A secure and collaborative data aggregation scheme for fine-grained data distribution and management in Internet of Things

One of the greatest threats to the Internet of Things (IoT) is the increase in the number of IoT devices, leading to an exponential increase in the traffics on the communication networks. Asides this, the recent rise in ransomware, which is becoming better at evading detection, is posing security and privacy threats on IoT. With these, there is a need for effective security and aggregation solutions capable of securing data, protecting privacy, and minimizing traffic on the networks. Most of the existing security approaches are network and application-centric and not effective for IoT due to the heterogeneity and resource constraints of its devices. To address these, we propose a security and aggregation solution, which not only reduces the traffic on the communication network but also enforces integrity and confidentiality on IoT. Our scheme is capable of securing, aggregating, and separating heterogeneous IoT devices' data. Besides, the scheme can detect and filter injected false data during in and out-of-network data access through the location-based parametric-attribute. Security and performance analysis show that our proposed scheme is secure and efficient.