Cities are experiencing unprecedented growth and face significant challenges in creating healthy, sustainable and safe places for their citizens to live and work. Through a variety of devices equipped with sensors, meters and cameras, the Internet of Things (IoT) offers cities new new opportunities to use data for analytics based on Artificial Intelligence (AI) in areas such as traffic management, infrastructure, environmental monitoring and security. Collecting and processing vast amounts of data from and about citizens is a prerequisite for this, but it is also a source of serious privacy concerns.
The overarching goal of PROPOLIS is to address these privacy concerns throughout the AI lifecycle and to develop a comprehensive understanding of data privacy in context of smart city analytics. The project will provide privacy-friendly solutions for (i) the training phase, where an AI model is trained with the collected data, and for (ii) the subsequent inference phase, in which the trained models are used for future queries and inferences, and will be implement. The proposed project will consider a variety of potential adversaries and ensure the protection of the different data used, i.e., the protection of the training data (and thus the citizens who voluntarily provide it), the protection of the query, and finally the protection of the model. The solutions developed will advance the state of the art and rely on differential privacy, homomorphic encryption and secure multi-party computations.
The PROPOLIS consortium consists of two partners (one academic, one industrial) from France and two partners (one academic, one industrial) from Germany. All partners will contribute their expertise to solve the various analytical and specific data protection problems. The academic partners will work with the industrial partners to design and develop the proposed privacy-compliant analytical modules. While KIT and the Urban Institute will focus on the AI training phase and investigate differentiated privacy protection mechanisms for citizens, EURECOM and SAP will address the inference phase (query and model data protection) and develop privacy-friendly inference solutions based on homomorphic encryption and/or secure multi-party computation. The main synergistic effect of this international collaboration is an end-to-end data protection approach for smart city applications, where both intellectual property and citizen privacy are protected. The primary goal of PROPOLIS is to realize the full potential of smart-city applications through the IoT for the benefit of society, the economy, and more broadly, the quality of life of citizens exploit.