Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

As in many companies around the world, Bitsight leadership believes that adoption and innovation through the use of artificial intelligence (AI) capabilities is crucial to the future of our company. From the top down, our employees are continually on the hunt for ways to leverage AI to improve business outcomes and customer productivity.

Masking large volumes of data isn’t just a bigger version of small-scale masking—it’s exponentially more complex. High-volume data masking introduces unique engineering challenges that demand careful balancing of performance, integration, accuracy, and infrastructure costs. In this blog, we’ll dive into the critical factors you must consider when choosing the right tool for large-scale data masking, helping you confidently navigate these complexities.

AI-powered solutions are becoming increasingly prevalent in enterprise environments, leading to a new trend in procurement: the need for comprehensive AI governance frameworks. This shift reflects a growing awareness of AI-specific risks and the need for more granular controls. As the founder of Nightfall AI, a startup building AI models for data security, I've navigated hundreds of procurement cycles and observed a rise in AI-specific requirements.

Microsoft Purview is a data governance and compliance solutions platform that helps organizations manage data security, classification, and regulatory compliance. It provides enterprises with tools to discover, classify, and protect sensitive information across hybrid cloud and on-premise environments. Microsoft Purview leverages automation and AI to streamline data governance processes, minimizing manual effort while improving AI accuracy.

Large Language Models (LLMs) have become central to many AI-driven applications. These models, such as OpenAI’s GPT and Google’s Bard, process massive amounts of data to generate human-like responses. Their ability to handle natural language has revolutionized industries from customer service to healthcare. However, as their use expands, so do concerns about LLM security. LLM security is critical because these models handle sensitive data, making them tempting targets for cybercriminals.

Eric Brüggemann, the new CEO of Code Intelligence, stepped into the role in September. We asked him about his vision of the role and future of AI and fuzz testing in securing automotive software.