Vaibhav Malik
Vaibhav Malik, Partner Solutions Architect, Cloudflare
St. Louis, Missouri, United States
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Vaibhav Malik is a Global Partner Solution Architect at Cloudflare, where he works with global partners to design and implement effective security solutions for their customers. With over 12 years of experience in networking, security, and cloud technologies, Vaibhav is a recognized industry thought leader and expert in Zero Trust Security Architecture for modern, distributed systems.
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Securing the AI Frontier: Challenges and Strategies in LLM and AI Security
As Artificial Intelligence (AI) and Large Language Models (LLMs) become increasingly integrated into business operations and decision-making processes, they present novel security challenges that traditional cybersecurity approaches are ill-equipped to handle. This presentation delves into the unique security landscape of AI systems, with a particular focus on LLMs. We will explore potential vulnerabilities, attack vectors, and defensive strategies, providing attendees with a comprehensive understanding of how to secure AI assets in their organizations.
Securing the AI Frontier: Challenges and Strategies in LLM and AI Security
As Artificial Intelligence (AI) and Large Language Models (LLMs) become integral to modern business operations, they introduce unprecedented security challenges that traditional cybersecurity measures struggle to address. This presentation explores the unique security landscape of AI systems, with a particular focus on LLMs, unveiling potential vulnerabilities and attack vectors that security professionals must be prepared to confront.
We will delve into critical issues such as data poisoning, model inversion, prompt injection, and the privacy implications of AI systems. Special attention will be given to LLM-specific challenges, including hallucination, unauthorized data disclosure, and the potential for misuse in creating malicious content.
Through a combination of technical insights and strategic considerations, attendees will gain a comprehensive understanding of how to secure AI assets within their organizations. We'll examine defensive strategies, best practices for robust ML model development, and the importance of ethical considerations in AI deployment.
Real-world case studies will illuminate the practical applications of these concepts, while a look at emerging trends will prepare attendees for the future of AI security. This session aims to equip information security professionals, AI/ML engineers, and decision-makers with the knowledge and tools necessary to navigate the complex intersection of AI and cybersecurity effectively.
Securing the AI Frontier: Challenges and Strategies in LLM and AI Security
As Artificial Intelligence (AI) and Large Language Models (LLMs) become integral to modern business operations, they introduce unprecedented security challenges that traditional cybersecurity measures struggle to address. This presentation explores the unique security landscape of AI systems, with a particular focus on LLMs, unveiling potential vulnerabilities and attack vectors that security professionals must be prepared to confront.
We will delve into critical issues such as data poisoning, model inversion, prompt injection, and the privacy implications of AI systems. Special attention will be given to LLM-specific challenges, including hallucination, unauthorized data disclosure, and the potential for misuse in creating malicious content.
Through a combination of technical insights and strategic considerations, attendees will gain a comprehensive understanding of how to secure AI assets within their organizations. We'll examine defensive strategies, best practices for robust ML model development, and the importance of ethical considerations in AI deployment.
Real-world case studies will illuminate the practical applications of these concepts, while a look at emerging trends will prepare attendees for the future of AI security. This session aims to equip information security professionals, AI/ML engineers, and decision-makers with the knowledge and tools necessary to navigate the complex intersection of AI and cybersecurity effectively.
Securing the AI Frontier: Challenges and Strategies in LLM and AI Security
As Artificial Intelligence (AI) and Large Language Models (LLMs) become integral to modern business operations, they introduce unprecedented security challenges that traditional cybersecurity measures struggle to address. This presentation explores the unique security landscape of AI systems, with a particular focus on LLMs, unveiling potential vulnerabilities and attack vectors that security professionals must be prepared to confront.
We will delve into critical issues such as data poisoning, model inversion, prompt injection, and the privacy implications of AI systems. Special attention will be given to LLM-specific challenges, including hallucination, unauthorized data disclosure, and the potential for misuse in creating malicious content.
Through a combination of technical insights and strategic considerations, attendees will gain a comprehensive understanding of how to secure AI assets within their organizations. We'll examine defensive strategies, best practices for robust ML model development, and the importance of ethical considerations in AI deployment.
Real-world case studies will illuminate the practical applications of these concepts, while a look at emerging trends will prepare attendees for the future of AI security. This session aims to equip information security professionals, AI/ML engineers, and decision-makers with the knowledge and tools necessary to navigate the complex intersection of AI and cybersecurity effectively.
Securing the AI Frontier: Challenges and Strategies in LLM and AI Security
As Artificial Intelligence (AI) and Large Language Models (LLMs) become integral to modern business operations, they introduce unprecedented security challenges that traditional cybersecurity measures struggle to address. This presentation explores the unique security landscape of AI systems, with a particular focus on LLMs, unveiling potential vulnerabilities and attack vectors that security professionals must be prepared to confront.
