Google has long been known for its strong security stance, developed over decades, which emphasizes a ‘shared fate’ approach to securing IT assets. That means there’s no line between the cloud provider’s responsibilities and the customer’s responsibilities; rather, it’s about sharing outcomes to better manage risk.
This is even more important with Generative AI (GenAi) entering the cyber security arena. While GenAI can help bolster security defenses, it’s also being used by cyber attackers to quickly generate sophisticated, highly personalized attacks. That’s why Google is continuously adapting its approach to security—and why it’s important for IT security pros to stay at the top of their game.
Google has baked security into its hardware, software, network, and system management technologies, with geographically dispersed data centers to keep its products and services running 24x7x365. Its security approach includes three main tenets:
Security by design: Security capabilities are continuously engineered into Google’s cloud platform to provide a defense-in-depth approach, which includes Google’s own private, encrypted network.
Security by default: Complementary defenses to reduce risk from cyberattacks and configuration errors, including default encryption for data at rest and in transit, as well as DDoS protection.
Security in deployment: Tools and guidance on security best practices, including Security Command Center, Google’s security and risk management platform to help with security misconfigurations and compliance issues.
Google’s approach to security is continuously evolving to deal with the ever-changing security landscape, which now includes generative AI. As a result, Google released a Security AI Framework to deal with this changing landscape.
Google’s Secure AI Framework (SAIF) is a conceptual framework for secure AI systems. Built on Google’s open, collaborative approach to security, SAIF is designed specifically for AI risks, from injecting malicious inputs to extracting confidential information in training data.
SAIF expands Google’s security approach into the AI ecosystem. For example, it includes monitoring inputs and outputs of generative AI systems to detect anomalies. Google is also using AI to beef up threat intelligence capabilities, including the speed and scale of response efforts.
So, by combining AI-based detection and analytics with its global threat intelligence network, Google is helping organizations counter AI-based cyber attacks. AI is also being used to provide consistency across organizations’ control frameworks, with secure-by-default protections in Google products such as Vertex AI and Security AI Workbench.
With the launch of Gemini—Google’s family of multimodal large language models—Google is providing AI-powered security to help detect and contain threats, reduce manual work for IT and security teams, and simplify security. Key features include:
Keeping up with these changes—and making sure your cloud environment is set up properly—is challenging for IT and security teams, especially if they don’t specialize in a particular cloud platform. That’s where Pythian can help.
As a managed service provider and premier Google Cloud Partner, we can be your reseller partner and help keep you secure. Our cloud security consulting services are backed by our deep technical expertise and implementation skills across cloud platforms, workloads, and use cases—so we can help with Google Cloud and any other cloud platforms in your environment.
For example, our Security Posture Analysis can help to identify risks and provide prioritized recommendations. And our Security Implementation Assessment provides a detailed analysis of a specific workload to understand the unique threat profile of different applications, platforms, and integrations.
Want to shore up your security with Gemini in Google Cloud and Pythian expertise? Contact us info@pythian.com.