AI for Security: How AI is Reshaping Cybersecurity

Agenda for the Masterclass

Introduction: The Security Landscape in the Age of AI
- Rise of AIdriven threats
- Why defenders need AI
- Overview of AI in SOCs and threat intelligence
AIPowered Threat Detection
- Machine learning for anomaly detection
- Behavioral analytics vs signaturebased defense
- Case study: AI in phishing and malware detection
Automating Incident Response
- SOAR (Security Orchestration, Automation, and Response)
- AIdriven triage and prioritization
- Reducing false positives and analyst fatigue
Offensive Use of AI in Security
- AIdriven reconnaissance: automated OSINT and vulnerability scanning
- Exploit generation using AI models
- Adversarial AI: crafting inputs to bypass detection systems
- Case study: AIassisted phishing campaigns and social engineering
Ethical and Operational Challenges
- Bias in AI models
- Data privacy and compliance
- Risks of dualuse AI (defensive vs offensive applications)
Demo / HandsOn Concept
- Example: Using an AI model to classify network anomalies (defense)
- Example: Simulating an AIgenerated phishing email (offense)
Introduction: Why AI Needs Security
- AI as a new attack surface
- Overview of AI system components (model, data, API, memory)
Threats to AI Systems
- OWASP Top 10 for LLM Applications
- Adversarial inputs, prompt injection, model poisoning
- Case study: Exploiting an AI chatbot
Securing the AI Pipeline
- Data validation and sanitization
- Model hardening and access control
- Secure deployment practices (sandboxing, API gateways)
Monitoring and Incident Response for AI
- Logging and anomaly detection for AI behavior
- Detecting prompt injection and data exfiltration
- Integrating AI security into SOC workflows
HandsOn Concept
- Simulated attack on an LLM and mitigation using guardrails

Why Attend This Masterclass

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Ashish Dhyani

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<ul>
<li>Introduction: The Security Landscape in the Age of AI
<ul>
<li>Rise of AIdriven threats</li>
<li>Why defenders need AI</li>
<li>Overview of AI in SOCs and threat intelligence</li>
</ul>
</li>
<li>AIPowered Threat Detection
<ul>
<li>Machine learning for anomaly detection</li>
<li>Behavioral analytics vs signaturebased defense</li>
<li>Case study: AI in phishing and malware detection</li>
</ul>
</li>
<li>Automating Incident Response
<ul>
<li>SOAR (Security Orchestration, Automation, and Response)</li>
<li>AIdriven triage and prioritization</li>
<li>Reducing false positives and analyst fatigue</li>
</ul>
</li>
<li>Offensive Use of AI in Security
<ul>
<li>AIdriven reconnaissance: automated OSINT and vulnerability scanning</li>
<li>Exploit generation using AI models</li>
<li>Adversarial AI: crafting inputs to bypass detection systems</li>
<li>Case study: AIassisted phishing campaigns and social engineering</li>
</ul>
</li>
<li>Ethical and Operational Challenges
<ul>
<li>Bias in AI models</li>
<li>Data privacy and compliance</li>
<li>Risks of dualuse AI (defensive vs offensive applications)</li>
</ul>
</li>
<li>Demo / HandsOn Concept
<ul>
<li>Example: Using an AI model to classify network anomalies (defense)</li>
<li>Example: Simulating an AIgenerated phishing email (offense)</li>
</ul>
</li>
<li>Introduction: Why AI Needs Security
<ul>
<li>AI as a new attack surface</li>
<li>Overview of AI system components (model, data, API, memory)</li>
</ul>
</li>
<li>Threats to AI Systems
<ul>
<li>OWASP Top 10 for LLM Applications</li>
<li>Adversarial inputs, prompt injection, model poisoning</li>
<li>Case study: Exploiting an AI chatbot</li>
</ul>
</li>
<li>Securing the AI Pipeline
<ul>
<li>Data validation and sanitization</li>
<li>Model hardening and access control</li>
<li>Secure deployment practices (sandboxing, API gateways)</li>
</ul>
</li>
<li>Monitoring and Incident Response for AI
<ul>
<li>Logging and anomaly detection for AI behavior</li>
<li>Detecting prompt injection and data exfiltration</li>
<li>Integrating AI security into SOC workflows</li>
</ul>
</li>
<li>HandsOn Concept
<ul>
<li>Simulated attack on an LLM and mitigation using guardrails</li>
</ul>
</li>
</ul>

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205 People have registered