Smart cities offer a great opportunity for change. From upgrading outdated infrastructure to making our society more sustainable: the possibilities are virtually endless. The potential cost savings from implementing smart cities are also likely to have a huge positive impact: the figures are expected to reach $249 billion globally by 2028, up from $96 billion in 2023. When it comes to developing these smart cities, data plays a major role. important role. Data enables a smart city to optimize resources, improve the quality of life of its residents and create sustainable economic development. All this data needs to be processed and analyzed, often in real time – and this is where artificial intelligence (AI) comes into the picture.
Despite all the promise that AI and smart cities can bring, there is hesitation among the businesses and people living in these cities to adopt such technologies due to the potential for data breaches or poisoning. To address this, those building smart cities must work with security experts to ensure that watertight security defenses are built into the foundations from the start – only then will smart cities reach their full potential.
Product Manager at Canonical.
Creating smarter and safer streets
The benefits of smart cities are already being felt by citizens around the world. In Dublin, an AI system monitors CO2 emissions, weather and noise levels, ensuring cleaner air on the city's streets, and providing city planners with data they can use to plan new schools and homes. Elsewhere, in Finland, smart city technology is helping Helsinki reduce CO2 emissions associated with heating homes, with the aim of becoming carbon neutral by 2030.
Smart city technology doesn't just improve everyday life: it helps reshape the future of cities and ensures new developments can be planned around the way people actually live. City planners are informed by data analytics and AI from many sources, allowing city governments to better meet the real needs of their citizens.
As technology evolves, AI systems will become increasingly important. Smart cities will become 'cognitive cities', where AI systems identify problems and then act, without the need for a human to be involved. There is so much potential for the technology, but it needs rapid implementation and any issues need to be identified and resolved early. Open source approaches will be critical and help speed product development, encourage experimentation, and allow problems to be fixed before they become problems.
Putting safety first in AI-enhanced cities
Consumers are becoming increasingly cautious about how their data is captured and used to train the AI models that underpin smart cities, and whether their privacy is at risk. Once an AI model has ingested a data set and trained on it, there is no way to retrieve the data. There is also a risk that it will be resold to third parties, allowing citizens to be tracked without them realizing it. To ensure data privacy and the ethical use of AI models, effective regulation is necessary. Although there are no frameworks for this yet, several countries have started developing guidelines, such as the UK's pro-innovation approach. Finally, organizations can use secure environments to develop the models, with breakthrough capabilities such as confidential computing, strict confinement or data tokenization.
When it comes to the security of smart cities, there are complex hurdles to overcome. A smart city brings together a range of data sources and interconnected devices, creating a much larger attack surface for hackers to exploit. For example, in the transportation sector, self-driving cars, smart traffic lights, and sensors on roads all collect data that feeds into the same connected network. Through a breach, a hacker can create traffic jams, manipulate signals and even gain access to personal data.
The Department for Culture, Media and Sport (DCMS) has already established a code of practice for consumer-generated IoT products. The guidelines ensure that any company designing IoT products and endpoints builds products that provide “security by design.” While this is a good starting point, organizations leading these smart city projects must do more to address security threats, especially when integrating new technology with existing infrastructure.
The principle of least privilege, where each entity in a network is given the minimum system authorization and resources necessary to perform its function, is critical. This should be followed by implementing strict measures such as multi-factor authentication (MFA) for both local and remote accounts and devices. MFA helps strengthen the security of the underlying framework that facilitates access to networks and systems, especially when accessing highly sensitive data. Incorporating the principles of zero trust network design will also help achieve a higher level of network security and better visibility into network operations. This approach requires authentication and authorization for each new connection, using a multi-layered defense strategy. Finally, using AI to automatically update IoT networks will ensure that each device can monitor its own health and install security patches or new software from authorized, trusted developers.
Securing the AI-powered cities of tomorrow
The rise of smart cities promises a more connected and efficient urban future. However, this vision must be based on safety and trust. As cities add sensors and data-driven services, they also increase the attack surface for cyber threats and privacy violations. City planners must adopt a security and privacy-first mindset by prioritizing cybersecurity and data privacy from the start, allowing smart cities to become truly intelligent urban environments that improve lives.
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