October 11, 2024 at 07:49PM
Organizations are increasingly seeking candidates with machine learning and large language model skills for cybersecurity roles, as highlighted in ISACA’s 2024 report. Key skill gaps include LLM SecOps, ML SecOps, cloud computing, and security controls implementation, while soft skills remain the most commonly identified gap among cybersecurity professionals.
### Meeting Takeaways:
1. **Growing Demand for LLM and ML Skills**:
– Organizations are increasingly prioritizing candidates with expertise in machine learning (ML) and large language models (LLM) for cybersecurity roles, driven by the need to safeguard corporate assets against risks associated with artificial intelligence technologies.
2. **Skills Gap in Cybersecurity**:
– According to ISACA’s 2024 State of Cybersecurity report:
– **24%** of respondents identified LLM SecOps and ML SecOps as the most significant skills gaps.
– **51%** cited the lack of soft skills (communication, flexibility, leadership) as a challenge for cybersecurity professionals.
3. **Understanding ML SecOps and LLM SecOps**:
– **ML SecOps**:
– Focuses on integrating security throughout the development and deployment of machine learning systems.
– Involves processes like data security, transparency to prevent bias, secure coding, threat modeling, security audits, and incident response.
– **LLM SecOps**:
– Encompasses securing the full lifecycle of large language models, covering:
– Ethical considerations in design,
– Data sanitization,
– Decision analysis during model training,
– Prevention of harmful content generation,
– Ongoing model monitoring post-deployment.
4. **Resource Availability for Skill Development**:
– A repository by Benjamin Kereopa-Yorke on GitHub offers resources and training for ML SecOps, categorized by related prior knowledge and vendor neutrality.
– OWASP provides resources including:
– Draft Machine Learning Security Top Ten list detailing ML attack methods and countermeasures.
– OWASP Top Ten for LLMs addressing specific risks like prompt injection and model theft.
5. **Additional Skill Gaps**:
– Beyond soft skills, other notable skill gaps include:
– **42%** in cloud computing,
– **35%** in security controls implementation,
– **28%** in software development (notably in testing and deployment rather than coding).
6. **Context of Cloud Security Needs**:
– The shift of organizational workloads to the cloud necessitates cybersecurity professionals with specialized knowledge to secure cloud assets, which require different mindsets and techniques compared to traditional networking.
Overall, organizations are facing significant skills gaps in cybersecurity, particularly regarding emerging technologies like ML and LLM, and are in need of dedicated training resources to bridge these gaps.