Time to Rethink Your Data Security Strategy in the Generative AI Era

Implement context-based discovery, advanced data protection and intelligent monitoring to prevent information leaks while using AI.The world changed when OpenAI introduced ChatGPT, its generative AI chatbot that can interact in human-like conversations and generate artifacts or content.  Google, Microsoft, and others are coming online with their own generative AI tools based on OpenAI or proprietary large language models (LLM).  These tools can generate images, product designs and specifications, emails, articles, marketing posts, song lyrics, computer code, and other content.

Most companies want to use AI to optimize existing operations but may use it to transform their business models as the technology matures.  In the future, more companies will incorporate AI into strategic and revenue-generating activities.

Artificial intelligence has the potential to revolutionize business and security.  But it also poses significant risks to your data and business.  The risks of generative AI include loss of intellectual property, privacy concerns, lack of transparency, bias, discrimination, lack of human oversight, and high cost.  You also need to validate responses, since they may not be accurate.  They are only as good as the data models and algorithms.  Most of us already have experiences where the answers to our prompts aren’t quite what we expected.

Attackers can use AI to improve the sophistication and effectiveness of their attacks.  This could be generating better phishing emails or writing malware to steal sensitive data.

Misuse of AI can lead to major privacy and security issues since the models collect and process vast amounts of data.  As users access these tools to generate content, they feed them data so they can learn and provide better responses in the future.  Users could mishandle information by adding proprietary or regulated data to the prompts, resulting in a data breach, intellectual property theft, and other forms of abuse.

Enhanced Security to Minimize AI Risks

You may think that blocking access to AI services will eliminate the problems, but that won’t work.  There are many legitimate uses for generative AI to improve revenue and grow your business, so you need to take advantage of them.  If don’t, your competitors will.  Plus, it’s not feasible to prevent users from accessing these tools anyway.

Using AI will help you increase your competitive advantage, but you also need to mitigate risks from misinformation, sharing personal and proprietary data, and other vulnerabilities on employees and contractors.  If sensitive third-party or internal company information is entered into a public service, like ChatGPT, that information will become part of the chatbot’s data model and can be shared with others who ask relevant questions, resulting in data leakage.  Any unauthorized disclosure of confidential information may violate your organization’s security policies or privacy laws like GDPR or CCPA.

What to Look for in the AI Era

All employees who use ChatGPT and similar services should treat the information they post as if they were posting it on a public site, like Instagram, LinkedIn, or a blog.  They should not post personally identifiable information (PII), company, or client information that is not generally available to the public.  You need to guard against someone inadvertently copying and pasting customer data or proprietary code into ChatGPT.  There are currently no clear assurances of privacy or confidentiality in these systems and the information you post will be used to further train the model.  And will become the answer to someone else’s question.

Three key elements are essential to implement data security posture management (DSPM) to mitigate risk from using AI tools.

Context-based discovery

Discover sensitive data in files on servers, in the cloud, or endpoint devices using machine learning to understand the content and context of the information.  If an employee or contractor generates a document using an LLM that contains sensitive data, you can automatically identify it.

Enforcement rules immediately classify and add a label to files, quarantine or assign adaptive access control to authorized users.  Once identified, it’s easy to categorize obsolete, redundant, and sensitive data.  Remediation is automatic based on configurable rules which prevents violating privacy or other security standards.

Advanced data protection

By automatically encrypting and assigning dynamic access control to sensitive files, you can limit editing, printing, screenshots, and sharing of sensitive content with unauthorized users and systems both inside and outside your organization.  Encrypting files with FIPS 140-2 validated cryptographic modules meets the highest standards for security.  You ensure that only authorized users can access your sensitive data based on security policies that validate user access continuously.

This prevents users from uploading sensitive data to ChatGPT and other AI engines and protects your organization from insider threats and external attacks.  Centralized policies make it easy to protect, control and trace any document format, including file derivatives, regardless of file location.

Flexible exception management ensures that users can easily request changes to security controls without burdening IT or Security.  This data-centric approach supports on-premise, cloud, and remote digital assets and devices deployed by organizations, their contractors, and suppliers.

Intelligent monitoring

Track file access regardless of user, device, or location to monitor usage patterns.  A unique persistent identifier in each file ensures full visibility of file access and usage.  File access policies are dynamic to accommodate changing business requirements.

Since users must validate each time they access a file, changed policies are implemented in real-time.  Centralized policy optimization allows you to alter security to meet changing requirements.  Understanding the usage of sensitive data prevents information leaks by protecting and controlling the data before it gets into the wrong hands.


The Fasoo Approach

Discovering sensitive data, encrypting it with Enterprise DRM, assigning explicit access controls, and using intelligent monitoring to prevent information leaks, helps protect your sensitive IP and regulated data.  This allows you to control what users can upload to public generative AI services.  If you download something sensitive as a result of using AI, the same approach flags it as sensitive so you can mitigate privacy violations.

The Fasoo Data Security Platform (FDSP) helps you enable data security posture management to identify potential risks and vulnerabilities, implement proper security controls, and maintain data visibility throughout its entire lifecycle.  There are all key components of a sound data security strategy and they will serve you well as we all navigate the new world of AI.

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