Protecting Confidential Data in the Age of ChatGPT

Introduction

ChatGPT is revolutionizing the way enterprises work by providing a significant performance boost and reducing skill inequalities among employees. However, it also comes with the risk of accidental data leaks, potentially exposing confidential intellectual property and sensitive information. To address this challenge, organizations are turning to generative AI isolation and other emerging technologies that offer protection without sacrificing speed. In this article, we explore the risks associated with ChatGPT and how vendors are tackling the issue.

The Risk of Intellectual Property Loss

Employees using ChatGPT may inadvertently share confidential data such as pricing, financial analysis, and HR information with large language models accessible by anyone. Recent incidents like Samsung accidentally divulging sensitive data have increased concerns among security and management leaders.

To tackle this issue, organizations are looking towards generative AI-based approaches to solve the security challenge while balancing efficiency gains. They want to protect IP without inhibiting the potential for improvement offered by ChatGPT.

Protecting Data in ChatGPT Sessions

Cisco, Ericom Security by Cradlepoint, Menlo Security, Nightfall AI, Wiz, and Zscaler are some notable vendors offering solutions to secure ChatGPT sessions.

Ericom Security by Cradlepoint’s Generative AI Isolation

Ericom Security by Cradlepoint provides Generative AI Isolation that executes user interactions in a virtual browser within their cloud platform. This approach ensures data loss protection and access policy controls. It routes all traffic through their cloud platform, preventing sensitive data from being submitted to generative AI sites like ChatGPT.

Nightfall AI

Nightfall AI offers three different solutions to protect confidential data. Nightfall for ChatGPT is a browser-based solution that scans and redacts sensitive information in real-time. Nightfall for LLMs is an API that detects and redacts sensitive data used in training LLMs. Nightfall for SaaS integrates with popular cloud applications to prevent the exposure of sensitive information within various services.

The Future of Knowledge – Gen AI

Outright banning generative AI-based chatbots like ChatGPT can lead to the flourishing of shadow AI and the adoption of alternative AI apps. Instead, organizations are piloting and implementing gen AI-based systems that eliminate the risk at the browser level. Technologies like generative AI isolation provide the scale needed to protect thousands of employees from accidentally sharing confidential data.

Conclusion

To harness the potential of generative AI while safeguarding against data loss and compliance challenges, organizations must be proactive in addressing the associated risks. By staying updated on the latest technologies and techniques, CISOs and security teams can protect confidential data and use gen AI as a competitive advantage in the knowledge-based business landscape.

Source: How enterprises are using gen AI to protect against ChatGPT leaks