Before J.A.R.V.I.S Goes Haywire: The Need for FHE in AI Agents

Anyone who has seen the Iron Man movies has probably thought how great it would be to have your own J.A.R.V.I.S., Tony Stark’s personal AI assistant. According to recent reports, many of today’s tech giants are working on very similar AI agents, personal assistants who organizes your busy work schedule and handle tedious activities that reduce productivity.

OpenAI, Microsoft, Google, and others are investing heavily in AI agents as the next generation of AI after chatbots. They are actively developing agent software designed to automate intricate tasks by assuming control over a user’s devices. Imagine never needing to manage payroll, write memos, return messages, or even book your own travel reservations. The AI agent would automatically manage your basic work assignments, leaving you time to focus on more important matters.

AI Agents and Your Data

While this sounds great, companies should tread carefully before allowing such AI agents into their workplaces. By granting an AI agent access to corporate devices, companies introduce significant security vulnerabilities to their proprietary data and that of their clients.

For example, employees could unwittingly expose sensitive information to the AI agent, or they could inadvertently open avenues for unauthorized access to data stored on the shared devices.

In addition, utilizing AI agents for certain tasks, such as gathering public data or booking flight tickets, would lead to significant data privacy and security risks. Automated AI agents would have authorization to access and transmit personal and proprietary information, potentially leading to unwanted data disclosures that could lead to reputational and financial damage.

In fact, the AI agent software has an inherent security flaw at its core, namely that it revolves around a Large Language Model (LLM), the machine learning module of the AI. Every piece of information that the agent accesses and every interaction the agent conducts is necessarily grafted into its LLM and could be churned back by the AI agent to other users.

Fully Homomorphic Encryption Secures AI Agents

To address these security threats, a robust, proactive encryption protocol is needed to safeguard the sensitive data processed by AI agents. The most promising innovation in development to secure privacy from AI agents is Fully Homomorphic Encryption. FHE allows applications to perform computation on encrypted data without ever needing to decrypt it. The AI agent would be unable to store confidential information in its LLM because that private information would always remain encrypted thanks to FHE.

Chain Reaction is at the forefront of the race to design and produce a processor that will enable real-time processing of Fully Homomorphic Encryption. This cutting-edge technology will enable AI agents to serve as loyal aides and personal assistants, while preventing them from exposing proprietary or personal data. Corporate enterprises could then confidently take advantage of artificial intelligence to increase productivity and profits without fear that their code and employees’ sensitive information is being compromised.