Integration of False Data Detection With Data Aggregation and Confidential Transmission in Wireless Sensor Networks

In wireless sensor networks, compromised sensor nodes can inject false data during both data aggregation and data forwarding. The existing false data detection techniques consider false data injections during data forwarding only and do not allow any change on the data by data aggregation. However, this paper presents a data aggregation and authentication protocol, called DAA, to integrate false data detection with data aggregation and confidentiality. To support data aggregation along with false data detection, the monitoring nodes of every data aggregator also conduct data aggregation and compute the corresponding small-size message authentication codes for data verification at their pairmates. To support confidential data transmission, the sensor nodes between two consecutive data aggregators verify the data integrity on the encrypted data rather than the plain data. Performance analysis shows that DAA detects any false data injected by up to T compromised nodes, and that the detected false data are not forwarded beyond the next data aggregator on the path. Despite that false data detection and data confidentiality increase the communication overhead, simulation results show that DAA can still reduce the amount of transmitted data by up to 60% with the help of data aggregation and early detection of false data.