Logicmates approach to secure AI
Businesses today are eagerly embracing the transformative power of machine learning and generative AI. As this technology evolves, they promise significant benefits, such as driving efficiency, innovation, and competitive advantage. However with this rapid advancement a critical question emerges – how can I be confident my AI is secure?
Our aim is to review the complex security challenges that must be addressed to safeguard business interests, customer trust, and compliance with regulatory standards.
Security Concerns for Generative AI in Business Applications
1. Data Privacy and Protection
The advent of generative AI in business applications brings to light significant concerns regarding data privacy and protection. As these systems rely on vast datasets to train and operate, they inherently risk exposing sensitive information, be it customer data, proprietary business insights, or confidential operational details.
Challenges
The primary challenge lies in ensuring that AI models access data securely and are not susceptible to breaches that could lead to unauthorised access or misuse. Additionally, there is concern for overreach when AI is accessing company data.
Mitigation
Along with our partners, Profound Logic Software, we use a holistic framework that will help prevent data privacy issues by implementing best practices when interacting with the LLM. Specifically, our product, Profound AI provides the following features to protect customers building AI functionality for their business applications.
Data access controls – In the Profound AI IDE, customers select the specific tables and columns that will be accessible by the LLM. The framework also validates all SQL statements before they execute to ensure the LLM has not requested data outside of the defined tables and columns.
Logging – Profound AI logs interactions with the LLM to allow for future auditing and troubleshooting. These logs are configurable to allow customers to fine tune the level of logging required. The logs are also consumable by enterprise monitoring software for automated notification of issues.
Data Access Exit Point – An exit point is available for data access. This exit point allows customers to implement custom node.js code to implement additional validation before data passes to the LLM.
2. Authentication and Authorisation
Generative AI is a powerful tool for enabling businesses to expand their capabilities. As businesses explore generative AI’s capabilities, it is vital to ensure that users are legitimate employees or customers and they are authorised to perform the requested actions.
Challenges
As with any technology used to access business data and proprietary information, the challenge to identify users and authorise their activities is a crucial one. Improper implementation of authentication and authorisation can leave your business susceptible to data exposure and system breaches.
Mitigation
For internal business applications, your AI solution should integrate with the authentication used by that system. For more stand-alone implementations, companies should implement widely accepted methods such as OAuth 2.0 and JWT to secure access to your solution.
Role-Based Authorisation: Defining clear user roles and permissions. After identifying a user, safeguards must be in place to prevent unwanted access to data.
3. Prompt injection
Generative AI gives users freedom to make requests that meet their specific needs. This freedom makes AI agents immensely powerful tools to enable users to be more productive and find unique solutions to business problems. This freedom can also be misused and kept under reasonable control in a business environment.
Challenges
Prompt injection is a technique where unintended or malicious instructions are embedded within the input given to an AI model, particularly one that processes natural language. This method aims to exploit the model’s design to perform actions or generate outputs that developers did not intend and that might be harmful or unauthorised.
Mitigation
Prompt control: By controlling access to the prompt, businesses can control the capabilities of the AI agent and implement guardrails to prevent exploitation.
Input Sanitation: Input from the end user should be examined to detect any possible injections to circumvent access controls or execute unintended functions.
Access controls: Access to data and application functions should be deliberate and controlled. Agents should have the minimum amount of authority to perform their intended functions.
4. Over Reliance
Generative AI increases productivity and creativity of employees when used effectively. As users integrate AI into their everyday workflow, it is natural to become more reliant on the powerful features that AI provides.
Challenges
Over Reliance on AI within business applications can pose significant security concerns, as it may lead to vulnerabilities and risks that could compromise business operations, data integrity, and stakeholder trust. When businesses become too dependent on AI solutions without fully understanding or managing their limitations and potential failure points, they expose themselves to various risks.
Mitigation
Human interaction: While AI can provide extensive insight, generative AI is not perfect. AI output should not be trusted blindly. Output should be fact checked periodically or when questionable.
Documentation of functionality: AI systems require frequent updates and maintenance both in tooling and models. As AI agents are built, they may perform certain tasks automatically as part of their design. It is important to document and understand these functions should they need to be performed manually during an outage of the AI. Businesses should implement balanced strategies that combine AI capabilities with human expertise, ensuring that AI systems are supportive tools rather than infallible solutions. It is crucial to maintain robust oversight mechanisms, conduct regular audits and updates, and foster a culture of continuous learning and adaptation to address the security challenges associated with overreliance on AI.
Best practises for ensuring a secure AI framework
As businesses increase their use of generative AI, some general best practices can go a long way in keeping usage safe and secure. Setting a proper foundation early will reduce the risk of security incidents and data leakage going forward.
Stay up to date: The world of generative AI moves fast. New models, model updates, and tool updates are released frequently. New models bring faster speeds, more capabilities, and lower costs. Model and tool updates mitigate security issues, patch bugs, and introduce enhancements. If you are not staying up to date, you are not only missing improvements, but also putting your business at risk. It is important to establish a regular cadence for installing, testing, and deploying updates for all aspects of your AI solution. During this update cycle, it is also a good idea to educate your users on new capabilities as well.
Minimise Authority: Whether building your own AI solutions or utilising tools like Profound AI, always start with a zero-access state. Add access to data elements, documents, and functions one at a time until your desired output is achieved. This minimises the opportunity for data leakage, AI overreach, or unintended results that could cost your business time and money. Once the desired output is achieved, thoroughly test your agent with requests of varying complexity. This will uncover any additional access needs that may have been missed during development.
User Training: Educating your user base on proper usage of AI is just as important as your implementation of AI functionality.
Move into the future with secure AI
As generative AI continues to evolve and become more integral to business operations, the importance of robust authentication and authorisation measures will only grow. By implementing these security best practices, businesses can confidently leverage the power of AI while protecting their valuable assets and maintaining user trust.
Ready to learn more about how Profound AI and impact your business? Schedule a demo and call with one of the Logicmate team and learn how AI can transform your business applications today!