With the regular construction of new protocols, constant security enhancement, and a move from lab demonstrations to real-world implementation, quantum cryptography is a rapidly emerging topic in quantum information science. The industry is rapidly expanding in order to commercialize the technology. Quantum computing will not just put present cryptography to the test; it may forever alter our approach to data encryption.
Much of the discussion around quantum computing revolves around the opportunities it brings in fields such as electric vehicles, supply chain optimization, and chemical research. However, others are concerned about the impact of quantum computing on cryptography and if present encryption methods would still be adequate for data protection.
While this threat is still years away, data center managers and security teams should be aware of it and work together to prepare for the future.
As quantum computing advances, quantum computers might theoretically break many of the encryption mechanisms that organizations employ today. Quantum assaults may endanger asymmetric and symmetric cryptography encryption systems because quantum computers may be capable of conducting decryption calculations. Many researchers, however, are investigating encryption approaches that can safeguard data center infrastructure from quantum attacks.
What is Quantum Cryptography?
Conventional public key cryptography uses mathematical functions like factorization to encode information in a way that would take current computers many years to break. However, working quantum computers (which are not yet a reality) could theoretically break this kind of encryption in a matter of days, hours, or seconds.
Quantum cryptography has been developed to secure electronic communications by applying the peculiar laws of quantum mechanics to computer algorithms. This technology produces a random bit string that is only known to two parties, who can use it to encrypt and decrypt electronic communications.
One useful property of quantum cryptography is the ability to tell if anybody is “eavesdropping” on secure communication. This is possible because of the effect observation has on quantum states: measuring a quantum system alters it. If a third party tries to read the information that was transmitted in a quantum state, that information will be altered and the eavesdropping can be detected.
The quantum cryptography market was estimated to be $89 million in 2020. Analysts predict it will keep growing at a CAGR of 19.1% to reach $214 million in 2025.
Increased digitization increases the need for secure transmission of information, and the COVID-19 pandemic sped up the pre-existing trend of digitization across all industry sectors. For example, in healthcare, most physicians are now keeping digital records. In many countries including the United States, these records must be kept secure by law.
While there is no working quantum computer that can break traditional cryptography as yet, scientists and industry commentators expect such technology to mature by the end of this decade. This means that information sent now could be intercepted and stored by a malicious party and then decrypted in the future when the technology is there to do it.
Because of this, there are a number of companies offering advanced quantum cryptography services in the market already.
CryptoNext Security, a French startup, is providing cryptographic standards to secure IT infrastructure. IdQuantique is a Swiss company that upgrades existing enterprise-level encryption with quantum cryptography. Qrypt, a New York-based technology startup, is another major player in this sector. Single Quantum is a Dutch provider with technology that can detect single photons with high precision for photonic (and quantum) communications.
How Quantum Computing Poses Threat to Traditional Cryptographic Systems
Encryption is the backbone of cybersecurity, keeping data and systems secure. Quantum computing threatens to make today’s encryption obsolete. Developing quantum-secure encryption is one of the main challenges facing the cybersecurity sector today, highlights Michael Redding, chief technology officer at Quantropi.
Read Also: Biometric Authentication: Challenges And Opportunities
Explaining how quantum computers work is challenging. It involves presenting complicated scientific concepts like superposition, which allows groups of qubits to create multidimensional computational spaces. For those who do not have a background in quantum physics, quantum computing can seem more like science fiction than computer science.
Explaining what quantum computers do, however, is much easier. In essence, they leverage the behavior of subatomic particles to increase computation speed exponentially. When Google announced in October 2019 that it had achieved “quantum supremacy,” it was celebrating the fact that it had used quantum computing to solve a complex mathematical problem in 3 minutes and 20 seconds. How long would a conventional computer have taken to solve the same problem? According to Google, it would have taken at least 10,000 years.
Encryption is the backbone of cybersecurity. It is the tool that keeps critical data under lock and key. Without it, security and privacy would be impossible to achieve.
Hackers have a number of avenues for gaining unauthorized access to encrypted information. One popular method involves social engineering attacks that seek to trick someone into revealing the password that provides access to data. Rather than cracking the code, hackers using social engineering attacks simply steal the key.
Data breaches provide another option for obtaining passwords. Reports of breaches regularly make the news, and each breach has the potential to put passwords into the hands of bad actors seeking to obtain access to encrypted data.
