UK to get ‘early or priority access’ to AI models from Google and OpenAI

June 12, 2023 Coin Telegraph

It’s unclear at this time what access the U.K. will receive, but the reported commitment could be the first of its kind.

British Prime Minister Rishi Sunak recently announced that Google DeepMind, OpenAI, and Anthropic — three tech outfits widely considered the global industry leaders in generative AI technologies — have agreed to provide the United Kingdom with early access to their AI models.

Sunak made the announcement during a speech opening London Tech Week, an event described by organizers as “a global celebration of tech, uniting the most innovative thinkers and talent of tomorrow in a week-long festival.”

He made the comment while explaining a three-part plan to ensure AI systems in the U.K. are deployed in a safe and secure manner. The first step, per a transcript of the speech, is to perform cutting-edge safety research:

“We’re working with the frontier labs - Google DeepMind, OpenAI and Anthropic. And I’m pleased to announce they’ve committed to give early or priority access to models for research and safety purposes to help build better evaluations and help us better understand the opportunities and risks of these systems.”

The prime minister went on to explain that the second step of the U.K.’s plan is the recognition that AI, as a technology, doesn’t “respect traditional national borders,” thus necessitating the formation of a global task force.

Finally, the third step, per Sunak, is to invest in both AI and quantum to “seize the extraordinary potential of AI to improve people’s lives.” He cited recent investments in the amounts of $1.125 billion and $2.75 billion, for compute and quantum technologies, respectively, as steps the U.K. had already taken towards accomplishing this goal.

It remains unclear at this time exactly what form of “early or priority” access the U.K. government will obtain or when such access will be afforded.

Google DeepMind, OpenAI, and Anthropic have historically offered betas and limited preview versions of their large language models (such as Google’s Bard, OpenAI’s ChatGPT, and Anthropic’s Claude). All three companies have also invested in both internal testing with company scientists and external testing with contracted experts.

The prime minister didn’t make it clear whether the U.K. would obtain earlier access to production models than the general public or contractors or if the commitment was simply to offer access to the government as well as other priority researchers.

These comments come at an active time for the U.K.’s regulatory efforts. Not only is parliament racing to come up with comprehensive protections for citizens relative to the recent generative AI boom, but it's also facing increasing pressure to regulate cryptocurrency, blockchain, and Web3 technologies.

Quantum miners would yield ‘massive’ energy savings for blockchain: Study

June 8, 2023 Coin Telegraph

Bitcoin mining

University of Kent researchers compared three quantum systems to an ASIC miner, and the quantum machines were demonstrably more energy efficient.

A pair of scientists from the University of Kent’s School of Computing in the United Kingdom recently conducted a study comparing energy consumption rates for current ASIC-based miners to proposed quantum-based solutions.

According to the team’s preprint research paper, the systems utilizing quantum computing demonstrably outperformed standard mining rigs in energy efficiency:

“We show that the transition to quantum-based mining could incur an energy saving — by relatively conservative estimates — of about roughly 126.7 TWH, or put differently the total energy consumption of Sweden in 2020.”

Bitcoin mining operations alone consumed more than 150 terawatt hours annually (as of May 2022), per the paper, putting into perspective the potential impact the proposed quantum-based systems could have.

The pair’s conclusions were based on experiments comparing three different quantum mining systems to an Antminer S19 XP ASIC miner.

The quantum mining devices were split between a system featuring a single layer of fault tolerance, another one with two layers of fault tolerance and one without any dedicated error-correction features.

As the researchers point out, blockchain mining is one of the few areas of quantum computing where error correction isn’t such a big deal. In most quantum functions, errors create noise that functionally limit a computing system’s ability to produce accurate computations.

In blockchain mining, however, success rates with state-of-the-art classical systems are still relatively low. Per the research paper, “A classical Bitcoin miner is profitable with only a success-rate of about 0.000070%.”

The researchers also note that, unlike classical systems, quantum-based systems can actually be fine-tuned over time for increased accuracy and efficiency.

While quantum computing technology is still considered to be in its infancy, the very specific problem of blockchain mining doesn’t require a full-service quantum computing solution. As the researchers put it, “a quantum miner is not, and need not be, a scalable, universal quantum computer. A quantum miner need only perform a single task.”

Ultimately, the researchers conclude that it should be possible to build miners using existing quantum technologies that demonstrate quantum advantage over classical computers.

