyber threats grow increasingly sophisticated, traditional reactive approaches to security are no longer sufficient. Proactive defense strategies, powered by artificial intelligence (AI), are revolutionizing how organizations detect, mitigate, and respond to threats. This session explores how AI can predict and prevent potential attacks by analyzing patterns, identifying vulnerabilities, and automating preemptive actions.

Attendees will gain insights into the technologies behind predictive threat mitigation, including machine learning models, behavioral analytics, and anomaly detection. We will discuss how organizations can use AI to anticipate threats, minimize risks, and enhance incident response.

Proactive Defense: Leveraging AI for Predictive Threat Mitigation and Response

Cyber attackers are leveraging advanced technologies to breach systems, but defenders are fighting back with AI-powered solutions. 

This presentation from TD Bank's Pankul Chitrav will explore how AI enhances cyber resilience by automating detection, response, and recovery processes. She will analyze how AI models identify subtle anomalies, mitigate risks in real-time, and enable continuous learning to adapt to new threats. Attendees will gain insights into best practices for integrating AI into existing security architectures.

Automated Defense: AI’s Role in Proactive Cyber Threat Mitigation

The EU is ahead of the US when it comes to AI regulation. As my fellow conference attendee in Amsterdam quipped last year “Americans innovate, Chinese replicate and the Europeans regulate”. While the US still must come up with a federal-wide law, the EU already came up with the EU AI Act in 2023. This is mandatory in all 27 full-fledged member states with over 449 million people. Another EU-birthed AI framework is gaining popularity. The ISO 42001, or the Artificial Intelligence Management System, was finalized in the Geneva, Switzerland-based International Standards Organization (ISO) also in the same year. Combined, these provide, a promising way to mitigate AI security risks among other benefits. 

In this presentation, industry thought leader Ralph Villanueva will highlight the relevant aspects of these two regulatory frameworks and how they can successfully mitigate AI security risks in your organization.

Using the EU Approach to Mitigate AI Security Risks

Microsoft Tay's infamous descent into unintended behavior serves as a stark reminder of AI's potential vulnerabilities in cybersecurity contexts. 

This webinar from industry thought leader John Bambenek explores key lessons from Tay’s deployment, highlighting the importance of safeguarding AI systems from exploitation and model poisoning. Participants will gain insight into managing AI securely by employing resource-augmented generation grounded in trusted frameworks like MITRE ATT&CK, D3FEND, and the NIST Cybersecurity Framework (CSF). Learn how these methodologies empower cybersecurity analysts to rapidly, accurately, and securely interpret security events, preventing adversaries from compromising AI integrity. 

Discover practical strategies for ensuring your organization's AI systems remain resilient against sophisticated AI-driven cyberattacks as well as how to transform the security operations center (SOC) from alert triage into a security program that stops the actual attackers targeting your organization.

What Microsoft Tay Teaches Us About Using AI Safely For Cybersecurity

AI-powered content generation introduces security risks, including data leakage, prompt injection, adversarial misuse, and compliance gaps. Companies using AI APIs from providers like OpenAI and Claude must address these vulnerabilities to prevent unauthorized data access and model exploitation.

This session breaks down real-world attack scenarios, including users manipulating AI prompts to extract sensitive information and API endpoints being exploited for adversarial attacks. We will introduce a structured AI security framework and a conceptual product design for mitigating these risks.

Attendees will learn how to implement real-time AI monitoring, enforce API-level security controls, and automate content governance to protect their systems without limiting AI-driven innovation.

Mitigating AI Security Risks in Content Generation: Securing API-Based AI Systems

In the ever-evolving landscape of DevOps, the paradigm is now shifting - where security is taking the central stage. With vast surface areas including containers, cloud, repositories and third-party components, cyber threats became more prominent than ever before in DevOps.

This presentation will delve into the evolution from traditional DevOps to the advanced usage of artificial intelligence (AI) technologies to automate and optimize the software development and delivery processes. This includes automating code scanning, testing and deployment processes while eliminating the threats in each possible way in the cycle. 

In this session, join Jyotirmayee Pradeep Kumar (Vice President - Cloud DevOps at a well-known global bank) as she unravels the stages of integration of AI at each phase of DevOps. Topics for discussion include:
- Types of AI used in DevOps. 
- Benefits of using AI in DevOps.
- Implementation of AI in DevOps.
- Best practices for using AI in DevOps.
- Eliminating security threats using AI in DevOps.

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