arXiv:2510.20692v2 Announce Type: replace-cross Abstract: Cloud computing is ubiquitous, with a growing number of services being hosted on the cloud every day. Typical cloud compute systems allow administrators to write policies implementing access control rules which specify how access to private data is governed. These policies must be manually written, and due to their complexity can often be error prone. Moreover, existing policies often implement complex access control specifications and thus can be difficult to precisely analyze in determining their behavior works exactly as intended. Re
The proliferation of cloud services and the increasing complexity of access control policies are driving the need for automated solutions, with large language models now capable of addressing these challenges.
This development indicates a tangible application of AI in managing critical infrastructure security, potentially reducing human error and increasing efficiency in cloud access control.
Access control policy writing and analysis, traditionally manual and error-prone, can now be significantly augmented or automated by LLMs, shifting the effort from manual coding to AI supervision.
- · Cloud service providers
- · Cybersecurity sector
- · AI development firms
- · Enterprises leveraging cloud
- · Manual policy writers
- · Legacy security software vendors
Reduction in cloud security breaches due to misconfigured access policies.
Increased adoption of automated policy management tools, integrated with LLMs, across cloud environments.
The role of human security administrators evolves from policy creation to oversight and fine-tuning of AI-generated policies.
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Read at arXiv cs.AI