التقنية : الميتافيرس
- AR Version
- Tech : Intelligence & Security / AICyberBridge Course
متخصص معتمد في أمن المعلومات والذكاء الاصطناعي ™
Certified Information Security & AI Professional (CISAIP)™ Workshop
Transform your CISSP expertise with AI-driven security strategies. Gain the documents, frameworks, and best practices needed to elevate your cybersecurity skills into the AI era.
- Last updated : February 8, 2025
- 4.721 students
About the Workshop
This 5-day intensive program focuses on bridging AI concepts into each of the eight CISSP domains. Instead of traditional labs, participants will generate practical toolkits (policies, checklists, frameworks, etc.) that they can use immediately in their organizations.
The course is designed for those interested in the design, implementation and responsible use of artificial intelligence systems and products within their organization.
- – CISSP-Certified Professionals looking to integrate AI into their existing security framework.
- – Cybersecurity Managers and Team Leads who oversee risk management, network security, or IAM.
- – IT Governance Professionals aiming to align AI strategies with corporate compliance.
- – Security Architects and Engineers exploring AI for threat modeling, detection, and response.
- – Chief Information Security Officer (CISO)
(Responsible for high-level security strategy and governance.) - – Security Operations Center (SOC) Manager
(Oversees day-to-day threat monitoring and incident response.) - – IT Risk & Compliance Officer
(Manages risk assessments and ensures regulatory adherence.) - – AI/ML Security Consultant
(Advises on integrating AI tools for improved security posture.)
- – AI Integration for Each CISSP Domain: Adapt your foundational knowledge with AI-driven solutions and documentation.
- – Strategic Document Creation: Develop governance policies, risk assessment frameworks, and compliance checklists that incorporate AI considerations.
- – Real-World Application: Discover how to immediately deploy these tools and templates for faster, more effective security management.
- – Future-Proof Your Skillset: Stay relevant by evolving your current CISSP knowledge to include AI advancements.
- – Practical Output: Walk away with ready-to-use documents and frameworks—no abstract theory, just actionable deliverables.
- – Certification Advantage: Earn the CISAIP credential, demonstrating your AI-readiness to employers and peers.
- – AI-Augmented Risk Management: Ability to incorporate machine learning insights into risk assessments and compliance processes.
- – Enhanced Policy Development: Proficiency in creating AI-inclusive governance documents for data protection and incident response.
- – Improved Decision-Making: Insight into AI-driven security architecture designs, enabling faster, data-informed strategies.
– AI Fundamentals for Cybersecurity
Explore core AI concepts (ML, NLP, Deep Learning) and how they apply to risk detection and threat intelligence.– Risk Management & Compliance Upgrades
Adapt traditional risk frameworks like NIST SP 800-30 with AI-based tools for predictive analysis.– Documenting AI-Infused Architecture & Engineering
Use curated templates to incorporate AI into network designs, hardware configurations, and secure system lifecycles.– AI-Driven IAM & Access Control
Build policies for biometric authentication, anomaly detection, and zero-trust frameworks augmented by AI.– Security Assessment & Testing Tools
Compile checklists for AI-driven penetration testing, vulnerability scanning, and continuous compliance.– Incident Response & Security Operations
Leverage AI to enhance incident response playbooks, streamline log analysis, and automate threat hunting.– Governance, Ethics, and Regulatory Considerations
Account for ethical AI deployment, data privacy, and evolving legal frameworks.AI in Software Development Security
Develop guidelines for integrating AI-powered static code analysis and secure DevOps pipelines.
– Policy & Framework Creation
Draft AI-focused policies aligned with industry standards (NIST, ISO 27001) to maintain robust governance.– Strategic Planning & Implementation
Understand how to build AI readiness strategies that align with organizational goals.– Risk & Compliance Enhancement
Incorporate ML predictions into risk scoring and compliance audits for more effective oversight.– Communication & Stakeholder Engagement
Clearly articulate AI-driven security initiatives to leadership, technical teams, and non-technical stakeholders.
- – Active CISSP Certification (or equivalent professional experience).
- – Basic understanding of cybersecurity fundamentals, including risk management, network security, and IAM concepts.