Despite the potential energy savings, it bears mention that the researchers focused on a type of quantum computing system called a “noisy intermediate-scale quantum” (NISQ) system.

According to the preprint paper, quantum miners should demonstrate “massive” energy savings at a size of around 512 quantum bits, or “qubits” — a term somewhat analogous to classical computing bits.

Typically, however, NISQ systems only operate with about 50-100 qubits, though there doesn’t appear to be an industry standard.

While the energy savings might be feasible, the costs of building and maintaining a quantum computing system in the 512 qubit range have, traditionally, been prohibitive for most organizations.

Only D-Wave and IBM offer client-facing systems in the same range (D-Wave’s D2 is a 512-qubit processor, and IBM’s Osprey weighs in at 433), but their architectures differ so greatly that comparisons between their qubit counts are ostensibly meaningless.

Scientists propose quantum proof-of-work consensus for blockchain

June 1, 2023 Coin Telegraph

Coin Telegraph

Boson sampling was once considered a problem looking for a solution. Now, it might be the bridge that brings quantum computing to the blockchain.

A team of researchers from universities in Australia and the United States, working in collaboration with quantum technology company BTQ, recently published research proposing a novel proof-of-work (PoW) scheme for blockchain consensus that relies on quantum computing techniques to validate consensus.

Our new paper on using NISQ-era quantum sampling problems in proof-of-work blockchain consensus algorithms. In collaboration with @BTQ_Tech.https://t.co/MKAB2czqSk
— Peter Rohde (@drpeterrohde) June 1, 2023

Dubbed “Proof-of-work consensus by quantum sampling,” the preprint research paper details a system that the authors claim “provides dramatic speedup and energy savings relative to computation by classical hardware."

According to the researchers, current algorithms for solving PoW consensus puzzles are slow and require a significant amount of computation resources to process:

“Whereas classical PoW schemes such as Bitcoin’s are notoriously energy inefficient, our boson sampling-based PoW scheme offers a far more energy efficient alternative when implemented on quantum hardware.”

According to the paper, the quantum advantage provided by this scheme would also increase the difficulty of mining, thus making it possible to “maintain consistent block mining time” as the number of miners increases, further incentivizing continuing participation of “quantum miners.”

The sampling process the researchers refer to, boson sampling, isn’t a new one, but its application to blockchain technology appears novel. Boson sampling has shown promise in numerous quantum computing applications. Still, as a non-universal quantum computing solution (it has to be used in a system built for a specific task), its potential has been limited to a select few domains, such as chemistry.

However, according to the researchers, it may be the perfect solution for future-proofing blockchain applications and, potentially, lowering the environmental impact of mining on the Bitcoin blockchain and similar chains.

Aside from quantum advantage, quantum hardware also has a leg up on old school computers due to the nature of how blockchain mining works.

One of the current advantages of classical supercomputers over their new quantum cousins is the ability to “precompute” when handling the same class of problem regularly. But, when it comes to blockchain, such precompute is essentially wasted.

Mining is, as the researchers put it, a problem that is “progress-free.” No matter how many times a blockchain puzzle is solved to provide proof-of-work, the computer and algorithms processing the challenges don’t ever get any better at solving the problem.

This means that quantum computers, despite being notoriously challenging to develop and expensive to build and maintain, would ultimately be capable of validating consensus more efficiently than state-of-the-art classical systems.

How does quantum computing impact the finance industry?

May 4, 2023 Coin Telegraph

Coin Telegraph

Quantum computing could revolutionize finance by solving complex problems quickly, improving risk management and enhancing cybersecurity measures.

Why is quantum computing a double-edged sword in cryptography?

Cryptography and blockchain technology will surely not stay untouched by quantum computing; however, the direction remains a question.

Quantum computing presents both a threat and an opportunity for cryptography. While it has the potential to break many of the current encryption methods, it also has the potential to create new and more secure methods that are immune to attacks by classical computers.

QCs are exponentially faster than classical computers, which means they can quickly solve mathematical problems that classical computers would take years, decades or even centuries to solve. This includes the mathematical problems that underlie many of the encryption schemes used to secure digital communication and transactions.

For example, Shor’s algorithm can be used to efficiently factor large numbers, which is the basis for many public-key encryption algorithms such as RSA (the abbreviation refers to the name of the creators, Rivest–Shamir–Adleman).

