Certified GenAI and LLM Cybersecurity Professional for Developers (CGLCP-D) Certification Course by Tonex
Certified GenAl and LLM Cybersecurity Professional for Developers Certification is a 2-day course where participants learn the basics of Generative AI and Large Language Models.
—————————————-
As businesses increasingly adopt generative AI and large language models (LLMs), the need for robust cybersecurity measures becomes paramount.
These AI technologies, while powerful, are also susceptible to various security threats. Understanding the specific cybersecurity technologies involved in protecting these systems is essential for safe and effective deployment.
Generative AI models, particularly LLMs, rely heavily on vast amounts of data. This data, if compromised, can lead to significant breaches. Encryption technologies, such as Advanced Encryption Standard (AES) and RSA encryption, are crucial in protecting the data used by these models.
These technologies ensure that data, both at rest and in transit, remains secure from unauthorized access, reducing the risk of exposure to cybercriminals.
Needless to say, deploying AI models in a secure environment is critical. Techniques like containerization and secure enclave computing are often employed. Containerization, through platforms like Docker, isolates the AI model in a controlled environment, minimizing the attack surface.
Secure enclaves, on the other hand, provide hardware-based protection, ensuring that sensitive data processed by the AI remains confidential, even from the host system.
Another security factor is access control, which is vital to restrict who can interact with the AI models. Multi-factor authentication (MFA) and role-based access control (RBAC) are commonly used technologies.
MFA adds an extra layer of security by requiring multiple forms of verification before granting access, while RBAC ensures that users have only the permissions necessary for their roles, limiting the potential damage from insider threats.
Additionally, real-time threat detection is essential in safeguarding AI models. Intrusion detection systems (IDS) and anomaly detection algorithms are utilized to monitor the system continuously for any unusual activities that could indicate a cyber-attack.
These technologies can detect and respond to potential threats before they escalate into major security incidents.
Certified GenAI and LLM Cybersecurity Professional for Developers (CGLCP-D) Certification Course by Tonex
The Certified GenAI and LLM Cybersecurity Professional for Developers (CGLCP-D) certification is tailored for developers focusing on the secure creation and maintenance of Generative AI and Large Language Models. This program provides practical skills in secure coding practices, security testing, and implementing comprehensive security controls throughout the AI development lifecycle. It also covers integrating DevSecOps principles and monitoring AI applications for threats.
Learning Objectives:
- Learn the basics of Generative AI and Large Language Models.
- Apply secure coding practices in AI application development.
- Conduct security testing on AI applications.
- Implement security controls throughout the AI development lifecycle.
- Integrate DevSecOps principles in AI projects.
- Monitor and respond to threats in AI applications.
Exam Objectives:
- Assess knowledge of secure coding practices for AI.
- Evaluate ability to conduct AI application security testing.
- Test understanding of implementing security controls in AI systems.
- Measure proficiency in integrating DevSecOps principles.
- Validate skills in monitoring and responding to AI threats.
Exam Domains:
- Introduction to GenAI and LLMs for Developers (10%)
- Secure Coding Practices for AI (25%)
- AI Application Security Testing (20%)
- Implementing Security Controls in AI Systems (20%)
- DevSecOps for AI (15%)
- Continuous Monitoring and Threat Detection (10%)
Type of Questions:
- Multiple-choice questions
- Scenario-based questions
- Hands-on practical tasks (e.g., secure coding exercises, security testing)