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All of AI benchmarking at your fingertips What are spin qubits? | IBM Quantum Computing Blog IBM to acquire HRL Laboratories IBM commits $50M in quantum access for US Genesis Mission It’s time for cryptography to get its own abstraction layer This could be the largest synthetic code dataset yet How to measure the performance of a quantum computer | IBM Quantum Computing Blog Release News: Qiskit v2.5 is here! | IBM Quantum Computing Blog CoFrGeNets replace the ‘bones’ of transformer-based models How training environments can teach AI models to misbehave What’s new at IBM Quantum - Q2 2026 | IBM Quantum Computing Blog Modeling the chemistry of fusion reactor material | IBM Quantum Computing Blog Ponder This Challenge - July 2026 - Return of the Superheroes Apply to IBM Quantum Developer Conference 2026 | IBM Quantum Computing Blog Qiskit Paulice: postselected quantum error correction | IBM Quantum Computing Blog What is IBM’s nanostack chip architecture? IBM introduces the smallest computer chip in the world A new playbook for quantum optimization benchmarking Running AI on mixed hardware for speed and affordability Explore next-gen quantum algorithms with IBM Quantum Credits | IBM Quantum Computing Blog Allstate explores quantum computing for insurance portfolios | IBM Quantum Computing Blog Can LLMs discover quantum error correction codes? Prototype and validate fermionic circuits faster with ffsim | IBM Quantum Computing Blog Bringing the power of semantic AI to IBM Db2 The fast Fourier transform, how and why it works Building AI more like software The future of quantum takes center stage at NY Tech Week Qiskit Fall Fest 2026: Applications open | IBM Quantum Computing Blog IBM to invest $10 billion in quantum computing | IBM Quantum Computing Blog Renowned mathematician Subhash Khot joins IBM Research Ponder This Challenge - June 2026 - The Superhero Team Movies New Classroom Accounts expand quantum access for educators | IBM Quantum Computing Blog Qiskit Global Summer School 2026: Registration now open | IBM Quantum Computing Blog How researchers built a record-setting quantum circuit | IBM Quantum Computing Blog IBM charts a new research path with MIT How IBM is using quantum computing to understand the operating system of the universe How to use sample-based quantum diagonalization on IBM hardware Quantum-centric supercomputing simulates 12,635-atom protein | IBM Quantum Computing Blog A decade of quantum on the cloud | IBM Quantum Computing Blog Ponder This Challenge - May 2026 - The Powers of a Binary Matrix Where the frontiers of high-speed racing and computing meet Introducing the IBM Granite 4.1 family of models Building the future of computing, together Next-generation algorithms could move fusion from the lab to the grid Bringing quantum-centric supercomputing to Illinois What’s new at IBM Quantum - Q1 2026 | IBM Quantum Computing Blog Release News: Qiskit v2.4 is here! | IBM Quantum Computing Blog How IBM Quantum is enabling healthcare and biology research | IBM Quantum Computing Blog How an extra training step can unlock AI’s reasoning power IBM demonstrates extreme scale for content-aware storage with a 100-billion vector database Ponder This Challenge - April 2026 - The Unlabeled Clock IBM Research and ETH Zurich open a new era of innovation IBM’s newest time-series models cover a full range of enterprise prediction tasks Toward a transparent supply chain for AI Quantum computers take a step into real materials science Donating llm-d to the Cloud Native Computing Foundation Cleveland Clinic & IBM debut new quantum simulation workflow | IBM Quantum Computing Blog Turning turbulence into transcripts Like the information in a dream: IBM’s Charles H. Bennett receives ACM Turing award Doubling down on open-access quantum computing | IBM Quantum Computing Blog Unveiling the first reference architecture for quantum-centric supercomputing Realizing Feynman’s vision for the future of simulation | IBM Quantum Computing Blog IBM is working today to secure communication from tomorrow’s quantum risks Building PyTorch-native support for the IBM Spyre Accelerator Quantum simulates properties of the first-ever half-Möbius molecule, designed by IBM and researchers A look back at the International Year of Quantum | IBM Quantum Computing Blog TerraStackAI: Bringing Earth and space AI to Red Hat and the world Ponder This Challenge - March 2026 - Path game on a hole-riddled chessboard IBM demonstrates High NA EUV process capability on track for insertion below 2 nm nodes at SPIE 2026 Quantum Advantage Tracker: the race to advantage | IBM Quantum Computing Blog
It’s time for cryptography to get its own abstraction layer
Navaneeth Rameshan, Gregoire Messmer, Silvio Dragone, Marc Stoec · 2026-07-17 · via IBM Research

There was a time when developers had to understand how data was physically stored just to write or read a file. They worked with tracks and sectors and wrote large amounts of code to manage storage details. Filesystems changed that: They introduced a stable abstraction and removed that burden from developers.

