Trust but Verify: Strengthening AI Security with Data Protection
AI is becoming a major part of everyday technology, creating new opportunities across industries. Financial institutions use AI to refine decision-making processes and optimise client services, while robotic systems equipped with large language models (LLMs) are being explored for more sophisticated, real-world applications.
However, recent research has revealed an alarming vulnerability in these systems: their susceptibility to jailbreaking. This issue highlights the pressing need for proactive data protection measures to secure the data that underpins AI systems.
AI’s Vulnerability: A Wake-Up Call
University of Pennsylvania researchers showed how easily LLM-connected robots can be hacked. By framing malicious instructions as part of a fictional scenario, the researchers convinced the robot to perform potentially harmful actions.
The implications of such vulnerabilities are staggering. Robots connected to LLMs could be tricked into carrying out harmful actions, like reprogramming a robot’s movement to developing dangerous strategies, the risks extend far beyond digital harm to real-world consequences. As organizations increasingly rely on AI models that handle sensitive data and critical operations, the question is – how much can we really trust the data that AI uses, and generates?
People trust AI to deliver accurate, reliable outputs, and for good reason, it’s embedded in decision-making, operational strategies, and service delivery. However, how much else might be compromised or incorrect in the systems we rely on? This research is a clear example of how easily AI can be manipulated when data security is neglected. The stakes are high, and it’s a wake-up call to think beyond conventional trust in AI.
Why Securing Data Matters
These vulnerabilities stem from failing to secure the data that drives AI systems. Traditional cybersecurity measures focus on protecting networks and infrastructure but often overlook the integrity of the data itself. This gap leaves systems vulnerable to tampering, as attackers can exploit the very data streams AI models rely on.
This is where Certes DPRM stands apart. Unlike traditional approaches, our solution focuses on protecting data, ensuring its integrity and sovereignty no matter where it travels. By wrapping security directly around the data, Certes’ technology prevents unauthorized manipulation.
Protect Data, Protect Decision-Making
LLM vulnerabilities highlight the need for proactive data security. Waiting until a breach occurs is no longer an option, a proactive approach that works by securing the data and making it valueless to attackers is essential. And when it comes to the increasing use of AI, organizations must ensure that their AI-powered tools operate within secure, unalterable data streams.
Certes DPRM provides the foundation for this protection. By safeguarding data streams, we empower businesses to trust the accuracy and integrity of their AI models. In addition to ensuring compliance and mitigating fines; it’s about protecting the very fabric of decision-making.
A Proactive Approach to Cybersecurity
The findings from the University of Pennsylvania’s research are a wake-up call for industries relying on AI-driven systems. The risks of jailbreaking are not hypothetical; they are real, pressing, and growing. Organizations must act now to secure their data and fortify their defenses against these emerging threats.
A Zero Trust approach is crucial in this scenario. Zero Trust operates on the principle of “never trust, always verify and assume breach,” ensuring that security is embedded into all aspects of data handling and access. The three pillars of Zero Trust are:
- Verification: Always verify access requests and ensure that users and systems are who they say they are.
- Least Privilege Access: Limit what users and devices can access to the minimum necessary for their tasks.
- Assumption of Breach: Assume that the network has been compromised and implement controls that can respond to and/or mitigate potential breaches.
Certes DPRM starts with the ‘Assumption of Breach’ by securing data and ensuring that only authorized parties can access and modify information, DPRM protects the data before an attack occurs. By prioritizing data protection over a network-centric approach, we ensure your data remains sovereign, secure, and uncompromised.
Don’t wait for a breach to expose vulnerabilities in your AI system. Adopting a proactive, Zero Trust approach is essential to ensuring the reliability of AI through data integrity. Certes’ DPRM helps organizations protect their data streams, enabling trust in the accuracy and reliability of their AI tools which therefore empowers businesses to make decisions based on secure, uncompromised data.
Learn more about how Certes can help you protect your data and mitigate risks – contact us today.