  Preservation of privacy has been a serious concern with the increasing use of
IoT-assisted smart systems and their ubiquitous smart sensors. To solve the
issue, the smart systems are being trained to depend more on aggregated data
instead of directly using raw data. However, most of the existing strategies
for privacy-preserving data aggregation, either depend on computation-intensive
Homomorphic Encryption based operations or communication-intensive
collaborative mechanisms. Unfortunately, none of the approaches are directly
suitable for a resource-constrained IoT system. In this work, we leverage the
concurrent-transmission-based communication technology to efficiently realize a
Multi-Party Computation (MPC) based strategy, the well-known Shamir's Secret
Sharing (SSS), and optimize the same to make it suitable for real-world IoT
systems.