However, quantum cryptography can also be used to create new cryptographic methods that are securer than classical methods. For example, quantum key distribution is a method to generate and distribute a secret key between two parties, the confidentiality and integrity of the information being exchanged can be ensured, even if a malicious entity intercepts the communication.

The mentioned features create some uncertainty in the future of QCs in blockchain technologies. It has the potential to break current encryption methods used in blockchain, which could compromise the security of digital assets and transactions. At the same time, researchers are working on developing quantum-resistant encryption methods for blockchains to counter this threat, such as CRYSTALS-Kyber public-key encryption by IBM. Additionally, QCs can enhance blockchains by increasing their processing speed and scalability, which can lead to more efficient and secure transactions.

What are the benefits of quantum computing for the finance industry?

The finance industry is optimistic about quantum computing. Tasks such as portfolio optimization, risk management and asset pricing have a great chance to be beneficiaries.

Grover’s and Shor’s algorithms can be applied to portfolio optimization. Portfolio optimization involves finding the optimal combination of investments to maximize returns while minimizing risk. Besides providing faster and more accurate calculations the technology can enable more flexible optimization strategies that take into account a wider range of factors, such as environmental, social and governance factors.

Another example could be asset pricing. Asset pricing is the process of estimating the value of financial assets such as stocks, bonds and derivatives. Traditional methods for pricing financial assets rely on complex mathematical models, such as Monte Carlo simulations, which involve simulating a large number of possible outcomes for a given financial asset and then using these simulations to estimate its value. Quantum Monte Carlo (QMC) can handle, for example, complex financial instruments, such as options, that have non-linear payoffs.

Traditional Monte Carlo simulations vs. Quantum Monte Carlo simulations

Here’s the billion-dollar question: Can quantum computers predict the stock market? While QCs may have some advantages over classical computers in certain financial modeling tasks, it is unlikely that they will be able to predict the stock market with complete accuracy. Additionally, as with any new technology, quantum computing also poses its own unique challenges and limitations that need to be addressed before its full potential in financial applications can be realized.

Many financial services companies have high expectations of QC’s effect on risk management. It involves identifying, assessing, prioritizing risks and taking actions to mitigate or manage those risks. Every step involves mathematical modeling and simulations for predicting risk outcomes, and time and accuracy play a crucial role in the process. Cybersecurity is an important part of risk management that can be enhanced by enabling more advanced encryption methods.

Encryption became a crucial measure in the banking industry that protects sensitive information from unauthorized access. It is used to secure communication channels between banking systems, websites and mobile apps and protect data on servers, databases and backups. Additionally, encryption is used to generate digital signatures that help ensure the authenticity of documents and prevent unauthorized modification or tampering of sensitive documents.

Why is it so challenging to incorporate quantum computers into existing technologies?

Despite the great potential of QC, the technology and its applications need to overcome several challenging barriers.

Working with qubits is an enormously challenging scientific task because they need to be isolated in a controlled quantum state, which is extremely fragile. The smallest change in the physical environment (vibration or temperature) can cause an imbalance, which is the collapse of the superposition. Complex preventive actions are required, such as supercooled refrigerators, insulation or vacuum chambers to protect the system from losing its equilibrium.

Another aspect of the challenge is that as a different paradigm, QCs require not only completely new hardware and software but also algorithmic solutions. Numerous articles discuss the potential of QCs in machine learning, artificial intelligence or cryptography. Less often emphasized that it does not only mean using QCs to run algorithms designed for classical computers (quantum-enhanced) but building completely new algorithms, which are leveraging the features of QCs.

QCs in banking can be a game changer due to the potential of multiplying the speed and volume of calculations and transactions. However, different financial institutions only started to experiment with their own quantum algorithms and the limits of those potentials are not clear yet. Quantum algorithms are algorithms that take advantage of the unique properties of quantum systems, such as superposition and entanglement.

One example of quantum algorithms is Grover’s algorithm, which can be used to search large, unstructured databases of financial data more quickly than classical algorithms. For example, it could be used to search for specific financial transactions or to identify patterns in financial data. Another example is Shor’s algorithm, which enables one to factor in large numbers more quickly than classical algorithms.

What are quantum computers?

QCs are new machines that can perform calculations much faster than classical computers, based on the principles of quantum mechanics.