We will delve into critical issues such as data poisoning, model inversion, prompt injection, and the privacy implications of AI systems. Special attention will be given to LLM-specific challenges, including hallucination, unauthorized data disclosure, and the potential for misuse in creating malicious content.
Through a combination of technical insights and strategic considerations, attendees will gain a comprehensive understanding of how to secure AI assets within their organizations. We'll examine defensive strategies, best practices for robust ML model development, and the importance of ethical considerations in AI deployment.
Real-world case studies will illuminate the practical applications of these concepts, while a look at emerging trends will prepare attendees for the future of AI security. This session aims to equip information security professionals, AI/ML engineers, and decision-makers with the knowledge and tools necessary to navigate the complex intersection of AI and cybersecurity effectively.
Securing the AI Frontier: Challenges and Strategies in LLM and AI Security
As Artificial Intelligence (AI) and Large Language Models (LLMs) become integral to modern business operations, they introduce unprecedented security challenges that traditional cybersecurity measures struggle to address. This presentation explores the unique security landscape of AI systems, with a particular focus on LLMs, unveiling potential vulnerabilities and attack vectors that security professionals must be prepared to confront.
We will delve into critical issues such as data poisoning, model inversion, prompt injection, and the privacy implications of AI systems. Special attention will be given to LLM-specific challenges, including hallucination, unauthorized data disclosure, and the potential for misuse in creating malicious content.
Securing the AI Frontier: Challenges and Strategies in LLM and AI Security
As Artificial Intelligence (AI) and Large Language Models (LLMs) become integral to modern business operations, they introduce unprecedented security challenges that traditional cybersecurity measures struggle to address. This presentation explores the unique security landscape of AI systems, with a particular focus on LLMs, unveiling potential vulnerabilities and attack vectors that security professionals must be prepared to confront.
We will delve into critical issues such as data poisoning, model inversion, prompt injection, and the privacy implications of AI systems. Special attention will be given to LLM-specific challenges, including hallucination, unauthorized data disclosure, and the potential for misuse in creating malicious content.
Through a combination of technical insights and strategic considerations, attendees will gain a comprehensive understanding of how to secure AI assets within their organizations. We'll examine defensive strategies, best practices for robust ML model development, and the importance of ethical considerations in AI deployment.
Real-world case studies will illuminate the practical applications of these concepts, while a look at emerging trends will prepare attendees for the future of AI security. This session aims to equip information security professionals, AI/ML engineers, and decision-makers with the knowledge and tools necessary to navigate the complex intersection of AI and cybersecurity effectively.
Securing the AI Frontier: Challenges and Strategies in LLM and AI Security
As Artificial Intelligence (AI) and Large Language Models (LLMs) become integral to modern business operations, they introduce unprecedented security challenges that traditional cybersecurity measures struggle to address. This presentation explores the unique security landscape of AI systems, with a particular focus on LLMs, unveiling potential vulnerabilities and attack vectors that security professionals must be prepared to confront.
We will delve into critical issues such as data poisoning, model inversion, prompt injection, and the privacy implications of AI systems. Special attention will be given to LLM-specific challenges, including hallucination, unauthorized data disclosure, and the potential for misuse in creating malicious content.
Through a combination of technical insights and strategic considerations, attendees will gain a comprehensive understanding of how to secure AI assets within their organizations. We'll examine defensive strategies, best practices for robust ML model development, and the importance of ethical considerations in AI deployment.
Real-world case studies will illuminate the practical applications of these concepts, while a look at emerging trends will prepare attendees for the future of AI security. This session aims to equip information security professionals, AI/ML engineers, and decision-makers with the knowledge and tools necessary to navigate the complex intersection of AI and cybersecurity effectively.
Implementing Zero Trust Architecture in OT/ICS Environments: Challenges and S
As cyber threats to industrial control systems continue to evolve, traditional perimeter-based security models are proving insufficient. This presentation explores the application of Zero Trust Architecture (ZTA) principles to Operational Technology (OT) and Industrial Control System (ICS) environments. We will discuss the unique challenges of implementing zero trust in industrial settings and provide practical strategies for enhancing security without compromising operational efficiency or safety.
Securing Open Source AI Frameworks and Workflows: Best Practices and Emerging Trends
In this presentation, we will explore the key security challenges facing open source AI and discuss best practices for mitigating these risks. We will cover topics such as:
Common security vulnerabilities in popular open source AI frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
Securing AI development workflows, including data pipelines, model training, and deployment
Implementing secure coding practices and conducting security audits for AI codebases
Managing dependencies and mitigating risks from third-party libraries and tools
Protecting sensitive data used in AI training and inference, including techniques like differential privacy and federated learning
Addressing privacy concerns and complying with relevant regulations (e.g., GDPR, CCPA) in AI contexts
Emerging trends and tools for enhancing AI security, such as confidential computing, trusted execution environments, and blockchain-based solutions.