Brute force attacks represent a different approach to cracking encryption. Rather than trying to obtain the password from a user or stolen data, these attacks use computers to cycle through possible passwords until the correct one is found. Essentially, brute force attacks figure out passwords through trial and error, leveraging computers to do the work quickly and systematically.
Current encryption methods are considered effective in thwarting brute force attacks, as the most advanced encryption systems work with passwords or keys that are long and complicated or highly random. With today’s computers, deciphering the key through trial and error can take millions of years.
However, quantum computing changes the timeline for cracking today’s encryption. By exponentially increasing processing speed, quantum computers could break the most advanced keys commonly used today in minutes.
Quantum Key Distribution
Quantum Key Distribution (QKD) is gaining popularity, particularly among cybersecurity specialists, and for good reason. Traditional encryption methods are currently under threat from the rise of quantum computers, necessitating the development of a more secure way of encryption.
Indeed, the Quantum-Safe Security Working Group supports QKD as one of the solutions “to protect and future-proof data against developments in computer power, new attack strategies, weak random number generators, and the emergence of quantum computers.”
QKD works by sending millions of polarised light particles (photons) from one entity to another over a fibre optic cable. Each photon has a random quantum state, and all of the photons combine to form a bit stream of ones and zeros.
When the photons arrive at the endpoint, the receiver uses beam splitters (horizontal/vertical and diagonal) to “read” the polarization of each photon. The receiver does not know which beam splitter to use for each photon and has to guess which one to use.
After the receiver tells the sender which beam splitter was used for each of the photons in the sequence they were sent, the sender then compares that information with the sequence of polarizers used to send the photons. The photons that were read using the wrong beam splitter are discarded, and the resulting sequence of bits becomes a unique optical key that can be used to encrypt data.
The security of QKD stems from the ability to detect any intrusion on the QKD transmission. Because of the unique and fragile properties of photons, any third party (or eavesdropper) who tries to read or copy the photons in any way will change the photons’ state.
The change will be detected by the endpoints, alerting them that the key has been tampered with and must be discarded. A new key is then transmitted. Moreover, since the keys generated are truly random, they are protected from future hacking attempts.
Challenges in Building a Practical Quantum Computer
Qubit decoherence is arguably the most difficult quantum computing difficulty. Qubits are extremely sensitive to their surroundings, and even minor perturbations can cause them to lose their quantum capabilities, which is known as decoherence. The fight to master decoherence may necessitate the development of novel materials, new computational tools, and a thorough examination of diverse quantum approaches. It’s not simply the gear that makes quantum computing difficult.
Quantum algorithms are thus significantly more complex than classical algorithms, necessitating creative approaches to computing issues. Because of its complexity, quantum computing scientists, engineers, and entrepreneurs face the following issues.
1. Error Correction
Most experts would consider this the biggest challenge. Quantum computers are extremely sensitive to noise and errors caused by interactions with their environment. This can cause errors to accumulate and degrade the quality of computation. Developing reliable error correction techniques is therefore essential for building practical quantum computers.
2. Scalability
While quantum computers have shown impressive performance for some tasks, they are still relatively small compared to classical computers. Scaling up quantum computers to hundreds or thousands of qubits while maintaining high levels of coherence and low error rates remains a major challenge.
3. Hardware Development
Developing high-quality quantum hardware, such as qubits and control electronics, is a major challenge. There are many different qubit technologies, each with its own strengths and weaknesses, and developing a scalable, fault-tolerant qubit technology is a major focus of research.
4. Software Development
Quantum algorithms and software development tools are still in their infancy, and there is a need for new programming languages, compilers, and optimization tools that can effectively utilize the power of quantum computers.
5. Classical Computers Interfaces
Quantum computers won’t replace classical computers; they will serve as complementary technology. Developing efficient and reliable methods for transferring data between classical and quantum computers is essential for practical applications.
6. Standards and Protocols
As the field of quantum computing matures, there is a need for standards and protocols for hardware, software, and communication interfaces. Developing these standards will be essential for ensuring compatibility and interoperability between different quantum computing platforms. We should also throw in benchmarking — the ability to measure performance standards is still in its infancy for quantum computing design, development and operation.
7. Trained Talent
The number of people properly educated and trained to enter the quantum workforce is small and spread across the world. Finding the right workers is a challenge. In a chicken-and-egg scenario, we won’t increase the number of people motivated to enter the quantum workforce until we have more practical quantum computers and we won’t have more practical quantum computers until we have more people motivated to become part of the quantum workforce.