The expression of QCs refers to a new type of machine based on the principles of quantum mechanics. Quantum mechanics is a division of physics that deals with the behavior of matter and light on the atomic and subatomic scales. The most valued property of QCs is that they perform certain types of calculations much faster than classical computers.

Classical computers store and process information in the unit of bits while QCs use quantum bits (or qubits). Bits represent information in a binary format and can have only two possible values: zero or one. Every piece of information going through a classical computer is essentially a long string of zeros and ones.

Qubits can exist in multiple states at once, a property known as superposition. This means that a single qubit can represent numerous possible combinations of zeros and ones; therefore, it can process a much larger amount of information than a classical bit.

Another exciting feature of qubits is the potential of “entanglement,” where qubit pairs are created. Modifying the state of one in the pair will change the state of the other qubit in a predictable way. This property gives extra power to QCs. Increasing the number of bits in a classical computer has a linear effect on the processing power, while adding an extra qubit to a quantum machine causes an exponential increase in the processing power.

How does quantum computing help the finance industry?

QCs are only in the developmental stage; experiments are already showing their great potential in the finance industry.

Based on the World Economic Forum’s estimate from 2022, national governments have invested more than $25 billion in quantum computing research, and over $1 billion in venture capital deals were closed in the previous year. Quantum computers (QCs) are in the early stages of development, and there are many technical challenges that need to be overcome before they can become practical tools for everyday use.

Nevertheless, they have already demonstrated great potential for applications in a wide range of fields. QCs have the ability to solve complex mathematical problems exponentially faster than classical computers, making them ideal for several complex tasks. The finance industry is one of the first runners in testing the technology. However, from the military to pharmaceuticals, logistics and manufacturing companies, several industries are experimenting with QC.

The mentioned features of QCs can have an enormous impact on the future of financial services. There are several tasks where financial forecasting and financial modeling can be supported by QCs for faster and more accurate processes. Notably, portfolio optimization, risk management and asset pricing are some of the most mentioned examples. However, their potential advantages and threats to cryptography make it important for financial service providers to monitor the technology.

Collaboration is crucial in the area of QCs due to the fact that technology and software development enable the revolution. Accelerating programs are initiated by the largest tech companies for experimentation with their hardware, software or cloud solutions, such as IBM, Microsoft, Google or Amazon.

Goldman Sachs has partnered with Microsoft Azure Quantum to explore the use of QCs for pricing. JPMorgan is experimenting with quantum solutions for optimization and risk management. HSBC announced its collaboration with IBM in 2022 to explore the use of QCs for pricing, portfolio optimization and risk mitigation.

Quantum vs. cloud computing: Key differences?

April 15, 2023 Coin Telegraph

cloud computing

Quantum and cloud computing are the future of computer operations. Here’s what they are, their applications, and their main differences.

Will quantum computing replace cloud computing?

A new trend is emerging, with cloud-based quantum computing combining both technologies and their advantages and providing direct access to quantum computers via the web using the cloud.

While quantum computing will not replace the cloud anytime soon, Big Tech companies are working on integrating the two solutions to get the most out of both worlds. Such integration can facilitate remote access to quantum computers using the cloud and be available to a broader range of users.

Cloud-based quantum computers can accelerate the pace of tech innovation, streamlining the work of researchers and developers who could access quantum hardware and computational resources via the cloud, leading to breakthroughs and discoveries faster.

A simple model for accessing a quantum processing unit (QPU) in the cloud

Businesses and individuals must overcome numerous challenges before being ready to integrate quantum and cloud computing. For instance, the complexity of accessing quantum computers and the expertise required to handle them make it challenging for the average person to use quantum solutions in the cloud. Another concern is security, as sensitive quantum algorithms must be safeguarded from unauthorized access or tampering, which is more prevalent in the cloud.

Quantum vs. cloud computing: Which is better?

Both solutions have benefits and drawbacks, and there is no winner between quantum and cloud computing. Eventually, they will be fully integrated to provide compelling and secure solutions for all kinds of businesses and individuals.

Before choosing between quantum and cloud computing, businesses must consider several factors such as cost, availability and specific requirements.

Quantum computing vs. Cloud computing

How does cloud computing work?

Cloud computing is hosted by specialized companies that maintain massive data centers to provide the necessary security, storage capacity and computing power for the support of the online infrastructure.

