Design Of Secure Data Aggregation Algorithm Based On Monitoring Mechanism In WSN

Wireless sensor networks technology is supposed to be one of the most influential technologies in21st century, and it has been widely applied to national defense, industry, transport and so many fields. It currently becomes the study hotspot, and the security issues have also received wide public concern. Compared with traditional network, wireless sensor networks have their own shortcomings and restrictions, such as energy limitation, computing and storage resource constraints, and communications range limitation, etc. These restrictions make the wireless sensor networks’security problems face more challenges.Data aggregation is a technology that can reduce energy consumption, eliminate redundant data and increase the accuracy of data. At the same time, as it has been restricted by some characters of wireless sensor networks, data aggregation faces many serious security problems, such as Denial of service attack, Replay attack and Sybil attack, etc. A great number of existing secure data aggregation technologies mainly use encryption mechanism to guarantee aggregation safety, but due to sensor nodes are easily to be captured and lead to internal attacks, using encryption mechanism alone already cannot completely guarantee the security of data aggregation.In order to solve the problem of internal attack, this thesis proposed a monitoring based secure wireless sensor networks data aggregation algorithm. Firstly, this thesis proposed a network model that fit for monitoring mechanism, and this model divided the sensor nodes into three types. Secondly, a monitoring mechanism was introduced to solve problems of data distortion, data discardment and so on, which were result from internal attack. Also a algorithm named "Fast detection-Slow recovery" was proposed contraposing the feature of on-off attack, in which different trust calculation schemes and different states of sensor node were used. These schemes were based on the behaviors which were listened by other nodes in the same grid, aiming at flexibly deal with secure data aggregation problems. Lastly, a network recovery method was designed when discovering malicious nodes and this thesis also proposed a way to elect new kinds of nodes and a method to recover grid tree. Simulation results demonstrated that the algorithm can effectively detect malicious nodes and guarantee the data aggregation proceeding based on the premise that energy consumptio is not so large.