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quantum computing becomes the need for next-generation

The public has quickly come to understand over the past four or five years that the exquisite and detailed golden chandeliers, which resemble upside-down, skeletal, multi-tiered metal wedding cakes, are popular and approximate representations of quantum computers. These chandeliers are frequently seen in TV shows and films, frequently in the settings of mad scientist labs or megalomaniacal villain lairs.

But in a real quantum computer, the main component is a cooler called a dilution refrigerator, which combines helium-3 and helium-4 to keep the processors temperature at 0.015 degrees Kelvin, which is quite cold that is, -273.135C or -459.643F. The quantum processor itself is located at the bottom of the chandelier.

Because quantum computers store information in quantum bits or qubits, very low temperatures are required. They comprise a particle, such as an electron, that can exist in two states. When the particle is in superposition, quantum computers, and quantum algorithms can exploit the combined potential energy of the two states.

However, qubits are extremely brittle and cannot be controlled or handled at normal temperatures. Qubits are extremely sensitive and easily disturbed even at very low temperatures. Examples of noise that can disturb them include temperature fluctuations, variations in the earths magnetic field, electromagnetic interference from devices like mobile phones and Wi-Fi terminals, microscopic flaws in quantum gates, and other vibrations or acoustic interferences like the sound of a subway train rumbling or taxis rattling. The quantum state will decohere in response to any of these (and other) circumstances, which will either utterly randomize the data and make it meaningless or wipe it entirely.

Even a small amount of noise can cause decoherence and the qubits to lose their remarkable properties of superposition and entanglement. This long-term problem of noise in a quantum computing environment is making progress toward developing large-scale, fault-tolerant, robust quantum machines more difficult.

Until a quantum system is measured, superposition refers to its capacity to exist in several states simultaneously: It permits several states or locations for quantum things to exist concurrently. This implies that a single thing can exist in two states simultaneously. The essential method of storing data in quantum computers is for particles to be in superposition.

When two or more quantum particles are linked together, even if they are separated by vast, galaxy-spanning distances, any change in one will cause a simultaneous change in the other. This phenomenon is known as quantum entanglement. Quantum computers can do several computations at once because of entanglement, which greatly boosts their processing capacity and accelerates them well beyond the capabilities of even the largest, most sophisticated, and most potent conventional supercomputers.

Thus, the pursuit of a solution or a suite of solutions to reduce noise is proceeding at a rapid speed. Several avenues are being explored, such as physically isolating qubits and creating ever-more-accurate control methods. It has become apparent that, like several other aspects of life, creating fault-tolerant, noise-immune quantum computers by human effort would require some walking before it can be considered a run. Currently, we are in the era of noisy, intermediate-scale quantum (NISQ) devices and it appears highly improbable that we will be able totally to tackle the noise problem using the devices and methods of today. It appears that everyone agrees that NISQ devices performance will increase gradually, although significant technical breakthroughs will be required before quantum

Quantum error suppression, error mitigation, and error rectification are some of the methods.

Although there are clear challenges in the process of creating and manufacturing quantum computers, it is thought that these obstacles can and will be solved. Thats why companies including the likes of Google, IBM, Intel, and Microsoft, having already spent billions of dollars on the technology, are ramping up their R&D investments in the sector, even as specialist startups developing solutions based on a combination of hardware and software for the prevention or mitigation of quantum errors are beginning to emerge.

Everybody involved is aiming to bring about the quantum utility era, in which solving issues needing a lot of processing power would naturally, practically, and economically make use of quantum devices rather than conventional computers. Various methods are being used as part of it. Because quantum computing will enable services to be accessible from anywhere in the globe, several businesses are attempting to integrate it into the cloud. It has indeed already occurred on an experimental scale. On May 4, 2016, about eight years ago, the first five-qubit cloud-access quantum computer in history went online. Within the first week of its launch, 7,000 research scientists signed up for access to the facilities, demonstrating its immediate popularity.

Three primary kinds of solutions have evolved as more has been discovered about the peculiar properties of quantum computing and the numerous challenges associated with managing a computational process based on quantum waves. The first is error suppression, which continuously analyzes whats happening in the quantum circuitry and qubits using the well-known characteristics of classical software and machine-learning algorithms. It then reconfigures the process design to make sure that the information stored in the qubits is better protected.

Error mitigation, the second method, is grounded in the fact that not all noise-induced errors lead to decoherence and, thus, program failure in quantum computing. An analog of echo-cancellation in telecom networks, or a kind of anti-noise filter to limit the propagation of errors, both during the computational process itself and in the final output, may be able to be loaded into a quantum system. However, such a computation will stray into paths that lead nowhere. Such a solution is incomplete since it just estimates noise rather than recognizing every detail of an occurrence, and it is more expensive because it requires running an algorithm several times for it to function.

Utilizing quantum error correction (QEC) is the third option. To minimize and rectify noise, information is encoded into several qubits in this instance. It functions, but to safeguard and manage a single logical qubit, the system has to transport a supercargo of many physical qubits. The ratio of these is often stated as one logical qubit for every 1,000 physical qubits (a very large and expensive overhead), however, some developers have lately said that under certain conditions, the ratios can be as low as 13:1 or even as low as 100:1. That could or might not be practical or profitable, but regardless of the ratio, QEC is costly and exceedingly challenging to operate.

More potent algorithms are also being developed in the meantime; the Quantum Approximate Optimisation Algorithm (QAOA) has shown to be more noise-resistant and applicable in todays constrained and imperfect quantum devices.