Networking followed the same path. Developers once had to implement retransmissions and reliability themselves. TCP/IP, accessed through the sockets API, moved that complexity into a shared layer and made network programming significantly simpler.

The field of cryptography has not yet made that jump. Even today, developers still write and maintain hundreds of lines of security-sensitive code to perform what should be straightforward operations: sign, verify, encrypt, and decrypt. We’ve had crypto libraries and APIs for decades — but they bake the algorithm choice into the calling code. Each use embeds detailed choices that are hard to change later. Over time, this leads to fragile systems and expensive technical debt.

The answer is cryptographic agility — but making it real has remained elusive.

But IBM Research is working to change that. Recently, at the Eurocrypt 2026 workshop on Migration and Agility in Cryptographic Systems (MAgiCS), we presented a principled approach to solving the cryptographic agility problem. The key insight is simple: those choices don’t belong in application code — they belong in a layer that can be governed and updated independently.

The ideas were first shared with a broader audience at the PKI Consortium conference in Kuala Lumpur in November 2025, and the feedback was clear. Cryptographic transitions consistently stall because developers carry both the implementation burden and the operational complexity.

Since the initial presentation, the work has moved from concept toward practice. Alongside the research papers, we have begun a partial, work-in-progress reference implementation and supporting documentation. The goal is to enable the community to test, validate, and shape this approach early — and to finally introduce the kind of abstraction layer for cryptography that storage and networking have had for decades.

Intent-based cryptography: from “how” to “what”

At its core, our idea is simple. Applications should not decide how cryptography is performed — they should only express what they need. The details of algorithms, parameters, and implementations move into a layer below, where they can be managed centrally and updated over time.

To make this a reality, we devised a new, intent-based API that introduces a vocabulary based on “scopes.” A scope represents a class of cryptographic intent, such as standard digital signatures or authenticated encryption. Within each scope, different algorithms can be used interchangeably because they share the same input and output structure. This allows systems to evolve without breaking application code. A scope says what is needed; policy decides which algorithm satisfies it — set centrally, not written into application code.

This shift fundamentally changes how cryptography is used. Developers no longer have to encode low-level decisions across hundreds of services. Instead, cryptographic behavior becomes an operational concern. Security teams can define which algorithms are allowed and how they are used. Systems then enforce these decisions consistently at runtime. This is the move SDN made for networks — separating the control plane that decides policy from the data plane that does the work. And because policy is decided and enforced in one place, auditors get a clear, reliable view of what was used and why.

Cryptographic systems must adapt continuously: keys are renewed, standards evolve, and much of the pressure comes not from new algorithms alone but from vulnerabilities, compliance requirements, and operational decisions. The ability to change implementations quickly — without touching application code — is therefore essential. An abstraction layer enables exactly that, treating cryptographic backends as interchangeable providers behind a single interface. The same operation can run on a software library, a hardware accelerator, a cloud service, or a trusted execution environment. Most importantly, it cleanly separates what is needed from how it is done, and where it runs.

Why now: PQC as a once-in-a-generation opportunity

Moving to PQC is not just about swapping algorithms. In reality, many systems cannot adopt PQC without significant changes first. Dependencies need to be upgraded, interfaces evolve, protocols change, and applications must be re-tested end to end. Many systems will require updates, such as newer runtime environments (e.g., Java 27+), support of TLS 1.3, or integration with latest versions of dependencies (with possibly new interfaces). In short, PQC is forcing a large-scale rearchitecture across the industry.

This moment creates a rare opportunity. Since software and systems must be revisited, this is the right time to fix a long-standing architectural gap. Instead of repeating today’s model with new algorithms, organizations can introduce a proper abstraction layer and move to a fundamentally better state.

Treating PQC as a one-time migration will only recreate the same challenges in the future. Cryptography will continue to evolve, and systems need to be designed for that reality. Introducing a cryptographic abstraction layer is therefore a move the industry would not regret. It reduces developer burden, strengthens governance, and turns future changes from costly engineering efforts into controlled operational decisions.

Try it, challenge it, help shape it

Filesystems and sockets once looked like unnecessary layers of indirection. A decade later, they became the obvious foundation of modern systems. Cryptography is ready for the same shift.

A specification only becomes meaningful when it is tested in practice. That is why, alongside the technical papers, we are releasing:

We invite developers, architects, and security teams to explore the work, challenge the assumptions, and help shape its evolution. Because the question is no longer whether cryptography will need to change again — it’s whether we are finally ready to make that change easy.

References