QIZ Platform Deploys in Google Cloud to Manage Quantum Readiness

Organizations face a growing and immediate threat as attackers begin stockpiling encrypted data for future decryption using quantum computers, a practice known as “harvest now, decrypt later.” To address this escalating risk, QIZ Security is collaborating with Google Cloud to offer a comprehensive platform for managing the transition to quantum-resistant cryptography. The QIZ platform, deployable within Google Cloud environments, analyzes cryptographic risk across an organization’s entire digital footprint, spanning cloud workloads, on-premise systems, applications, databases and infrastructure. This provides identification of vulnerabilities and a post-quantum cryptography (PQC) risk prioritization, migration roadmap, and remediation guidance to help enterprises through the complex process of modernization. QIZ and Google Cloud aim to provide the secure foundation needed for organizations to build quantum-resilient security architectures.

QIZ Platform Delivers Cryptographic Discovery and PQC Risk Prioritization

The escalating threat of quantum computing is no longer a distant concern; attackers are actively employing “harvest now, decrypt later” tactics, collecting encrypted data with the intention of cracking it once sufficiently powerful quantum computers become available. QIZ Security is responding to this immediate risk with a new collaboration with Google Cloud, aiming to provide organizations with the tools to proactively assess and mitigate their cryptographic vulnerabilities. The collaboration intends to support enterprises in heavily regulated sectors, financial services, government, telecommunications, and critical infrastructure, as they shift toward post-quantum security. Industry momentum is building, driven by tightening PQC regulations and rapid advancements in quantum computing; QIZ and Google Cloud are positioning themselves to move organizations beyond awareness of quantum risk toward practical management of enterprise-wide PQC migration. The companies state that organizations can now begin building quantum-resilient security architectures, signaling a shift from theoretical preparation to actionable implementation of quantum-resistant defenses.

Google Cloud Enables Scalable Post-Quantum Cryptography Management

This proactive threat demands immediate attention to cryptographic vulnerabilities, extending beyond theoretical risk to a present-day challenge for organizations across multiple sectors. This partnership leverages QIZ’s cryptographic posture management platform within the Google Cloud infrastructure, offering enterprises unified visibility into cryptographic risks spanning both cloud and on-premise systems. Organizations can now analyze cryptographic risk across a broad spectrum of digital assets, including cloud workloads, applications, databases, and core infrastructure, extending the scope of security beyond traditionally cloud-focused solutions. Scalability is central to this approach, allowing organizations to manage quantum readiness across distributed environments and maintain ongoing governance and regulation conformance. According to the companies, QIZ and Google Cloud provide the secure, scalable foundation enabling organizations to modernize their cryptographic posture while maintaining operational resilience. This collaboration is particularly relevant for heavily regulated industries like financial services, government, and critical infrastructure, as they prepare for a decade-long cybersecurity transformation towards a quantum-resistant future and begin building resilient security architectures immediately.

Organizations can now begin building quantum-resilient security architectures – starting today.

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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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