LiPI: Lightweight Privacy-Preserving Data Aggregation in IoT

The ability of IoT devices to sense and share various physical parameters plays a key role in a smart system. Along side benefits, it also bears the potential to cause a breach of privacy for the users of the smart-systems. Existing solutions for privacy-preserving computation for distributed systems either extensively use highly complex cryptographic techniques or exploit an extremely high degree of message passing among the devices through secure channels. However, for the resource-constrained IoT devices, which compose a significant fraction of the smart-systems, the existing solutions for privacy-preserving computation strategies does not fulfill the current requirements. To address this issue, in this work, we propose a novel real-time lightweight strategy LiPI for Privacy-Preserving Data Aggregation in low-power IoT systems. LiPI uses lightweight distributed and collaborative data obfuscation, which substantially minimizes the computation requirements. In addition, it exploits the recent advances in Synchronous-Transmission (ST)-based protocols to efficiently fulfill the communication requirements too, making it efficient to work in real-time. Furthermore, LiPI also avoids dependency on any trusted third party. Extensive evaluation based on comprehensive experiments in both simulation platforms and publicly available WSN/IoT testbeds demonstrates that our strategy achieves the goal at least 51.7% faster and consumes 50.5% lesser energy compared to the existing state-of-the-art strategies.