Attendees of this presentation will leave with a deeper understanding of the security landscape in open source AI, as well as practical insights and strategies for building and deploying AI systems that are both innovative and secure.
Implementing Zero Trust for Hybrid and Multi-Cloud Kubernetes Deployments
Here's a potential description for the talk "Implementing Zero Trust for Hybrid and Multi-Cloud Kubernetes Deployments":
As organizations increasingly adopt Kubernetes across hybrid and multi-cloud environments, ensuring consistent security controls and zero-trust principles can be a daunting challenge. Different clusters, clouds, and on-prem infrastructure each introduce unique security considerations and complexities. How can we effectively implement zero-trust security in these heterogeneous environments?
In this talk, we'll explore the key security challenges of hybrid and multi-cloud Kubernetes deployments and discuss best practices for implementing consistent zero-trust controls across diverse infrastructures.
Highlight various open source tools and technologies, such as Istio, Cilium, Open Policy Agent, Kubernetes Federation, and multi-cluster management platforms like Rancher and Anthos, that can help address these challenges.
SSANS CloudSecNext Summit 2024
The rapid advancements in Generative AI have opened up a new frontier in cybersecurity, presenting both unprecedented opportunities and daunting challenges. This presentation aims to equip attendees with the critical knowledge and tools needed to navigate the evolving threat landscape shaped by the rise of AI-powered cyber attacks. The session will delve into the dark side of Generative AI, showcasing how malicious actors are weaponizing this technology to create highly sophisticated phishing campaigns, develop advanced malware, and introduce novel attack methods such as LLM supply chain poisoning. Through live demonstrations and real-world examples, participants will gain a comprehensive understanding of the emerging risks associated with Generative AI in the context of cybersecurity. However, the presentation will also emphasize the importance of harnessing the potential of Generative AI responsibly to strengthen organizational defenses. Attendees will learn essential security strategies and best practices to fortify their systems against AI-driven threats, as well as techniques to identify and neutralize these evolving attacks proactively. By striking a balance between exploring the dark side of Generative AI and empowering participants to adapt their defenses accordingly, this session aims to foster a more secure and resilient cybersecurity landscape in the face of this transformative technology.
Generative AI: The Double-Edged Sword in Cybersecurity
Are you ready to face the impending surge of Generative AI-powered cyber threats? Join us as we arm you with the essential knowledge and tools to fortify your defenses against this rapidly evolving threat landscape. Together, we will explore:
The Dark Side of Generative AI: How Hackers are Weaponizing this Technology
Phishing Evolved: Witness how AI can generate highly convincing emails and social media posts that evade conventional detection techniques.
Malware on Steroids: Uncover the alarming trend of AI-driven malware development, resulting in faster and more advanced threats.
LLM Supply Chain Poisoning: Experience a LIVE demonstration of this groundbreaking attack method and grasp its far-reaching consequences.
Empowering Your Defenses & Harnessing the Potential of Generative AI Responsibly
Fortifying Your Fortress: Implement crucial security strategies to shield your organization from the onslaught of Generative AI-based attacks.
Staying Vigilant: Master the art of identifying and neutralizing these ever-evolving threats before they wreak havoc on your systems.
Lucy in the Cloud with Diamonds SecureWorld
Can you “imagine” if The Beatles, when first starting out, had to deal with having their catalog of music hacked, stolen, and held for ransom simply because it was in an unsecure cloud setting? While it is possible for that to happen with their hit-laden collection of songs today, it’s merely a tiny example of how businesses operate at a minimum in a hybrid cloud environment—many in a cloud-only platform.
With that comes security issues and another major area which cybersecurity professionals must work diligently to protect.
Our panel of experts share the good, the bad, and the ugly of operating in a cloud environment, what it takes to make the move to hybrid or multi-cloud successful, how to protect data from insider and outsider threats, and what it takes to provide the support DevOps teams need.
HTTP/2 Rapid Reset DDoS Attack: Detecting Zero-Days Before Zero-Day
1.) In today's rapidly evolving cyber threat landscape, the term "zero-day" sends shivers down the spines of security professionals. With the ever-increasing sophistication of attackers, the potential for a massive DDoS (Distributed Denial of Service) HTTP attack looms as a formidable threat.
2.) We'll explore how leveraging threat intelligence can provide the early warning signs necessary to thwart the largest DDoS HTTP attacks ever recorded.
Vaibhav Malik
Vaibhav Malik, Partner Solutions Architect, Cloudflare
St. Louis, Missouri, United States
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