Generative artificial intelligence (GenAI) has become a prevalent technology in today’s world, with over 55% of organizations either piloting or actively using this innovative tool. Despite the growing interest in the potential benefits of GenAI, security teams must prioritize implementing and safeguarding this technology according to industry and company best practices.
A recent poll conducted by Information Security Media Group (ISMG) revealed five common concerns related to the implementation of GenAI. Among these concerns, data security and the risk of sensitive data leakage are at the forefront of security teams’ considerations.
To ensure that organizations are prepared to securely implement GenAI, security teams can take proactive steps aligned with foundational cybersecurity best practices. By adhering to widely used security standards, CISOs can incorporate trustworthiness considerations into the design, development, deployment, and utilization of AI systems within their environments.
One essential step to prepare for GenAI is to implement a Zero-Trust Security Model. Zero trust is a fundamental aspect of any cyber resilience plan, as it operates on the assumption of a breach and verifies each request as though it originates from an unsecured network. Applying a zero-trust model can help organizations effectively manage and oversee GenAI tools operating in their environments.
Additionally, adopting Cyber Hygiene Standards is crucial in protecting against potential cyber threats and ensuring the ongoing viability of businesses. Meeting minimum standards for cyber hygiene can mitigate risks and safeguard against common threats, especially concerning privacy and potential misuse of AI.
Establishing a comprehensive Data Security and Protection Plan is paramount for GenAI implementation due to the critical nature of data security. Security teams should focus on implementing a defense-in-depth approach to fortify data security, enforce data labeling for sensitive information, and implement stringent data permissions to prevent unauthorized access.
Furthermore, defining an AI Governance Structure is essential before fully activating any GenAI solution. Organizations should establish processes, controls, and accountability frameworks to govern data privacy, security, and the development of AI systems. Implementing responsible AI standards within the governance structure is also crucial for ensuring the safe and secure use of GenAI.
In conclusion, the potential of GenAI to revolutionize security is evident in its ability to address challenges such as the cybersecurity talent gap by enhancing the productivity of defenders through automated remediation guidance. However, realizing this potential relies on securely implementing, managing, and governing GenAI to create a safer and more resilient cyber landscape for future generations.
Partner Perspectives from Microsoft Security offer further insights and guidance on effectively securing and leveraging GenAI technology for the betterment of cybersecurity practices.