Training Guide
1. Course Handbook
- Comprehensive guide covering all course modules.
- Detailed explanations of ISO/IEC 42001 principles, requirements, and implementation strategies.
2. Lecture Slides:
- Visual aids used during lectures for better understanding.
- Key points, diagrams, and examples.
3. Study Notes
- Summarized notes for quick reference.
- Important points highlighted from each lecture.
Service Guide
1. AI-Infused Domain Frameworks (for each CISSP domain)
- Step-by-step instructions on how to implement the ISO/IEC 42001 standard.
- Detailed processes, templates, and best practices.
2. Policy & Template Toolkits for governance, risk, and compliance
- Templates to help identify, evaluate, and mitigate AI-related risks.
- Examples and guidelines on how to fill out the templates.
3. Compliance Checklists
- Checklists to ensure all necessary steps are taken for compliance.
- Items covering legal, ethical, and operational aspects.
Practical Tools
1. Case Studies
- Real-world examples of successful ISO/IEC 42001 implementation.
- Analysis of challenges faced and solutions applied.
2. Interactive Exercises
- Practical exercises to apply concepts learned.
- Group activities, role-playing scenarios, and problem-solving tasks.
3. Certification preparation guides and practice exercises.
- Access to AI management software or platforms used during the course.
- Training on how to use these tools effectively.
Templates and Forms
1.Policy Templates
1- Downloadable PDF Handbooks and AI Reference Docs
2- Optional Recorded Sessions for post-workshop review
3- Supportive Online Community Forum for Q&A and resource sharing
4. Certification Exam Preparation
- – Practice exams and sample questions.
- – Study guides focused on certification requirements.
Practices
Practices for the ISO/IEC 42001 Course
English
1. Interactive Workshops:
Hands-on sessions where participants work on real-world scenarios.
Group activities to encourage collaboration and knowledge sharing.
Practical exercises to apply concepts learned.
2. Case Study Analysis:
In-depth examination of successful ISO/IEC 42001 implementations.
Discussion of challenges faced and solutions applied.
Lessons learned and best practices.
3. Risk Assessment Exercises:
Identifying and evaluating AI-related risks.
Developing risk mitigation strategies.
Using provided templates and tools for risk management.
4. Compliance Audits:
Conducting mock internal audits.
Reviewing compliance checklists and documentation.
Identifying areas for improvement and developing action plans.
5. Role-Playing Scenarios:
Simulating real-world situations to practice decision-making.
Role-playing different stakeholders to understand various perspectives.
Problem-solving tasks to reinforce learning.
6. Policy and Procedure Development:
Creating AI management policies using provided templates.
Developing standard operating procedures for AI tasks.
Customizing documents to fit organizational needs.
7. Ethical and Legal Considerations Workshops:
Discussing ethical implications and legal requirements of AI.
Analyzing case studies on ethical dilemmas.
Developing strategies for ethical AI management.
8. Software Tools Training:
Hands-on training with AI management software or platforms.
Demonstrating how to use tools effectively.
Practice sessions to build proficiency.
9. Q&A Sessions and One-on-One Consultations:
Scheduled sessions for participants to ask questions.
Opportunities for individual consultations with instructors.
Addressing specific concerns and providing tailored advice.
10. Certification Exam Preparation:
Practice exams and sample questions.
Study guides focused on certification requirements.
Tips and strategies for successful exam performance.
Arabic
1. ورش العمل التفاعلية:
جلسات عملية حيث يعمل المشاركون على سيناريوهات واقعية.
أنشطة جماعية لتعزيز التعاون وتبادل المعرفة.
تمارين عملية لتطبيق المفاهيم المكتسبة.
2. تحليل دراسات الحالة:
فحص متعمق لتنفيذات ناجحة لمعيار ISO/IEC 42001.
مناقشة التحديات التي واجهتها والحلول المطبقة.
الدروس المستفادة وأفضل الممارسات.
3. تمارين تقييم المخاطر:
تحديد وتقييم المخاطر المتعلقة بالذكاء الاصطناعي.
تطوير استراتيجيات التخفيف من المخاطر.
استخدام القوالب والأدوات المقدمة لإدارة المخاطر.
