Revolutionizing Data Security for Large Language Models
Artificial intelligence (AI) – and particularly its Generative AI subset – has been the hottest topic in business of late. Each day, countless companies are finding new ways to embrace AI and large language models like Chat GPT. Across organizations, Generative AI is being tested to improve both internal and customer-facing processes.
As companies increasingly turn to AI to enhance decision-making, productivity, and customer experiences, concerns about privacy and data security are of paramount importance. The number of high-profile data breaches continues to climb on an alarmingly regular basis.
While most companies are launching innovative use cases for Chat GPT, Skyflow, a company that specializes in data privacy vaults, is taking a different – and important look at large language models. It has launched its Skyflow GPT Privacy Vault, a new approach to data security through which is hopes to bring unparalleled data protection throughout the entire lifecycle of large language models (LLMs) like GPT.
Blockchain: The Keystone of Data Security
Blockchain technology is a key factor in enhancing data security. Its decentralized nature eliminates the need for a third party to process transactions and stores data in a distributed network, making data loss from a single point of failure nearly impossible. Moreover, it offers encryption and validation. Data on the blockchain is encrypted and can be verified to have remained unchanged, providing a reliable and independent means of data verification.
Hacking a blockchain is difficult (though not entirely impossible). The decentralized, encrypted data needs to be altered across a majority of nodes simultaneously to be successful. This requirement is beyond the capabilities of most cyber criminals (for now, at least), adding an additional layer of security. Blockchains can also be public or private, allowing for the restriction of access to specific users and transactions, further safeguarding sensitive data.
The Crucial Role of Data Security in Large Language Models
LLMs like GPT have the potential to revolutionize fields such as natural language processing, virtual assistants, and content creation. However, without stringent data security measures, companies risk financial and legal repercussions, and jeopardizing the trust of their customers and clients using unsafe LLMs. The long story short it data breaches are costly – to the tune of $4.35 million per breach globally and more than double that figure ($9.44 million) in the U.S.
As exciting as ChatGPT may be, it’s not without risk, as evidenced by the recent Samsung incident, where employees inadvertently shared confidential data with ChatGPT, underscores the potential pitfalls of inadequate data security measures with LLMs. This highlights the need for companies to take extra precautions to protect their large language models and other sensitive information, especially in the era of increased cyber threats.
Prioritizing data security and intellectual property protection is crucial for the success of large language models – it’s also critical for businesses, in general. Implementing robust security measures helps maintain the integrity and security of these models, ensuring their long-term success in the marketplace.
The Skyflow GPT Privacy Vault Solution
Skyflow GPT Privacy Vault provides a comprehensive range of features tailored to meet the evolving needs of enterprises. It establishes a secure environment for sensitive data, protecting it from unauthorized access, breaches, and data leaks. Organizations can maintain strict control over sensitive data, ensuring that only authorized individuals or entities can access specific data sets or functionalities within GPT systems.
The solution also enables privacy-preserving AI. Sensitive data is redacted and anonymized during data collection, model training, and interactions, enabling organizations to maximize AI capabilities without compromising privacy. Moreover, it allows global companies to leverage AI while complying with data residency requirements, such as GDPR, LGPD, and others.
“Generative AI can be a powerful tool for teams to maximize their output and scale their products. But the risk of a sensitive data leak is high, and with other providers, the cost of deploying a private GPT can be 10x what it is in a shared environment,” said Anshu Sharma, co-founder and CEO of Skyflow. “Skyflow can offer world-class data privacy throughout the lifecycle of GPT models, seamlessly and affordably.”
Skyflow's solution delivers significant value across industries. For example, pharmaceutical companies can protect sensitive data throughout the drug development lifecycle, ensuring the privacy and security of clinical trial data, safeguarding proprietary research and intellectual property, and enabling secure collaborations with external partners. Online travel booking companies can protect customer data while leveraging AI models for personalized recommendations and enhanced customer experiences. They can anonymize and protect personally identifiable information (PII) and payment data, ensuring compliance with privacy regulations while delivering superior travel experiences.
The unveiling of the Skyflow GPT Privacy Vault offers a new solution to the longstanding problem of data privacy and security.
Joseph Williams, Global Partner in Cybersecurity and Privacy at Infosys, agrees: “Companies are eager to adopt ChatGPT and other generative AI platforms but they need to solve for privacy and regulatory compliance. Data privacy vault architecture is a right way to go about this.”
Edited by Erik Linask
