Length: 2 Days

Certified AI SOC Analyst (CAISOC) Certification Program by Tonex

Certified AI SOC Analyst (CAISOC) Certification Program by Tonex

The Certified AI SOC Analyst (CAISOC) Certification Program by Tonex focuses on monitoring, detection, and triage of security threats targeting machine learning (ML) systems. This course equips SOC analysts with the knowledge and tools to handle AI-specific risks. Participants learn how to baseline ML model behavior, detect anomalies, and integrate telemetry into SIEMs. Practical guidance on AI incident playbooks and dashboarding threats is also covered. Designed for modern SOC environments, CAISOC enables professionals to respond effectively to evolving AI risks and ensure model integrity.

Audience:

  • SOC analysts
  • Cybersecurity engineers
  • Threat detection teams
  • AI/ML engineers
  • Security architects
  • Incident responders

Learning Objectives:

  • Understand logging and telemetry strategies for ML models
  • Learn how to baseline AI model behavior and detect drift
  • Integrate AI systems with enterprise SIEM platforms
  • Build SOC playbooks for AI-related incidents
  • Visualize model health and threat indicators
  • Strengthen detection and response in AI environments

Program Modules:

Module 1: Logging and Telemetry for ML Systems

  • Importance of telemetry in AI security
  • Logging pipelines for AI workloads
  • Data collection points across ML lifecycle
  • Secure logging practices for AI models
  • Monitoring endpoints and inference logs
  • Tools for AI-centric telemetry

Module 2: AI Model Behavior and Drift Detection

  • Understanding model drift and concept drift
  • Baseline model behavior in production
  • Anomaly detection in AI outputs
  • Threshold tuning for model alerts
  • Change detection in input distributions
  • Automation of drift monitoring

Module 3: SIEM Integration for AI Threat Monitoring

  • Overview of SIEM systems
  • Forwarding AI logs to Splunk and Sentinel
  • Customizing SIEM rules for ML events
  • Parsing AI-specific log data
  • Correlation of AI events with threat intel
  • Alerting on AI model misuse

Module 4: SOC Playbooks for AI Incident Response

  • Defining AI-specific attack scenarios
  • Step-by-step AI incident workflows
  • Model poisoning response actions
  • Inference abuse response strategies
  • Playbook testing and simulation
  • Coordination with data science teams

Module 5: AI Model Health and Threat Dashboards

  • Key metrics for model performance
  • Threat visibility in dashboard format
  • Visualization tools for model status
  • Real-time alert integration
  • Custom dashboards for SOC view
  • Examples of AI threat monitoring UI

Module 6: Governance, Compliance, and AI Security Policies

  • AI-specific compliance requirements
  • Role of governance in model integrity
  • Access control in ML environments
  • Documenting AI security controls
  • Alignment with AI regulations
  • Policy templates and guidance

Exam Domains:

  1. AI Threat Detection and Response Fundamentals
  2. Telemetry and Logging in AI Systems
  3. SIEM Integration Techniques for AI Workloads
  4. AI Model Drift and Behavioral Analysis
  5. AI Incident Response and Playbook Design
  6. AI Governance, Risk, and Compliance in SOC

Course Delivery:

The course is delivered through a combination of lectures, interactive discussions, and project-based learning, facilitated by experts in the field of AI and cybersecurity operations. Participants will have access to online resources, including readings, case studies, and tools for practical exercises.

Assessment and Certification:

Participants will be assessed through quizzes, assignments, and a capstone project. Upon successful completion of the course, participants will receive a certificate in Certified AI SOC Analyst (CAISOC).

Question Types:

  • Multiple Choice Questions (MCQs)
  • True/False Statements
  • Scenario-based Questions
  • Fill in the Blank Questions
  • Matching Questions (Matching concepts or terms with definitions)
  • Short Answer Questions

Passing Criteria:

To pass the Certified AI SOC Analyst (CAISOC) Certification Training exam, candidates must achieve a score of 70% or higher.

Advance your SOC skills in the AI era. Enroll in the CAISOC certification and become a trusted AI threat defender.

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