Cloud services are accessible via an internet connection and computing devices such as smartphones, laptops or desktop computers. Users choose a cloud computing hosting company and pay for the rights to use their services. Such services include the infrastructure needed to facilitate communication between devices and programs, such as downloading a file on a user’s laptop that would be instantly synced on the same user’s iPhone file folder.

Cloud computing has a front end that enables users to access their stored data with an internet browser and a backend made of servers, computers, databases and central servers.

The central servers use specific protocols’ rules to facilitate operations and ensure smooth communication between the cloud-linked devices.

Some of the available cloud hosting companies are foremost tech leaders such as Amazon Web Services, Microsoft Azure, Apple iCloud and Google Drive.

Advantages and disadvantages of cloud computing

Advantages:

Cloud computing allows businesses to scale their infrastructure on demand, which means they can quickly and easily add or remove servers as their needs change. This can help businesses handle sudden market demands without worrying about capacity constraints.
Cost-effectiveness for businesses as they do not need to invest in expensive hardware or software installations.
Cloud computing provides easy accessibility to data and applications from anywhere, as long as there is an internet connection.

Disadvantages:

Security is still a concern for cloud computing due to its reliability on an internet connection, which can be vulnerable to hacking attacks.
The high centralization of cloud servers means that services may go offline in specific locations during outages; even censorship resistance is compromised with centralized providers.

How does quantum computing work?

While a classical processor uses bits to process operations and conduct various programs, a quantum computer uses qubits to run multidimensional quantum algorithms.

Quantum computers utilize a variety of multidimensional algorithms to perform measurements and observations through qubits, which can represent 0 and 1 simultaneously. The processing power of such multidimensional spaces increases exponentially in proportion to the number of qubits added.

Quantum computers are smaller and require less energy than supercomputers, computers with a high level of performance as compared to general-purpose computers. A quantum processor is similar to the size of a laptop processor, while a quantum hardware system is made up mostly of cooling systems.

Quantum computers are sensitive tools with high error rates, which are prevented by keeping the hardware at a very cold temperature, about a hundredth of a degree above absolute zero. Such cooling systems are defined as superfluids that must be able to extra-cool down the processors to create superconductors.

Here, electrons can move through without resistance, generating quantum information more quickly and efficiently and creating complex multidimensional spaces proportional to the number of qubits added.

Advantages and disadvantages of quantum computing

Advantages:

Opportunities for several industries to develop and design advanced computer programs based on highly accurate, safe and efficient data
Enhanced and unbreakable data encryption methods for better fraud detection and general security of sensitive data
Unprecedented data processing speed to manage vast amounts of data at once, which is impossible on conventional computers
Quantum computing can help in the development of new materials, medicines and chemicals by simulating complex molecular structures.

Disadvantages:

Quantum computers are highly sensitive to external interference, such as temperature and electromagnetic radiation, which can affect the accuracy of the calculations.
Scarce availability and consequent lack of mass adoption don’t allow developers to assess quantum computers’ features and reliability properly
The requirement for a large amount of data to function correctly means businesses must invest in enormous data storage systems to accommodate quantum computers.

What is cloud computing?

Cloud computing — or “the cloud” — is an application-based software that distributes computing services throughout the internet, utilizing third-party servers, storage, databases, networking, software, analytics and intelligence to store and process data.

Before cloud computing, businesses had to buy and maintain their own servers containing enough space to prevent downtime and outages and manage peak traffic volume. Still, a lot of server space often went unused, wasting money and resources. The cloud computing ecosystem allows organizations to employ a more efficient and cost-effective solution without requiring expensive hardware, private data centers or software installation, focusing on innovation, dynamic resources and economies of scale.

Cloud computing was invented in the 1960s but became more predominant in the 2020s when a more productive computing system was required to handle the challenges of organizations’ remote working that emerged during the pandemic.

Thanks to cloud computing, many businesses can share services instantaneously at any time, other than managing, accessing, and storing data and applications remotely. Using the cloud, they benefit from scalable storage for files, applications and different types of information, saving time and money.

What is quantum computing?

Quantum computing is a development of quantum mechanics, a discipline that covers the mathematical description of the properties of nature at the level of atomic and subatomic particles, such as electrons or photons.

