GEN AI Security two-hour live webinar

AI is revolutionizing industries, but it also introduces new security challenges. This webinar explores AI security risks, attack vectors, governance frameworks, and future threats. Learn from experts how to safeguard AI systems against cyber threats, adversarial attacks, and compliance risks.

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Course Overview

General Description:

Gen AI Security Webinar: Understanding Risks, Threats & Future Trends

✅ As AI continues to evolve, so do the security challenges that come with it. This comprehensive webinar explores the current landscape of AI security, major threats, attack vectors, and governance frameworks while providing insights into the future of AI-driven cybersecurity.

Course Objectives

Understand AI Security Risks & Challenges – Gain insights into the evolving threat landscape and how AI is both a security enabler and a target for cybercriminals.

Identify AI Attack Vectors & Surfaces – Learn about adversarial attacks, deepfakes, synthetic identity fraud, and how to implement threat modeling for AI systems.

Implement AI Security Best Practices – Explore Zero Trust AI architectures, ethical AI considerations, and strategies for securing AI models and data.

Navigate AI Governance & Compliance – Understand regulatory frameworks like the EU AI Act, NIST guidelines, and compliance best practices.

  • Trainer Profile :
    Rammohan is a highly accomplished Technology Leader and former Associate Directorat
    IBM/Kyndryl, boasting over 25 years of IT experience, including 17+ years inleadership
    roles across Hybrid-Cloud, Security & Managed Services in the EMEA and AP regions. He
    was rated as top people Manager at IBM/Kyndryl and led teams of 100+ reporting to him
    globally.
    Renowned as a technology trainer and coach, he excels in simplifying complex concepts
    in Gen AI, Hybrid Multi-Cloud, AI Security & ICS/OT Security empowering organizations
    and professionals to harness innovation effectively

Target Audience / Prerequisites

To ensure participants are well-prepared and can fully benefit from the course, the following prerequisites are recommended:

  • Any one interested  in AI Security as a career  – From early stage professionals to experienced pros.

  • Familiarity with cybersecurity principles

  • Knowledge of cloud computing & DevOps is a plus

  • Experience with programming (Python preferred) is beneficial but not mandatory

Certification

Sample Certificate

Course Duration & Course Schedule Date

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Course Outline

AI Security - Current Landscape ( 30 Min)
⦁ AI Security - Introduction
⦁ How AI is Reshaping Security Strategies
⦁ How Cybercriminals & Nation-States (APT's) Weaponize AI
⦁ Real-World Case Studies / Examples of Complex Security Breaches
AI Security - Attack Vectors & Attack Surfaces ( 30 Min)
⦁ Threat Modeling in AI Security
⦁ Deepfake & Synthetic Identity Threats
⦁ Zero Trust AI Security Architecture
AI Governance & Compliance ( 15 min)
⦁ AI Governance & Compliance (EU AI Act, NIST, etc.)
The Future of AI Security ( 30 min)
⦁ The AI Security Arms Race
⦁ Sovereign AI & Data Embassies
⦁ Red Teaming with AI
⦁ Quantum Threats to AI Security
Q & A ( 15 min)

Review

Shaik Abdullah (Visteon)
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Overall experience is very good. Guidelines given by trainers were excellent. It is well designed course with practical orientation
Lipsa Tripathy (Mindtree Ltd)
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All of the trainers were excellent, extremely professional and knowledgeable and created positive learning environments.
Rajeev (CSC India Pvt)
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I thoroughly enjoyed this training. The tutor's attitude was exemplary. He displayed a good knowledge of the subject and built up a rapport with the attendees in no time.
Priyanka Mishra (GI)
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This place is great for doing corporate training- a central location and well equipped. Good facilities for lunch and with good travel links - an ideal venue
Sourav (Mindtree Ltd)
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Very well organised and implemented. A lot of lessons learned. The training was commendable and the trainers were also professional. Overall a good experience.
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FAQ

AI systems face risks like data poisoning, adversarial attacks, model theft, and bias exploitation.

Implement secure coding practices, encryption, access controls, and continuous monitoring to safeguard AI models.

  • Ethical AI helps reduce bias, ensure transparency, and build trust, making AI systems more secure and reliable.

AI enhances threat detection, automates security responses, and improves fraud prevention through predictive analysis.

  • Yes, frameworks like GDPR, NIST AI RMF, and ISO/IEC 27001 guide AI security and compliance

GEN AI Security two-hour live webinar

23rd April 2025 | 11:00 AM to 1:00 PM | online mode 

Special Offer for limited seats only… Hurry Up!!!

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