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It will take some time before quantum computing becomes useful. - Medium

The Quantum Threat to Digital Security

Quantum computing, once a theoretical concept, is rapidly becoming a reality. With this progression comes a significant threat to our digital security infrastructure. Traditional encryption methods, which have been the bedrock of cybersecurity for decades, are vulnerable to quantum attacks. As quantum computers gain in power and sophistication, they pose a risk to the current encryption methods, making the need for quantum-proof codes and post-quantum cryptography inevitable.

The Y2Q clock, or years to quantum, is a metaphorical countdown to a time when quantum computers will have the ability to crack modern cryptography. This would render current public-key cryptography useless, potentially exposing sensitive information and disrupting digital security globally. The development of quantum-proof codes and post-quantum cryptography is a race against time, a race to secure our digital future before the Y2Q clock runs out.

To address this imminent threat, the National Institute of Standards and Technology (NIST) initiated a public contest for post-quantum or quantum-resistant cryptography. The goal was to accelerate the development of new encryption techniques that could withstand quantum attacks. This urgency is further underscored by the passage of the Quantum Computer Cybersecurity Preparedness Act, which mandates government agencies to create a plan for transitioning to these new algorithms.

After a rigorous analysis, NIST selected CRYSTALS-Kyber as a winner, along with three other winners in the category of digital signatures. These algorithms are designed to be resistant to quantum attacks, providing a blueprint for the future of quantum-proof cryptography. However, these algorithms are based on lattice mathematics, a complex field that has its own potential vulnerabilities. Thus, the development of quantum-proof cryptography remains an ongoing challenge.

The transition to post-quantum cryptography is not a simple switch; it will take many years and require a significant overhaul of our current digital security infrastructure. Until then, messages sent with old cryptography may be readable with a future quantum computer. Thus, the need for quantum-proof codes is not just about preparing for the future; its about securing the digital communications we exchange today.

As we stand on the brink of the quantum revolution, it is clear that the future of cybersecurity lies in our ability to develop and implement quantum-proof codes. While the challenge is significant, so too are the opportunities. By embracing this new frontier, we can ensure the security of our digital world for decades to come.

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The Quantum Threat to Digital Security | Importance of Quantum-Proof Codes - Medriva

The Quantum Computing Cryptopocalypse Ill Know It When I See It

Can quantum computing break cryptography? Sure, it can. Can it do it within a persons lifetime? Yes. In fact, it will likely achieve this sometime within your career. Will it be a cryptopocalypse, as some experts suggest? Possibly. Advances in quantum computing mean that we dont necessarily have to wait for a large quantum computer running at supercooled strengths at sufficient qubits to run Shors algorithm (the best-known algorithm for factoring large numbers). There are newer, more sophisticated techniques on the table, such as combinations of attacks that can do what one brute force thing cant. So, it might not be time to panic, but it certainly is time to recognize that the threats and the benefits of quantum computing are here now, and security professionals need to ensure that they and the organization they work for are fully prepared.

These are just some of the thoughts that Johna Till Johnson, CEO at Nemertes Research, and Bob Burns, Chief Product Security Officer at Thales, shared with me on the latest episode of the Security Sessions podcast. Quantum has been discussed and theorized for years, and like the sudden rise of AI and generative technology that seemed to happen in early 2023, efficient and cost-effective use of quantum computing may also jump to a critical mass, and sooner than expected, despite its long voyage of research and development.

Bob asks, for example, What happens if we find that quantum computing actually can be used as a multistage step to break the factoring that doesnt involve Shors algorithm? What if we make incremental improvements or chain multiple results from a quantum computer thats realizable today? Those are the types of thoughts that keep him up at night. They are a testament to peoples relentless desire for innovation, as well as their abilities to advance by developing techniques, products, and solutions that werent even foreseen when the technology was first introduced.

You can say such things about almost any technology, of course the personal computer, the internet, and the smartphone they all became much more versatile than their inventors ever foresaw. But Johna provides an example of how this evolution in breaking cryptography happened just recently: researchers from the KTH Royal Institute of Technology in Stockholm used recursive training AI combined with side-channel attacks to crack one of NISTs quantum-resistant algorithms. In this case, it measured out-of-band information, specifically temperature changes corresponding to the processing inside the machine.

This has direct and ominous implications on what is known as a Q-Day that point in time when quantum computers can render all current encryption methods meaningless, as PCMagazine succinctly puts it. But as Bob points out, for calculating a Q-Day, I look at all my data, and I take the biggest amount of data that I want to keep the longest amount of time, and I predict how long it might take me to make that transition. But when my Q-Day ends up being, lets say, ten years away, my concern will be that someone forces that up to three of four years.

But both Johna and Bob point out that quantum computing is not all doom and gloom. There are lots of good reasons to deploy quantum computing, and many arent what most people think they are. Basically, Johna says they can solve problems for which the answer isnt the best or the only, but good enough by some consistent definition of good enough, for example, policy hardening. Whether this refers to a technical policy, a cybersecurity policy, or even a geopolitical policy, its helpful to know all the answers. In the latter case, a government might need to identify all the possible things it can do that will not result in war with a particular country. Thats the kind of thing that a classical computer with AI cant answer very well, but a quantum computer can because it effectively computes all the possible scenarios and outcomes at once. Its not great at telling you which of those scenarios is the absolute best, but it can help decision-makers draw a line to say, anything above this line, we dont go to war, and thats good enough.

Essentially, this is about taking on the category of problems that we dont even try to solve right now because theyre too hard; they require a technique of solving all possible scenarios at once and cherry-picking the ones that come above some definition of good enough. And those are all the problems that quantum can solve. Johna concludes, Once you let your imagination go with that, policy hardening is just kind of the tip of the iceberg.

About the author: Steve Prentice

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PierluigiPaganini

(SecurityAffairshacking, quantum computing)

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The Quantum Computing Cryptopocalypse Ill Know It When I See It - Security Affairs