Quantum computing utilizes subatomic particles to turn computers into robust machines that can calculate and process data at a breakneck speed. They achieve extreme speed thanks to qubits (quantum bits) and their ability to exist simultaneously in one and zero states or any linear combination of the two. In contrast, conventional computers’ binary systems exist only with one (“on” or “true”) or zero (“off” or “false”) states. Qubits allow these particles to exist in multiple states simultaneously.

In other words, such an ability to live in both one and zero states at once enables quantum computers to process vast amounts of data simultaneously. This is impossible in binary-based computer systems that can only process one piece of information at a time.

Quantum computing emerged back in the 1980s when physicists Richard Feynman and Yuri Manin discovered that quantum theory and algorithms could be applied to computing with more efficient results than their classical counterparts.

Applied quantum computing is still in its infancy but will impact many industries, especially helping large organizations deal with enormous amounts of data faster and more efficiently.

Due to their ability to solve highly complex problems, such as processing huge amounts of data superfast or providing better prediction models in various fields, quantum computers could break existing encryption protocols, posing a threat to blockchain technology and cryptocurrencies.

ETH Merge Forks, Quantum Computing, Biden Draining Oil Reserves, DOJ Targets Criminal Crypto Use — Week in Review

September 25, 2022 Bitcoin.com

Bitcoin vs. Quantum Computers: US Government Says Post-Quantum World Is Getting Closer, CISA Warns Contemporary Encryption Could Break

September 20, 2022 Bitcoin.com

Why quantum computing isn’t a threat to crypto… yet

September 9, 2022 Coin Telegraph

Coin Telegraph

Quantum computing still has a long way to go before posing a threat to blockchain technology.

Quantum computing has raised concerns about the future of cryptocurrency and blockchain technology in recent years. For example, it is commonly assumed that very sophisticated quantum computers will one day be able to crack present-day encryption, making security a serious concern for users in the blockchain space.

The SHA-256 cryptographic protocol used for Bitcoin network security is currently unbreakable by today’s computers. However, experts anticipate that within a decade, quantum computing will be able to break existing encryption protocols.

In regard to whether holders should be worried about quantum computers being a threat to cryptocurrency, Johann Polecsak, chief technology officer of QAN Platform, a layer-1 blockchain platform, told Cointelegraph:

“Definitely. Elliptic curve signatures — which are powering all major blockchains today and which are proven to be vulnerable against QC attacks — will break, which is the ONLY authentication mechanism in the system. Once it breaks, it will be literally impossible to differentiate a legitimate wallet owner and a hacker who forged a signature of one.”

If the current cryptographic hash algorithms ever get cracked, that leaves hundreds of billions worth of digital assets vulnerable to theft from malicious actors. However, despite these concerns, quantum computing still has a long way to go before becoming a viable threat to blockchain technology.

What is quantum computing?

Contemporary computers process information and carry out computations using “bits.” Unfortunately, these bits cannot exist simultaneously in two locations and two distinct states.

Instead, traditional computer bits may either have the value 0 or 1. A good analogy is of a light switch being turned on or off. Therefore, if there are a pair of bits, for example, those bits can only hold one of the four potential combinations at any moment: 0-0, 0-1, 1-0 or 1-1.

From a more pragmatic point of view, the implication of this is that it is likely to take an average computer quite some time to complete complicated computations, namely those that need to take into account each and every potential configuration.

Quantum computers do not operate under the same constraints as traditional computers. Instead, they employ something that is termed quantum bits or “qubits” rather than traditional bits. These qubits can coexist in the states of 0 and 1 at the same time.

As mentioned earlier, two bits may only simultaneously hold one of four possible combinations. However, a single pair of qubits is capable of storing all four at the same time. And the number of possible options grows exponentially with each additional qubit.

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As a consequence, quantum computers can carry out many computations while simultaneously considering several different configurations. For example, consider the 54-qubit Sycamore processor that Google developed. It was able to complete a computation in 200 seconds that would have taken the most powerful supercomputer in the world 10,000 years to complete.

In simple terms, quantum computers are much faster than traditional computers since they use qubits to perform multiple calculations simultaneously. In addition, since qubits can have a value of 0, 1 or both, they are much more efficient than the binary bits system used by current computers.

Different types of quantum computing attacks

So-called storage attacks involve a malicious party attempting to steal cash by focusing on susceptible blockchain addresses, such as those where the wallet’s public key is visible on a public ledger.

