Description

In many sensor applications, the data collected from individual nodes is aggregated at a base station or host computer. To reduce energy consumption, many systems also perform in-network aggregation of sensor data at intermediate nodes enroute to the base station. Most existing aggregation algorithms and systems do not include any provisions for security, and consequently these systems are vulnerable to a wide variety of attacks. In particular, compromised nodes can be used to inject false data that leads to incorrect aggregates being computed at the base station. As the performance of very low power processors dramatically improves and their cost is drastically reduced, future aggregator no des will be capable of performing more sophisticated data aggregation algorithms, which will make WSN less vulnerable to severe impact of compromised no des. Iterative filtering algorithms hold great promise for such a purpose. Such algorithms simultaneously aggregate data from multiple sources and provide trust assessment of these sources, usually in a form of corresponding weight factors assigned to data provided by each source. In this project, the system proposes, an improvement for iterative filtering techniques by providing an initial approximation for such algorithm s which makes them not only collusion robust, but also more accurate and faster converging.