Align with NIST AI Risk Management Framework with Lumeus
AI Access Control,AI Guardrails,Enterprise AI,GenAI,LLM,Shadow AI
ByRobertsonDecember 16, 2024
As artificial intelligence (AI) continues to transform industries, the importance of implementing robust governance frameworks for AI systems becomes increasingly clear. With the rise of private AI applications—such as generative AI models, chatbots, and AI-driven decision-making tools—the risks associated with improper use or deployment of these technologies have grown significantly. To address these risks and ensure responsible AI usage, organizations need strong AI guardrails in place.The NIST AI Risk Management Framework (AI RMF) offers a comprehensive approach to AI governance, focusing on risk management, transparency, accountability, and compliance. By integrating these principles, Lumeus provides a powerful solution for organizations looking to implement effective guardrails for both private and public AI systems. Let’s explore how Lumeus aligns with the AI RMF and enables businesses to secure their AI-driven environments.1. Visibility: Monitoring AI Usage with AccountabilityOne of the core components of the NIST AI RMF is “Govern,” which emphasizes the need for transparency and accountability in AI systems. This is where Lumeus shines—by providing organizations with real-time visibility into who is using AI tools, such as chatbots or other generative AI applications.Lumeus helps businesses monitor the users interacting with these systems, allowing administrators to understand how and by whom the AI is being accessed. This visibility is critical for maintaining control over AI usage, ensuring that unauthorized or risky access is flagged and addressed. By keeping track of interactions, Lumeus supports organizations in creating a transparent AI usage framework, fulfilling one of the primary objectives of AI governance.2. Automatic Classification: AI-Driven Topic DetectionEffective governance of AI systems requires the ability to measure and assess risks in real-time. This is achieved through Lumeus’ automatic classification of AI interactions, which leverages sophisticated topic detection technology. Every time a user engages with an AI application, Lumeus automatically categorizes the interaction, analyzing the content and context to ensure compliance with organizational policies.This aligns with the “Map” and “Measure” functions of the NIST AI RMF, which focus on identifying AI risks and monitoring AI performance. Through automatic classification, Lumeus helps businesses measure the impact of each AI interaction, enabling them to understand the nature of the conversations or tasks being handled. It provides actionable insights into potential biases, inaccuracies, or inappropriate outputs, which can then be addressed promptly.3. Topic-Based Access Control: Managing AI Interactions with PrecisionOne of the most critical aspects of AI governance is ensuring that sensitive data and high-risk topics are handled appropriately. This is where Lumeus’ topic-based access control system proves invaluable. Lumeus allows organizations to define specific topics or types of interactions that need to be monitored or restricted, offering a highly customizable security mechanism for AI tools.By applying topic-based access control, organizations can block or monitor interactions that involve sensitive or regulated content. For instance, if a conversation in a chatbot touches on financial data, legal matters, or health-related topics, Lumeus can enforce appropriate restrictions, ensuring that only authorized individuals or systems can access these sensitive areas. This capability strengthens security and ensures compliance with privacy regulations, aligning with the “Manage” function of the NIST AI RMF.Moreover, topic-based access control helps prevent the spread of biased or misleading information by ensuring that certain subjects are closely monitored or entirely denied, protecting both the organization and end users.4. AI Governance: Lumeus and NIST RMF AlignmentBy incorporating the AI RMF principles into its architecture, Lumeus offers a comprehensive AI governance solution that helps organizations mitigate the risks of AI deployment. Here’s how Lumeus’ features align with the core functions of the NIST AI RMF:Govern: Lumeus provides visibility into AI usage, enabling organizations to hold users accountable and ensure AI tools are being accessed appropriately.Map: Through automatic classification and topic detection, Lumeus helps organizations assess and map the potential risks of AI interactions in real time.Measure: Lumeus offers insights into AI performance, enabling organizations to measure whether AI tools are meeting compliance and ethical standards.Manage: Lumeus’ topic-based access control allows businesses to manage AI interactions with precision, ensuring that sensitive or high-risk topics are appropriately handled. Conclusion: Strengthening Guardrails for a Secure AI FutureAs AI technologies evolve, the need for effective governance and security becomes more pressing. Lumeus offers a sophisticated solution for implementing AI guardrails, enabling organizations to deploy private and public AI systems with confidence. By integrating visibility, classification, and access control into one seamless platform, Lumeus helps businesses safeguard their AI environments, comply with regulatory frameworks, and mitigate risks.Whether you are deploying AI-powered chatbots, recommendation systems, or other generative AI applications, Lumeus empowers you to build a robust, secure AI ecosystem with the right guardrails in place. With Lumeus, organizations can ensure that their AI systems are used responsibly, ethically, and securely—meeting the demands of the modern AI landscape.Demohttps://www.youtube.com/embed/X9FyyOPDR9Y