Four million Bitcoin (BTC), or 25% of all BTC, are vulnerable to an attack by a quantum computer due to owners using un-hashed public keys or re-using BTC addresses. The quantum computer would have to be powerful enough to decipher the private key from the un-hashed public address. If the private key is successfully deciphered, the malicious actor can steal a user’s funds straight from their wallets.

However, experts anticipate that the computing power required to carry out these attacks would be millions of times more than the current quantum computers, which have less than 100 qubits. Nevertheless, researchers in the field of quantum computing have hypothesized that the number of qubits in use might reach 10 million during the next ten years.

In order to protect themselves against these attacks, crypto users need to avoid re-using addresses or moving their funds into addresses where the public key has not been published. This sounds good in theory, but it can prove to be too tedious for everyday users.

Someone with access to a powerful quantum computer might attempt to steal money from a blockchain transaction in transit by launching a transit attack. Because it applies to all transactions, the scope of this attack is far broader. However, carrying it out is more challenging because the attacker must complete it before the miners can execute the transaction.

Under most circumstances, an attacker has no more than a few minutes due to the confirmation time on networks like Bitcoin and Ethereum. Hackers also need billions of qubits to carry out such an attack, making the risk of a transit attack much lower than a storage attack. Nonetheless, it is still something that users should take into mind.

Protecting against assaults while in transit is not an easy task. To do this, it is necessary to switch the underlying cryptographic signature algorithm of the blockchain to one that is resistant to a quantum attack.

Measures to protect against quantum computing

There is still a significant amount of work to be done with quantum computing before it can be considered a credible threat to blockchain technology.

In addition, blockchain technology will most likely evolve to tackle the issue of quantum security by the time quantum computers are widely available. There are already cryptocurrencies like IOTA that use directed acyclic graph (DAG) technology that is considered quantum resistant. In contrast to the blocks that make up a blockchain, directed acyclic graphs are made up of nodes and connections between them. Thus, the records of crypto transactions take the form of nodes. Then, the records of these exchanges are stacked one on top of the other.

Block lattice is another DAG-based technology that is quantum resistant. Blockchain networks like QAN Platform use the technology to enable developers to build quantum-resistant smart contracts, decentralized applications and digital assets. Lattice cryptography is resistant to quantum computers because it is based on a problem that a quantum computer might not be able to solve easily. The name given to this problem is the Shortest Vector Problem (SVP). Mathematically, the SVP is a question about finding the shortest vector in a high-dimensional lattice.

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It is thought that the SVP is difficult for quantum computers to solve due to the nature of quantum computing. Only when the states of the qubits are fully aligned can the superposition principle be used by a quantum computer. The quantum computer can use the superposition principle when the states of the qubits are perfectly aligned. Still, it must resort to more conventional methods of computation when the states are not. As a result, a quantum computer is very unlikely to succeed in solving the SVP. That’s why lattice-based encryption is secure against quantum computers.

Even traditional organizations have taken steps toward quantum security. JPMorgan and Toshiba have teamed up to develop quantum key distribution (QKD), a solution they claim to be quantum-resistant. With the use of quantum physics and cryptography, QKD makes it possible for two parties to trade confidential data while simultaneously being able to identify and foil any effort by a third party to eavesdrop on the transaction. The concept is being looked at as a potentially useful security mechanism against hypothetical blockchain attacks that quantum computers might carry out in the future.

BIS to launch market intelligence platform amid stablecoin, DeFi collapse

June 19, 2022 Coin Telegraph

BIS

BIS’s cryptocurrency market intelligence platform will be launched under the Eurosystem Centre initiative to provide vetted data about crypto projects.

The Bank for International Settlements (BIS) Innovation Hub announced the launch of a new set of projects targeting various aspects of traditional and crypto payments — including a cryptocurrency market intelligence platform and security for retail central bank digital currency (CBDC).

BIS’s cryptocurrency market intelligence platform will be launched under the Eurosystem Centre initiative, which aims to provide vetted data about crypto projects. One of the key drivers for the project’s commencement is the collapse of numerous stablecoins projects and decentralized finance (DeFi) lending platforms such as Terra (LUNA) and Decentralized USD (USDD). As explained in the official announcement:

“The project's goal is to create an open-source market intelligence platform to shed light on market capitalisations, economic activity, and risks to financial stability.”