4. تدقيق الامتثال:
إجراء تدقيقات داخلية وهمية.
مراجعة قوائم التحقق ووثائق الامتثال.
تحديد مناطق التحسين وتطوير خطط العمل.
5. سيناريوهات لعب الأدوار:
محاكاة مواقف واقعية لممارسة اتخاذ القرارات.
لعب أدوار أصحاب المصلحة المختلفين لفهم وجهات النظر المختلفة.
مهام حل المشكلات لتعزيز التعلم.
6. تطوير السياسات والإجراءات:
إنشاء سياسات إدارة الذكاء الاصطناعي باستخدام القوالب المقدمة.
تطوير إجراءات التشغيل القياسية لمهام الذكاء الاصطناعي.
تخصيص الوثائق لتناسب احتياجات المنظمة.
7. ورش العمل حول الاعتبارات الأخلاقية والقانونية:
مناقشة التداعيات الأخلاقية والمتطلبات القانونية للذكاء الاصطناعي.
تحليل دراسات الحالة حول المعضلات الأخلاقية.
تطوير استراتيجيات لإدارة الذكاء الاصطناعي بشكل أخلاقي.
8. تدريب على أدوات البرمجيات:
تدريب عملي على إدارة البرمجيات أو المنصات المستخدمة في الذكاء الاصطناعي.
عرض كيفية استخدام الأدوات بشكل فعال.
جلسات تدريب لبناء الكفاءة.
9. جلسات الأسئلة والأجوبة والمشاورات الفردية:
جلسات مجدولة لطرح الأسئلة من قبل المشاركين.
فرص للتشاور الفردي مع المدربين.
معالجة القضايا المحددة وتقديم نصائح مخصصة.
10. التحضير لامتحان الشهادة:
اختبارات تجريبية وأسئلة نموذجية.
أدلة دراسية تركز على متطلبات الشهادة.
نصائح واستراتيجيات لتحقيق أداء ناجح في الامتحان.
By incorporating these practices into the course, participants will gain practical experience and confidence in implementing the ISO/IEC 42001 standard, preparing them effectively for real-world application and certification.
- Course Introduction
- Certificate Introduction & Exam Details.
- 1.1 Introduction to AI in Cybersecurity : Overview of AI concepts (Machine Learning, Deep Learning, NLP) and why they matter for CISSP holders.
- 1.2 CISSP Meets AI : Mapping AI capabilities to the eight CISSP domains and understanding key synergy points.
- 1.3 Core Tools & Technologies : Common AI frameworks, data analytics platforms, and security-specific AI solutions.
- 2.1 AI-Driven Risk Assessments (Domain 1 & Domain 2) : Using AI tools to forecast threats and prioritize asset protection.
- 2.2 Security Architecture & Engineering with AI (Domain 3) : Integrating AI models in secure system design, focusing on predictive monitoring.
- 2.3 AI in Communication & Network Security (Domain 4) : Building anomaly detection models for network traffic and zero-trust communications.
- 3.1 Identity and Access Management (Domain 5) : Evaluating AI-based authentication (biometric, behavioral analytics) and continuous access controls.
- 3.2 Security Assessment & Testing with AI (Domain 6) : Designing checklists for AI-assisted vulnerability scans, automated pen testing, and threat simulations.
- 3.3 Refining AI Outputs : Methods for validating AI results (accuracy, false positives/negatives) and adapting models.
- 4.1 Risk Prioritization & Compliance Mapping: Planning how AI-based insights feed into GRC (Governance, Risk, Compliance) strategies.
- 4.2 Enablement of Teams & Stakeholders: Outlining training needs, stakeholder buy-in, and resource allocation for AI initiatives.
- 4.3 Developing an AI Roadmap: Step-by-step blueprint aligning AI projects with organizational objectives and CISSP best practices.
- 5.1 Governance Frameworks for AI (Domain 1 & Domain 2): Drafting policies that merge AI governance with existing cybersecurity structures (NIST, ISO 27001, etc.).
- 5.2 AI-Enhanced Security Operations (Domain 7): Incorporating AI into SOC procedures, incident response, and compliance monitoring.
