TL;DR:
- Sentra introduces Sentra ChatDLP Anonymizer, a feature that redacts PII from ChatGPT and Google Bard prompts.
- ChatDLP enhances data security, ensuring compliance with GDPR and CCPA.
- It mitigates the risk of sensitive information being ingested into public large language models.
- Sentra’s ChatDLP engine offers comprehensive visibility and understanding of data security measures.
- The Anonymizer leverages innovative AI-based models to filter out sensitive information.
- It will be available for Google Bard users from June 12.
Main AI News:
Sentra, a leading provider of data security solutions, has introduced Sentra ChatDLP Anonymizer, a groundbreaking feature designed to redact Personal Identifiable Information (PII) from ChatGPT and Google Bard prompts. With this innovative tool, organizations can safeguard their critical data while capitalizing on the advantages offered by advanced technologies.
In today’s data-driven landscape, businesses face significant challenges in maintaining data privacy and complying with stringent regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Sentra ChatDLP Anonymizer addresses these concerns by minimizing the risk of sensitive information being ingested into public large language models (LLMs). By leveraging this cutting-edge solution, enterprises can uphold their commitment to data security throughout their technology stack.
The emergence of generative AI platforms has undoubtedly revolutionized productivity across various industries. However, this progress also raises legitimate concerns about data privacy and security. While LLMs have proven invaluable in enhancing efficiency, they pose a potential threat to the confidentiality of valuable information. Sentra’s ChatDLP engine, built on the foundation of its Data Posture Security Management (DSPM) platform, offers a robust solution to mitigate these risks.
Through ChatDLP, enterprises gain comprehensive visibility into their data and its security measures. This empowers organizations to gain a thorough understanding of their data landscape while ensuring that no sensitive information leaks to ChatGPT or Google Bard. By embracing these technological advancements with proper guardrails, businesses can confidently leverage AI language models without compromising data privacy.
Ron Reiter, Chief Technology Officer at Sentra, acknowledges the transformative potential of ChatGPT and Google Bard as industry-altering productivity tools. However, he also emphasizes the need for organizations to address the evolving security and data privacy risks associated with these technologies. In response to feedback from CISOs and security professionals, Sentra developed and delivered ChatDLP Anonymizer as a logical extension to their DSPM platform. By implementing this innovative solution, enterprises can ensure that employees harness the power of AI language models securely and responsibly.
Sentra’s ChatDLP Anonymizer employs state-of-the-art Generative AI-based Named Entity Recognition models and regular expressions to effectively filter out sensitive information such as names, email addresses, credit card numbers, and phone numbers. For enhanced data security, an enterprise version of the feature is available, enabling the redaction of ChatGPT and Google Bard prompts within the customer’s cloud infrastructure. This comprehensive approach ensures that sensitive data remains secure and compliant, thanks to privacy-preserving classification engine features that provide full visibility and control.
Conclusion:
The introduction of Sentra ChatDLP Anonymizer represents a significant advancement in data security in the face of generative AI technologies. By addressing concerns about privacy and compliance, Sentra empowers enterprises to embrace the productivity benefits of ChatGPT and Google Bard without compromising sensitive information. This innovative solution will likely drive increased adoption of AI language models in the market, as organizations can now confidently leverage these technologies while maintaining data privacy and security.
