Research On Secure Data Aggregation In Wireless Sensor Networks

Wireless sensor network(WSN)is a low-cost,flexible and easy to deploy selforganizing network,which has a wide application prospect in the military and civilian fields such as target detection and event monitoring.Usually,WSN nodes are faced with the limitation of computing power and energy resources.Therefore,how to reduce transmission data redundancy,reduce node energy consumption and protect data security has become a hot issue in WSN research.Data aggregation is an important means of data processing in sensor network,which is collected by sensor nodes in the network and processed by upper-level aggregation nodes.At present,simple data aggregation algorithms such as data averaging have poor robustness when attacked by malicious nodes,and their data reliability cannot be guaranteed.Aiming at the problem of malicious attack in data aggregation,this thesis proposes the iterative data aggregation method under attack scenario and the weighted combined data aggregation method based on malicious node identification.The main achievements and contributions are as follows:1.Firstly,the traditional iterative filtering algorithm is introduced.By introducing the normalized reputation bias,the different properties of the iterative filtering method when using reciprocal discriminant function,exponential discriminant function and linear discriminant function are studied.Then the discriminant function is used to generate the weight and its implementation in data aggregation is given.Then,by introducing the collusion attack model,experimental data are used to verify the problem that the existing iterative filtering method is easy to converge to fake data in the attack scenario.2.In order to solve the problem of collusive data attacks in WSN,a robust security data aggregation method against collusive attacks is proposed.Firstly,based on the principle of sliding window outlier detection,the abnormal data of attack nodes were eliminated,and then the initial credibility of iteration was obtained by noise parameter estimation method and maximum likelihood estimation method.The numerical simulation results show that the proposed method improves the robustness of the algorithm against collusion attacks and the accuracy of the aggregation results by estimating the initial iteration reputation of the sensor nodes.3.In order to solve the problem of data aggregation when WSN nodes are captured by malicious users,a method of malicious node identification based on difference degree criterion is proposed.In the data aggregation stage,different from the traditional method to exclude all malicious nodes,the reliability weight of each node is allocated according to the influence of each node on the final aggregation to conduct data aggregation.Experimental results show that the proposed method can achieve better data aggregation performance compared with the method that completely excludes malicious nodes from the aggregation.