Smart utility meters, such as the hydrometers that measure water consumption in homes, buildings and other facilities, have recently gained an innovative security feature: encryption keys reinforced by quantum computing. The solution, developed by Honeywell using Quantinuum's Quantum Origin technology, will help protect consumer data from cybersecurity threats and thus increase trust in utilities. According to Honeywell, meters with advanced security set a new standard in data breach protection and help ensure uninterrupted operations of water, electricity and gas utilities for residential and commercial applications. "By integrating Quantinuum's quantum computing-enhanced encryption technology into our smart meters, we're providing more security for our customers' data and helping to shape the dialogue on how utilities should approach cybersecurity in the quantum age," says Hamed Heyhat, president of Honeywell's Smart Thermal Energy Solutions business. "This integration emphasises how innovation enables our customers to stay ahead in the evolving threat landscape. It's a vitally important level of protection in our increasingly digital and interconnected world," he adds. Quantinuum's Quantum Origin technology offers an advantage over traditional solutions by generating encryption keys using the randomness provided by quantum computing, significantly raising data security levels for the end users of public utilities. Honeywell points out that no other company in the smart meter market offers enhanced protection through quantum cryptography. Integrating the technology into Honeywell's Smart Energy and Thermal Solutions products will help meet the growing demands for data security, especially in the case of critical infrastructures. "Robust cybersecurity requires a multi-faceted approach that exploits the capabilities of the latest technologies. Our work with Honeywell demonstrates the importance of using the power of today's quantum computers to create a more resilient cyber infrastructure that better protects our customers," emphasises Tony Uttley, president and chief operating officer of Quantinuum. Honeywell's Smart Energy and Thermal Solution products with Quantum Origin are now available to customers in North America and Europe. Risks to privacy and security Smart meters are seen as an essential component in the digitalisation of utility systems, such as the supply of water, electricity and water. However, the data that circulates between these meters still raises concerns about consumer privacy and security. These smart meters regularly capture data and transmit it to the utilities. However, if they suffer cyber attacks, they will fall into the hands of criminals who will be able, for example, to know the routine of the property and find the most favourable time to break in, calculating, for example, the number of people in the house or even whether they are sleeping. Consumption data can also be used to estimate a family's economic situation. In addition, smart meter data can be combined with other sources of information, such as social media and other smart devices. Great Britain is setting an example of the need to be careful about the privacy of data processed by smart meters. It is conducting a Smart Meter Implementation Programme (SMIP), seeking to modernise the national electricity and gas metering infrastructure. According to a report by Imperial College London, the programme has recognised that there is a significant risk to data privacy and has put in place various regulatory protections, which establish rights and choices for consumers in terms of how and who can access smart meter data. The Imperial College London study lists some privacy-preserving techniques that can help share data more widely while protecting consumers from possible violations. They are: 1. Data obfuscation to remove information that may be considered confidential. 2. Differential privacy, with cryptography that introduces noise into data sets to give mathematical guarantees of anonymity. 3. Homomorphic encryption that performs arithmetic operations on encrypted data. 4. User demand modelling that alters actual consumption patterns. 5. Distributed learning that ensures consumption data is kept locally on smart meters.