- 5.3 Ethical and Regulatory Landscape: Addressing AI ethics, data privacy regulations (GDPR, CCPA), and industry-specific compliance.
- 6.1 Architecture & Deployment Models: Reviewing on-premises vs. cloud-based AI solutions, continuous monitoring strategies, and AI tool maintenance.
- 6.2 Continuous Threat Detection: Real-time analytics, automated alerts, and incident response enhancements through AI.
- 6.3 Software Development Security (Domain 8): Integrating AI into SDLC processes, code scanning, and DevSecOps pipelines.
- 7.1 CISAIP Exam Overview: Exam structure, question types, and domain coverage.
- 7.2 Review of Key Templates & Documents: Final recap of AI-focused frameworks, risk checklists, and governance policies created throughout the modules.
- 7.3 Next Steps & Continuous Learning: Guidance on staying current with AI developments, relevant industry certifications, and professional communities.
How the CISSP Domains Fit In
- – Domain 1 & 2 (Security & Risk Management, Asset Security): Explored in Modules 2 & 5 for AI-based risk assessments and asset classification.
- – Domain 3 (Security Architecture & Engineering): Covered in Module 2 for AI-based design considerations.
- – Domain 4 (Communication & Network Security): Included in Module 2 for AI-driven network anomaly detection.
- – Domain 5 (IAM): Featured in Module 3 for AI-based authentication and continuous access controls.
- – Domain 6 (Security Assessment & Testing): Addressed in Module 3, focusing on automated vulnerability scanning and AI pen-testing.
- – Domain 7 (Security Operations): Highlighted in Module 5, integrating AI into SOC and incident response.
- – Domain 8 (Software Development Security): Presented in Module 6, detailing AI in DevSecOps and code security.
Each of these modules culminates in the development of practical, AI-focused policies and toolkits—all aligned with the CISSP knowledge base but enhanced for AI readiness.
- Course Introduction
- Certificate Introduction & Exam Details.
- 1.1 AI-Driven Governance and Policy : How to update existing security policies with AI considerations, including ethical AI guidelines.
- 1.2 AI in Risk Assessment: Leveraging predictive analytics for threat forecasting and prioritization.
- 1.3 Compliance and Regulatory Requirements: Incorporating evolving AI regulations into standard compliance checklists (e.g., GDPR, ISO 27001).
- 2.1 Data Classification with AI: Automating classification processes using machine learning.
- 2.2 AI-Enabled Asset Discovery: Identifying unknown or untracked assets through anomaly detection.
- 2.3 Information Lifecycle Management: Managing data retention and destruction policies with AI-driven audits.
- 3.1 AI-Augmented System Design: Integrating machine learning models into secure-by-design principles.
- 3.2 Hardware and Firmware Considerations: Evaluating AI accelerators, edge devices, and their security implications.
- 3.3 Emerging Technologies: Quantum-resistant cryptography and how AI aids in designing future-proof architectures.
- 4.1 AI in Network Segmentation: Automating segmentation policies based on real-time traffic analytics.
- 4.2 Intelligent Threat Detection: Machine learning for anomaly detection, intrusion prevention, and traffic flow analysis.
- 4.3 Secure Protocols and Encryption: Assessing AI’s role in identifying vulnerabilities in encryption algorithms and protocols.
- 5.1 Biometric Authentication with AI: Facial recognition, voice authentication, and continuous monitoring for identity assurance.
- 5.2 Adaptive Access Control: Using AI to determine dynamic access privileges based on user behavior patterns.
- 5.3 Zero Trust Models: Leveraging AI to enforce just-in-time access decisions and micro-segmentation.
- 6.1 Automated Vulnerability Scanning: Enhancing traditional tools with AI to reduce false positives and streamline reporting.
- 6.2 Penetration Testing with AI: Scripted AI bots to discover complex attack paths and misconfigurations.
- 6.3 AI-Driven Compliance Testing: Crafting checklists to validate adherence to regulations and internal policies.
- 7.1 AI in Security Operations Centers (SOCs): Implementing ML-based event correlation, automated alert triaging, and real-time threat hunting.
- 7.2 Incident Response Automation: Leveraging AI to detect attacks faster and orchestrate response playbooks.
