FORMATION IA
L'IA pour les opérations de cybersécurité
Dotez les équipes SOC des compétences pour déployer et défendre des flux de détection des menaces augmentés par l'IA.
Ce qu'elle couvre
Ce programme de niveau praticien forme les professionnels des opérations de sécurité à intégrer l'IA et le machine learning dans leurs workflows clés : détection des menaces, prévention du phishing et réponse automatisée aux incidents via les plateformes SIEM/SOAR. Les participants réalisent des exercices pratiques simulant de véritables scénarios d'attaque et apprennent à identifier les menaces liées à l'IA adverse, notamment l'injection de prompts et l'empoisonnement de modèles ciblant les systèmes d'IA internes. Le format combine des sessions animées par un formateur avec des exercices sur des outils réels tels que Microsoft Sentinel, Splunk et CrowdStrike. À l'issue du programme, les participants disposent d'un playbook SOC augmenté par l'IA prêt à être déployé.
À l'issue, vous saurez
- Configure an AI-based anomaly detection rule within a SIEM platform and explain the model's decision logic to stakeholders
- Build and test an automated SOAR playbook that triages phishing alerts using an NLP classifier
- Identify and document prompt injection vulnerabilities in an enterprise-facing AI assistant or copilot
- Conduct a red-team exercise simulating adversarial attacks against an AI-augmented SOC tool and propose mitigations
- Produce a governance checklist for deploying AI models in a regulated security operations environment
Sujets abordés
- AI-powered threat detection: supervised and unsupervised anomaly detection models
- SIEM/SOAR automation with AI: use cases in Microsoft Sentinel, Splunk SOAR, and Palo Alto XSOAR
- Phishing and social engineering prevention using NLP-based classifiers
- Adversarial AI threats: prompt injection, model poisoning, and data exfiltration via LLMs
- Securing internal AI systems and copilots deployed in enterprise environments
- Automated incident triage and response playbook design
- Threat intelligence enrichment using generative AI and LLM-based analysis
- Compliance and governance considerations for AI in security operations
Modalité
Delivered as a blended programme over three to five days on-site or via interactive remote sessions. Approximately 60% of time is hands-on lab work using pre-configured sandboxed environments replicating real SIEM/SOAR stacks. Participants receive a lab workbook, threat scenario library, and AI-augmented SOC playbook template. Remote delivery uses a dedicated virtual lab environment accessible throughout the programme. A follow-up Q&A session is typically offered four weeks post-training to review real-world implementation challenges.
Ce qui fait que ça marche
- Involving SOC tier-1 and tier-2 analysts alongside security architects to ensure operational buy-in and practical relevance
- Running the training against the organisation's own (anonymised) log data and alert history to ground exercises in real context
- Establishing a post-training AI model review cadence so detection models are retrained as threat landscapes evolve
- Pairing training with a formal AI security policy update to embed new practices into SOC operating procedures
Erreurs fréquentes
- Deploying AI detection models without baseline tuning, leading to alert fatigue from high false-positive rates
- Overlooking adversarial threats specific to AI systems, leaving internal copilots and LLM integrations unaudited
- Treating SOAR automation as a black box without analyst understanding, causing misplaced trust in automated triage decisions
- Skipping governance and compliance review for AI tooling, creating liability under NIS2, GDPR, or sector-specific regulations
Quand NE PAS suivre cette formation
This programme is not the right fit for organisations that have not yet deployed a SIEM solution or established basic security monitoring practices — foundational security operations training should come first before introducing AI augmentation.
Fournisseurs à considérer
Sources
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