8. Overall Expense
Perhaps this is an obvious outcome of all the above challenges, but expense remains a huge roadblock — or stumbling block — for quantum computing. The likelihood that two Steves will be slapping together quantum computers in their garage is an unlikely scenario. Quantum talent is expensive. Quantum hardware is expensive. Supply chains are complex, vulnerable and — you guessed it — expensive to establish and maintain. Dealing with these expenses and finding investments to offset these costs will likely be a standard duty of institutional scientists and commercial entrepreneurs for the foreseeable future.
Google’s Quantum Supremacy Claim
If the quantum computing age had begun three years ago, its rising sun might have been hidden beneath a cloud. In 2019, Google researchers claimed to have achieved quantum supremacy after their quantum computer Sycamore completed an esoteric calculation that would have taken a supercomputer 10,000 years to complete in 200 seconds. Scientists in China have already completed the computation in a matter of hours using standard computers. They claim that a supercomputer could completely defeat Sycamore.
“I think they’re right that if they had access to a big enough supercomputer, they could have simulated the … task in a matter of seconds,” says Scott Aaronson, a computer scientist at the University of Texas, Austin. The advance takes a bit of the shine off Google’s claim, says Greg Kuperberg, a mathematician at the University of California, Davis. “Getting to 300 feet from the summit is less exciting than getting to the summit.”
Still, the promise of quantum computing remains undimmed, Kuperberg and others say. And Sergio Boixo, principal scientist for Google Quantum AI, said in an email the Google team knew its edge might not hold for very long. “In our 2019 paper, we said that classical algorithms would improve,” he said. But, “we don’t think this classical approach can keep up with quantum circuits in 2022 and beyond.”
The “problem” Sycamore solved was designed to be hard for a conventional computer but as easy as possible for a quantum computer, which manipulates qubits that can be set to 0, 1, or—thanks to quantum mechanics—any combination of 0 and 1 at the same time. Together, Sycamore’s 53 qubits, tiny resonating electrical circuits made of superconducting metal, can encode any number from 0 to 253 (roughly 9 quadrillion)—or even all of them at once.
Starting with all the qubits set to 0, Google researchers applied to single qubits and pairs a random but fixed set of logical operations, or gates, over 20 cycles, then read out the qubits. Crudely speaking, quantum waves representing all possible outputs sloshed among the qubits, and the gates created interference that reinforced some outputs and canceled others. So some should have appeared with greater probability than others. Over millions of trials, a spiky output pattern emerged.
The Google researchers argued that simulating those interference effects would overwhelm even Summit, a supercomputer at Oak Ridge National Laboratory, which has 9216 central processing units and 27,648 faster graphic processing units (GPUs). Researchers with IBM, which developed Summit, quickly countered that if they exploited every bit of hard drive available to the computer, it could handle the computation in a few days.
Zhang and colleagues also relied on a key insight: Sycamore’s computation was far from exact, so theirs didn’t need to be either. Sycamore calculated the distribution of outputs with an estimated fidelity of 0.2%—just enough to distinguish the fingerprintlike spikiness from the noise in the circuitry. So Zhang’s team traded accuracy for speed by cutting some lines in its network and eliminating the corresponding gates. Losing just eight lines made the computation 256 times faster while maintaining a fidelity of 0.37%.
The researchers calculated the output pattern for 1 million of the 9 quadrillion possible number strings, relying on an innovation of their own to obtain a truly random, representative set. The computation took 15 hours on 512 GPUs and yielded the telltale spiky output. “It’s fair to say that the Google experiment has been simulated on a conventional computer,” says Dominik Hangleiter, a quantum computer scientist at the University of Maryland, College Park. On a supercomputer, the computation would take a few dozen seconds, Zhang says—10 billion times faster than the Google team estimated.
The advance underscores the pitfalls of racing a quantum computer against a conventional one, researchers say. “There’s an urgent need for better quantum supremacy experiments,” Aaronson says. Zhang suggests a more practical approach: “We should find some real-world applications to demonstrate the quantum advantage.”
Still, the Google demonstration was not just hype, researchers say. Sycamore required far fewer operations and less power than a supercomputer, Zhang notes. And if Sycamore had slightly higher fidelity, he says, his team’s simulation couldn’t have kept up. As Hangleiter puts it, “The Google experiment did what it was meant to do, start this race.”