- 7.3 Behavior Analytics & Insider Threats: Using AI to profile normal behaviors and flag suspicious deviations.
- 8.1 AI-Enhanced Code Review: Tools and approaches for automatically identifying security flaws during development.
- 8.2 Secure DevOps Pipelines: Integrating AI-based vulnerability scanning into CI/CD workflows.
- 8.3 AI for Threat Modeling: Generating risk scenarios and countermeasures early in the software lifecycle.
Participants will walk away with a comprehensive toolkit, including:
- – Governance Policy Templates (AI-specific expansions of standard security policies)
- – Risk Assessment Frameworks (ML-based predictive risk scorecards)
- – Compliance Checklists (Automated tracking for AI-centric regulatory requirements)
- – AI Project & Team Management Tools (Guidelines for overseeing AI project lifecycles and cross-functional teams)
These resources ensure you’re prepared to apply your AI-enhanced knowledge immediately in any cybersecurity environment.
Certificate/accreditation and examination
1. The importance of certification:
- Journalists and content creators who work in various media outlets and want to keep up with technological developments.
2. The Exam:
- Journalists and content creators who work in various media outlets and want to keep up with technological developments.
3. Certificate and accreditation:
Attendance Testimonials
1. مقدمة عن التقنيات الحديثة في الإعلام:
- تعريف بالذكاء الاصطناعي والميتافيرس.
- أهمية تطبيقاتهم في مجالات الصحافة والإعلام والثقافة.
Q&A
1. مقدمة عن التقنيات الحديثة في الإعلام:
- تعريف بالذكاء الاصطناعي والميتافيرس.
- أهمية تطبيقاتهم في مجالات الصحافة والإعلام والثقافة.
Registrations is Closed, please Watch the Recording or Contact us for another class
Evaluate to Obtain a Certificate of Attendance
التقييم انتهى ، نراكم في محاضرات أخرى
Ramy AlDamati
General Informations
- – Delivery Languages : Arabic or English.
- – Material Languages : Arabic or English.
- – Delivery Format: Inperson, Online , or Self-Based video lectures.
- – Access from any device and from anywhere.
- – Internationally recognized certificate of attendance.
- – CPE/CPD credits.
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Plan Your Next Steps
Get a Full 360° ISO/IEC 42001 & AI Auditing Offering : These next steps provide Customers with a clear pathway to certification, practical tools for success, and continued professional development as Chief AI Auditor (CAIA)™.
Join Classroom
Attend live, interactive sessions either online or Recorded inperson for a collaborative learning experience. Sessions led by industry experts, offering opportunities for networking, hands-on exercises, and real-time discussions to deepen their understanding of AI governance and oversight.
Take the Exam
Ready to validate your skills and knowledge by taking the exam. This assessment ensures participants are equipped to lead AI initiatives effectively, covering governance, strategy, compliance, and project management.
Study Materials
Receive comprehensive study materials and the CISAIP Body of Knowledge (BoK)—a curated collection of core concepts, frameworks, and tools centered around AI-infused security. These resources are designed to bolster your learning experience and serve as a long-term reference throughout your professional development.
vCAIO Services
Our Virtual Certified AI Overseer (vCAIO)™ services provide a comprehensive solution for organizations seeking to integrate AI into their operations with expert leadership and minimal overhead. We offer strategic AI consulting tailored to your business needs, helping you design, implement, and manage AI-driven solutions.
CISAIP Preparedness Tooling™
The CISAIP Preparedness Tooling™ equips participants with practical resources to oversee AI-infused security initiatives. It includes templates for governance policies, risk assessment frameworks, compliance checklists, and tools for managing AI-driven projects and teams. This toolkit ensures participants are ready to apply their skills immediately within their organizations.
CISAIP Knowledge Resources
The CISAIP Knowledge Guides are a collection of in-depth, expert-authored documents covering specialized topics like AI risk management, ethical AI practices, and regulatory compliance. These guides serve as valuable references, helping professionals stay updated and make informed decisions as they integrate AI into their cybersecurity strategies.
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Meet our Instructors
Ramy AlDamati
ServME ACADEMY
Noor Zahran
Nidal Talib
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