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AI Access Control: The Key to Secure and Scalable Enterprise AI Solutions

AI Access Control,Enterprise AI,GenAI,Zero Trust Security,Access Management
ByMattApril 22, 2024
Summary Successful Enterprise AI implementations, such as those by Virgin Pulse and Gilead Sciences, showcase its ability to enhance internal search functionality, streamline processes, and improve efficiency. However, challenges like authorization issues, permission awareness and data overexposure persist, which become a barrier in its implementation. AI Access Control emerges as a solution to overcome these implementation barriers as it facilitates secure and managed access to diverse data, essential for IT and Security teams.  What is Enterprise AI? Enterprise AI is the integration of AI-driven assistants like Amazon Q from AWS, Google’s Vertex AI or Microsoft’s Azure AI, with an organization’s database, information systems, and workflows. It helps employees, vendors and third parties to gain the capability to craft detailed, organization specific queries tailored to their needs and receive customized responses, filtered to display only the data they’re cleared to access.Enterprise AI facilitates an environment where company information flows freely yet securely, ensuring that the right insights reach the right people at the right time. It is skilled in solving for challenges unique to any enterprise. Enterprise AI success stories from leading companies Virgin Pulse: Enterprise AI, through Amazon Q and Amazon Bedrock, has helped Virgin Pulse by unifying search functions across the worldwide employee base and improved search results within the organization, offering collaboration across dispersed locations and a personalized and secure experience for employees. Gilead Sciences: For Gilead, Enterprise AI enabled search of important documents, knowledge, and data in one centralized location which helped in quicker insight generation and analysis of vast data sets across the organization, it simplified connecting to data sources, automating complex tasks, and delivering relevant insights efficiently.Wunderkid: Wunderkid possesses vast amounts of proprietary data, and faced challenges in navigating through multiple data ‘silos’ to extract relevant answers and transform them into swift, actionable insights. Implementing Enterprise AI as a top layer across different content and data repositories has significantly enhanced efficiency for their customer success and marketing teams. What are the challenges with Enterprise AI implementation? Authorization:  Integration with SAML 2.0–supported identity providers for authorization in Enterprise AI systems presents challenges such as compatibility issues, complex configurations, security concerns, and the need for ongoing maintenance and support to ensure a secure and efficient connection.Permission Awareness: Enterprise AI faces permission awareness challenges due to the intricate nature of enterprise data and permissions, requiring careful system design and maintenance to manage access controls, data ownership, compliance, and scalability effectively.Overexposure: Despite having permission awareness mechanisms, Enterprise AI systems risk data overexposure through misconfigurations, human errors, and insufficient monitoring, necessitating robust processes like regular audits and employee training to safeguard data. What is the need for AI Access Controls? The management of access to a vast and diverse array of information ranging from documents and emails to multimedia content like images and audio/video files poses a significant challenge for IT and Security teams within enterprises. Given the sheer volume of data, in various formats and stored across multiple locations, streamlining access while ensuring security is becoming increasingly burdensome.In response to these challenges, AI Access Control emerges as a solution, enhancing the way enterprises interact with applications, communications, and documents directly within their workflows. AI Access Control simplifies the integration and accessibility of both structured and unstructured data. This technology facilitates a unified access point to content sources across the enterprise, enabling the authorization, access, permissions and analysis of data, whether it’s housed on-site or in the cloud. Framework for a successful Enterprise AI implementation via AI Access Controls Streamlined Integration and Identity ManagementImplement standardized protocols like SAML 2.0, OAuth, and OpenID Connect, and integrate with specialized third-party vendors for seamless identity and access management solutions.Advanced Permission ManagementImplement advanced, dynamic access control systems with a granular permissions framework for real-time, precise management of roles, permissions, and policies, offering precise adjustments based on specific roles, data types, and operational contexts, ensuring fine-grained security through meticulous management of access permissions.Enhanced Security MeasuresImplement comprehensive data management strategies that include administrative controls that allow for the blocking of topics and the filtering of content based on keywords, organization of data assets by grouping and cataloging, visibility with least privilege access, rigorous risk and compliance management, and track the location of data through IP addresses and file paths to enhance data security and align with organizational policies. By integrating these steps, organizations can build a more secure, efficient, and responsive AI Access Control system, ensuring that access to sensitive information is properly managed and protected against emerging threats.Lumeus.ai offers Zero Trust Security for AI, enabling IT Security to efficiently manage ShadowAI, control AI access, and enforce AI Guardrails. It integrates seamlessly with existing security infrastructures, supporting identity platforms like Okta, Google, Active Directory, and network security platforms from Palo Alto, ZScaler, Fortinet, enabling a smooth deployment.If you’re interested in a deeper discussion or even in contributing to refining this perspective, feel free to reach out to us.

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