The move goes against the norm of relying on self-reported information by unregulated firms when it comes to data on asset backing, trading volumes and market capitalization. The BIS also highlighted the ease with which quantum computers can break the cryptography used by traditional financial institutions to secure and settle payments. As a result, a Eurosystem Centre project will be dedicated to testing several cryptographic solutions and examining the overall performance of the traditional system.

Moreover, BIS’s Sela initiative will explore technological solutions for allowing CBDC issuance via intermediaries while ensuring greater security and lower costs. The BIS Innovation Hub’s Hong Kong Centre will also collaborate with the United Nations Framework Convention on Climate Change (UNFCCC) to develop the prototype for the second phase of its green finance project, Genesis:

“In this new phase, blockchain, smart contracts and other related technologies will be used for the tracking, delivery and transfer of so-called digitised Mitigation Outcome Interests - de facto carbon credits recognised under national verification mechanisms compliant with the Paris Agreement - attached to a bond.”

Cointelegraph recently attended the UNFCCC’s DigitalArt4Climate press conference to understand the various blockchain initiatives that actively fight climate change.

Ukraine joined Norway and Liechtenstein to become the third non-EU country to join the European Blockchain Partnership (EBP), an initiative derived by 27 member states to deliver cross-border public services.

Speaking to Cointelegraph, Konstantin Yarmolenko, the founder and CEO of Virtual Assets of Ukraine said:

“Next step is full blockchain integration of Ukraine and EU based on EBP/EBSI initiatives.”

Quantum-based random number generator for Web3 games and wallets launched

May 4, 2022 Coin Telegraph

Coin Telegraph

The QRNG uses a fluctuating quantum system to guarantee unpredictable randomness, which can be used in Web3 gaming and gambling.

Researchers at Australia National University have teamed up with blockchain oracle provider AP13 to launch the first Quantum Random Number Generator (QRNG).

The joint effort will allow Web3 entities to access a completely unpredictable random number generation system that is highly secure and free to use.

Random number generators are not new, but the QRNG system is the first of its kind to generate a random number using quantum mechanics. This provides the first genuinely random number mechanism beyond the pseudo-mathematical systems currently used that may be biased or repeated.

There are several traditional applications for random numbers, such as gambling and lotteries, sports and competitions, and sampling and statistics. As more organizations look to embrace the world of Web3, a tamper-proof, true random number generator not reliant on third parties will be required.

API3’s QRNG measures random quantum fluctuations in phase and amplitude of an electromagnetic field in a vacuum to guarantee unpredictable randomness and generate the numbers. Dr. Aaron Tranter from the ANU Research School of Physics explained the process to Cointelegraph:

“Quantum mechanics predicts that a vacuum, generally regarded as the absence of 'things', actually contains particles popping in and out of existence. This is the origin of the term vacuum noise. This noise is fundamentally random and can actually be measured using a laser, optics, and some fast electronics. We measure these fluctuations and convert them into random numbers which are then served to the AWS cloud for distribution via an API gateway.”

The system is currently available as an application programming interface (API) for 13 blockchains, including Ethereum, BNB Chain, Arbitrum, Avalanche, Optimism, Polygon, Fantom, and Moonbeam. Users need not pay for the service, but there will be a minor network fee for calling the API.

Web3 and Metaverse gaming could be one of the biggest beneficiaries of such a system as games continuously rely on a degree of randomness and unpredictability to keep players engaged.

Blockchain-based gambling applications would also greatly benefit from a tamper-proof random number generator, resulting in greater trust in the betting platforms.

Dr. Tranter added that people can use random numbers for whatever application they want, from the generation of unique NFTs and artwork to automated decision making. He explained:

“For example, if you wanted to draw randomly from a pool of clients for a task then you would want to ensure that you are truly sampling randomly. This could include distribution of resources, assigning of tasks and even decentralized quorums for voting.”

He added they could also be used for crypto wallet generation since the current solution of pseudo-random number generators can often result in repetition or have complex patterns that could be exploited. “A QRNG is guaranteed to be truly random by the laws of quantum mechanics, removing this loophole,” he added.

Web3 applications that involve public participation, such as random token distribution or drawn winners, will also benefit from a tamper-proof system.

API3 QRNG is hosted by the Australia National University Quantum Optics Group on Amazon Web Services (AWS), and all data passed between servers is encrypted. Additionally, the random numbers are destroyed after use, so the firm never has access to them.

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