Cybersécurité IA : maîtriser les risques des modèles d’intelligence artificiell

Assurer la cybersécurité de vos modèles IA est primordiale pour assurer la disponibilité, l’intégrité ainsi que la confidentialité de vos services. (CIA : confidentialiy, integrity & availability)

Artificial intelligence opens up new opportunities, but also new attack surfaces. Protecting models, data and users is not an option: it's an essential prerequisite for guaranteeing a successful Reliable, responsible and compliant AI aux réglementations (RGPD, GDPR). Voilà ce qu’il est possible de faire pour assurer la cybersécurité de vos modèles IA.

Guardrails : to strictly control model input and output, reduce the risk of hallucinations and align behavior with business, ethical and regulatory rules.
Data sanitization and prompts to prevent malicious injections, clean inputs and prevent leakage of sensitive information.
Proxy and model isolation : to filter, log and control flows, while partitioning environments to limit the impact of potential attacks.
IA endpoint security : to reinforce authentication, control access and audit API calls, guaranteeing system resilience.
Proactive prevention : encryption, key rotation, penetration testing and regular audits to identify vulnerabilities.
Alignment with standards : integration of OWASP best practices (application security, API, LLM Top 10) and threat mapping according to MITRE ATT&CK, to cover known and emerging attack vectors.

Objective: ensure that AI remains a strategic asset and not a vulnerability, by building robust, explainable systems capable of withstanding current and future threats.

Voyez la cybersécurité de votre IA comme un investissement et non pas un poste de dépenses.