TL;DR:
- Dig Security enhances Dig Data Security to safeguard data fed into Large Language Models (LLMs).
- New capabilities enable secure training and deployment of LLMs while maintaining data integrity.
- DSPM scans and classifies sensitive data across cloud accounts, ensuring AI models are not trained with critical information.
- Data detection and response feature allow tracking and control of data flow within AI model training corpuses.
- Data access governance identifies AI models with API access to organizational data stores.
- Dig Security’s comprehensive solution combines DSPM, DLP, and DDR capabilities in one platform.
Main AI News:
Cloud data security provider, Dig Security, has taken a significant step forward in safeguarding sensitive information processed through large language model (LLM) architectures with the latest additions to its Dig Data Security offering. These new capabilities aim to bolster the security, compliance, and visibility of the data fed into AI models, ensuring organizations can confidently leverage the power of LLMs without compromising on data integrity.
In an era where data breaches pose significant threats to organizations, Dig’s data security posture management (DSPM) offering emerges as a game-changer. With DSPM, customers can now seamlessly train and deploy LLMs while keeping a vigilant eye on the confidentiality and privacy of the data used. The implications of this advancement have not gone unnoticed, as industry experts recognize the pressing need to mitigate risks associated with AI model usage.
Jack Poller, an esteemed analyst at ESG Global, highlighted the significance of Dig’s new data security capabilities, emphasizing the growing importance of safeguarding sensitive data as the adoption of AI technology continues to surge. He emphasized that Dig Security’s innovation positions the company at the forefront of seizing opportunities in the rapidly evolving market.
The new capabilities will be available to all of Dig’s existing customers as part of the comprehensive Dig Data Security offering. What sets this offering apart is Dig’s ability to scan and scrutinize every database across an organization’s cloud accounts thoroughly. This enables the detection and classification of sensitive data such as Personally Identifiable Information (PII) and Payment Card Industry (PCI) data. Additionally, it allows organizations to monitor data access rights and user roles, offering granular control over data use.
Organizations have long struggled with the daunting task of discovering and accurately classifying data, and the challenge is magnified with AI models due to their opacity. However, Dig’s data detection and response mechanisms empower users to trace data flow within AI model training corpuses, identifying potential data vulnerabilities. By proactively addressing these issues, organizations can mitigate the risk of inadvertently using sensitive data for AI training purposes.
The importance of data access governance cannot be overstated, and Dig’s new capabilities shed light on AI models with API access to organizational data stores. Through this groundbreaking feature, organizations can understand the extent of data exposure and take preemptive measures to protect sensitive information.
Dan Benjamin, the CEO, and co-founder of Dig Security stressed the comprehensiveness of the solution. It spans the entire cloud environment, covering databases even on unmanaged virtual machines. Benjamin further noted that the feature alerts security teams to sensitive data storage or movement, ensuring robust data protection.
Dig Data Security seamlessly integrates DSPM, data loss prevention (DLP), and data detection and response (DDR) capabilities into a unified platform. By doing so, Dig Security emerges as a true pioneer in the field, offering organizations a comprehensive and robust solution to safeguard their data when harnessing the power of AI through large language models. As the AI landscape continues to evolve, Dig Security is poised to remain at the forefront of ensuring data integrity and security for its customers.
Conclusion:
Dig Security’s latest advancements in data protection for Large Language Models address crucial security concerns in the growing AI market. By offering a comprehensive solution to safeguard sensitive data used in AI model training, Dig Security is well-positioned to capitalize on the increasing demand for AI security solutions. As organizations increasingly rely on AI technologies, Dig’s innovative approach ensures data integrity and compliance, making them a key player in the competitive data security market.
