Cryptography and cybersecurity
Encryption algorithms protect passwords used for transactions and secure communications. If not impossible today, it is relatively complex to solve the mathematical problems behind encryption based on keys that are relatively well dimensioned.
Nevertheless, these encryption methods will not resist the computational potential of future quantum computers, which represents a threat not to be neglected, and this in all the sectors that govern our lives today. Quantum cryptography will then be necessary to respond to this threat and to protect our data. While work is already underway in post-quantum cryptography, future developments to meet the challenges of cybersecurity are exponential.
We are developing algorithms dedicated to security applications based on cloud infrastructures (quantum simulation computers then quantum computers), allowing the delivery of quantum encryption solutions with a new approach to cybersecurity.
One of the problems currently facing artificial intelligence is the limited computational capacity of computers to execute complex algorithms. Thanks to its combinatorial power, the quantum computer should make it possible to reduce the so-called “learning” time and the processing time of applications while improving reasoning. Quantum computing is a potential technical answer to improving the security and processing speed of algorithms used by artificial intelligence systems. Future sectors are promising, such as connected objects, signal processing, or autonomous vehicles, which will require more and more complex intensive calculations.
We are developing algorithms dedicated to connected applications that will use cloud infrastructures (quantum simulation computers and then quantum computers) in the fields related to related objects, signal processing, and embedded systems.
The computing power of future quantum computers, while constituting a risk for financial data security, promises attractive development prospects in sectors related to the protection of exchanges, risk assessment, and fraud detection. Studies have shown that financial institutions lose between $10 and $40 billion in annual revenues due to fraud and poor data management practices. By offering the ability to perform massive and complex calculations, quantum computers open up new avenues for financial forecasting and understanding complex economic phenomena. In addition, quantum computers’ data modeling capabilities are superior to defining new models, performing classifications, and making predictions that are not feasible today.
We are developing algorithms dedicated to risk assessment and fraud detection applications based on cloud infrastructures (quantum simulation and quantum computers).