With the rapid development and widespread use of wearable wireless sensors, data aggregation technique becomes one of the most important research areas. However, the sensitive data collected by sensor nodes may be leaked at the intermediate aggregator nodes. So, privacy preservation is becoming an increasingly important issue in security data aggregation. In this paper, we propose a security privacy-preserving data aggregation model, which adopts a mixed data aggregation structure. Data integrity is verified both at cluster head and at base station. Some nodes adopt slicing technology to avoid the leak of data at the cluster head in innercluster. Furthermore, a mechanism is given to locate the compromised nodes. The analysis shows that the model is robust to many attacks and has a lower communication overhead.
Zhang et al. proposed a security privacy-preserving data aggregation model, which adopts a mixed data aggregation structure of tree and cluster for the wearable wireless sensors in REF .
A secure privacy-preserving data aggregation model in wearable wireless sensor networks
J. Electrical and Computer Engineering
J. Electrical and Computer Engineering
Computer Science