Quantum related technologies have the potential to disrupt a number of key areas of IT over the next 5 years. Due to the mind-boggling principles of superposition and entanglement, a future quantum machine will have the power of parallelisation and could tackle some of the hardest computational tasks in a short period of time.
Quantum computers are not expected to become commercially ready until around 2025, but there is a lot that businesses should do to prepare for this next digital revolution. Having an awareness of the threats and opportunities can help businesses deploy quantum safe security right now.
For certain IT heavy industries like financial services, the impact of this radical technology is double edged. Future machines could supercharge profits for firms and could also open up wide-scale and systemic breaches of existing security and governance mechanisms. Such developments would be disastrous to the financial services market if they are not properly anticipated and managed. Hence much of fintech today is focused on quantum computing, which comes with both benefits and threats to financial services.
Financial services are one of the markets most dependent on IT because of a reliance on security and the need to deliver differentiated services. New ways of communicating and interacting with financial services digitally (e.g. online and mobile banking, peer-to-peer payment platforms and digital currencies), as well as the continuing improvements in computing power, have led to increased concerns over cybersecurity. It is an ongoing challenge for encryption methods to keep pace with the sophistication and processing power of technology that is capable of compromising the protection they offer.
Generally, quantum algorithms would require logarithmically fewer calculations than a classical computer to achieve the same result, and would therefore run at a much faster speed. One particularly interesting application for banking is algorithmic trading. This uses algorithms to automatically initiate stock trades according to pre-defined strategies. Becoming proficient in running these algorithms for high-frequency trading can offer a significant advantage over those without such a capability.
Pattern recognition algorithms can be effectively used to spot fraudulent activities and reduce data breaches. This is done via machine learning, whose goal is to accelerate the learning rate of artificial neural networks. Using classical techniques, and particularly in the complicated mathematical world of the banking sector, it is very difficult to train a neural network in big-data applications. Having fast learning neural networks thanks to quantum computers will provide levels of insight and understanding to help fight fraudulent activities which were previously inconceivable.
The basic algorithm for the public-key/private-key of blockchains is not quantum safe. This puts the development of crypto-currency markets at risk since currently their keys are sent via the internet. In theory, having acquired a quantum computer, it will be possible to take any number of public keys and rapidly de-crypt them to determine their private key counterparts. The first person to perform this feat could use such knowledge to execute the largest bank robbery in the history of mankind.
In a similar way, some algorithms which could be run with quantum computers can decrypt RSA keys (one of the most common cryptography technique) rendering them practically useless. In fact, there are many cryptography standards in use today that are not quantum safe. It is advisable for any institution to perform a quantum risk assessment to determine the risks associated with their current encryption infrastructure. It should be noted that if the outcome of such an assessment shows serious gaps in security, the institutions’ core business will be rendered extremely vulnerable with the advent of quantum computers.
Possible elements of a solution to these threats include the development of new encryption algorithms and methods that are resistant to attacks from quantum computers (“post-quantum cryptography”). Such solutions range from the use of encryption algorithms where increasing complexity drives an exponential increase in solution runtime even for quantum computers; through to the creation of all new encryption methods that would be problematic for a quantum computer.
Another technique with a lot of potential is quantum key distribution (QKD), which uses quantum technology as a defence to ensure privacy in data exchange. Quantum states are affected by the very act of measuring them, so it is relatively easy to detect if quantum keys have been intercepted and read by 3rd parties during the process of exchange.
“At the quantum level there’s what’s known as the Heisenberg Uncertainty Principal which means that as you intercept information it can be perturbed and detected. You can essentially see if someone is listening in. In practical terms what this means is that typically communications are done on optical fibres. Classical communication rely on bright pulses of light – millions of pulses of photons. And an adversary can intercept a few of these photons, get 100% of the information without perturbing the photons.”
Ultimately, the adoption of at least one of these techniques will be vital in coming years to anyone who wishes to transmit sensitive or confidential data securely. There are already QKD solutions available commercially, as well as post-quantum cryptography methods, and it is an active research area for many academic institutions and government organizations, including the NSA.
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Reference to source: MarketMogul