  In the modern digital world, a user of a smart system remains surrounded with
as well as observed by a number of tiny IoT devices round the clock almost
everywhere. Unfortunately, the ability of these devices to sense and share
various physical parameters, although play a key role in these smart systems
but also causes the threat of breach of the privacy of the users. Existing
solutions for privacy-preserving computation for decentralized systems either
use too complex cryptographic techniques or exploit an extremely high degree of
message passing and hence, are not suitable for the resource-constrained IoT
devices that constitute a significant fraction of a smart system. In this work,
we propose a novel lightweight strategy LiPI for Privacy-Preserving Data
Aggregation in low-power IoT systems. The design of the strategy is based on
decentralized and collaborative data obfuscation and does not exploit any
dependency on any trusted third party. In addition, besides minimizing the
communication requirements, we make appropriate use of the recent advances in
Synchronous-Transmission (ST)-based protocols in our design to accomplish the
goal efficiently. Extensive evaluation based on comprehensive experiments in
both simulation platforms and publicly available WSN/IoT testbeds demonstrates
that our strategy works up to at least 51.7% faster and consumes 50.5% lesser
energy compared to the existing state-of-the-art strategies.
