Securing AI: From Models to Agents

Honghui Xu's IntelliTrust Lab
  • 0.0 (0)
  • Technology

AI is rapidly evolving from chatbots to autonomous agents. But as these systems become more capable, they also become more vulnerable. Hosted by Dr. Honghui Xu and his PhD students, this podcast explores the foundations, attacks, defenses, and future of AI security. Through research-driven discussions, we break down topics such as prompt injection, indirect attacks, multi-agent security, backdoors, model robustness, and secure AI deployment. Whether you’re a researcher, engineer, student, or simply curious about the future of AI, this podcast helps you understand how to build and secure the

Episodes

  1. Industry Reality: What Big Tech Is Actually Doing

    Jun 12

    Industry Reality: What Big Tech Is Actually Doing

    In Episode 8, host Honghui Xu talks with Shiva Shrestha and Kazi Sharif about what big tech companies are actually doing for AI security. They discuss real-world practices, challenges, and lessons from industry AI deployments.

    33 min
  2. Build a Secure Physical AI System under Real-world Constraints?

    Jun 12

    Build a Secure Physical AI System under Real-world Constraints?

    In Episode 12, host Honghui Xu talks with Shiva Shrestha about building a secure Physical AI systems under real-world constraints. They discuss how to balance security, usability, cost, and performance in practical AI deployments.

    19 min
  3. Hidden in Meaning: The Next Generation of Backdoor Attacks

    Jun 12

    Hidden in Meaning: The Next Generation of Backdoor Attacks

    In Episode 11, host Honghui Xu talks with Tahmid Imtiaz Imu about backdoor attacks in LLM agents. They discuss how hidden triggers can affect agent behavior and why detecting these attacks is important for building safer AI systems.

    19 min
  4. When LLMs meet Quantum: Model-Level Defense

    Jun 12

    When LLMs meet Quantum: Model-Level Defense

    In Episode 10, host Honghui Xu talks with Emama Nahid about model-level defense for LLMs. They discuss how quantum-inspired ideas can help improve model robustness and security.

    16 min
  5. Detection-Based Defense for Multimodal LLMs

    Jun 12

    Detection-Based Defense for Multimodal LLMs

    In Episode 9, host Honghui Xu talks with Md Abdullahil Oaphy about detection-based defense for multimodal LLMs. They discuss how to detect risks across text and image inputs, and how these defenses can make multimodal AI systems safer and more trustworthy.

    23 min
  6. Defense Evolution: From Prompt Tricks to Architectural Security

    Jun 12

    Defense Evolution: From Prompt Tricks to Architectural Security

    In Episode 7, host Honghui Xu talks with Shiva Shrestha and Kazi Sharif about how AI security defenses are evolving. They discuss why prompt-based tricks are not enough and why stronger architectural security is needed for real-world AI systems.

    26 min
  7. Beyond Single Agents: Multi-Agent & System-Level Attacks

    Jun 12

    Beyond Single Agents: Multi-Agent & System-Level Attacks

    In Episode 6, host Honghui Xu talks with Shiva Shrestha and Kazi Sharif about multi-agent and system-level attacks. They discuss how attackers can exploit interactions between agents, tools, and systems, and why stronger system-level defenses are needed.

    23 min
  8. The Real Danger: Indirect Injection & Data Poisoning

    Jun 12

    The Real Danger: Indirect Injection & Data Poisoning

    In Episode 5, host Honghui Xu talks with Shiva Shrestha and Kazi Sharif about indirect injection and data poisoning. They discuss how these hidden attacks can compromise LLM systems and why they are difficult to detect and defend against.

    21 min
  9. Attacks on LLMs: From Prompt Injection to Agent Hijacking

    Jun 12

    Attacks on LLMs: From Prompt Injection to Agent Hijacking

    In Episode 4, host Honghui Xu talks with Shiva Shrestha and Kazi Sharif about attacks on LLMs. They discuss prompt injection, jailbreaks, data leakage, and agent hijacking, and explain why these attacks matter for real-world AI systems.

    15 min
  10. The Root Cause: Why LLMs Are Fundamentally Vulnerable

    Jun 12

    The Root Cause: Why LLMs Are Fundamentally Vulnerable

    In Episode 3, host Honghui Xu talks with Shiva Shrestha and Kazi Sharif about why LLMs are fundamentally vulnerable. They discuss how these risks come from the way LLMs are trained, designed, and used in real-world AI systems.

    17 min
  11. The Five-Layer Stack: A New Lens for AI Security

    Jun 12

    The Five-Layer Stack: A New Lens for AI Security

    In Episode 2, host Honghui Xu talks with Shiva Shrestha and Kazi Sharif about the Five-Layer Stack as a new way to understand AI security. They discuss how different layers of AI systems create different risks and require different defenses.

    18 min
  12. From LLMs to Agents: Why Security is No Longer Just Text

    Jun 12

    From LLMs to Agents: Why Security is No Longer Just Text

    In Episode 1, host Honghui Xu talks with Shiva Shrestha and Kazi Sharif about how AI security changes as LLMs evolve into agents. They discuss why security is no longer just about text, but also about tools, actions, data, and real-world systems.

    27 min
  • 12 Episodes

About

AI is rapidly evolving from chatbots to autonomous agents. But as these systems become more capable, they also become more vulnerable. Hosted by Dr. Honghui Xu and his PhD students, this podcast explores the foundations, attacks, defenses, and future of AI security. Through research-driven discussions, we break down topics such as prompt injection, indirect attacks, multi-agent security, backdoors, model robustness, and secure AI deployment. Whether you’re a researcher, engineer, student, or simply curious about the future of AI, this podcast helps you understand how to build and secure the

Information