Design Of Drone-assisted Privacy Data Aggregation Schem

Wireless Sensor Networks(WSNs)have been widely applied in various fields.However,due to the deployment of sensor nodes in open or even hostile environments,data security is easily threatened by attackers through eavesdropping and tampering.Moreover,sensor nodes have limited resources,and nodes closer to the base station tend to deplete their energy earlier,resulting in network unavailability.Therefore,ensuring the security of WSNs and extending the network’s lifespan under resource constraints is a highly challenging problem.Security Data Aggregation(SDA)guarantees the security of WSNs with limited resources by providing high security and low data transmission overhead.Using Unmanned Aerial Vehicles(UAVs)for data collection can address the energy consumption issue caused by network topology,thus prolonging the network’s lifespan.This paper focuses on SDA from three aspects: data accuracy,data confidentiality,and UAV trajectory optimization.The proposed mechanisms are analyzed in terms of security,computational overhead,communication cost,and energy consumption performance.Firstly,the research focuses on a secure and privacy-preserving homomorphic data aggregation mechanism.In WSNs,if every sensor node participates in sensing tasks,it can result in a large amount of redundant data.Therefore,it is feasible to have only the most relevant sensors participate in the sensing tasks.This paper introduces an auction model into SDA,discussing the auction model for SDA.Compared to traditional auction models,this model utilizes homomorphic encryption algorithms to ensure data privacy while using message authentication codes to guarantee data integrity.The research also investigates incentive mechanisms where Cluster Heads(CHs)collect sensing data only from a subset of member nodes within the cluster,reducing communication overhead between nodes without compromising accuracy and integrity.Simulation results demonstrate that this mechanism ensures system effectiveness while maintaining accuracy constraints.This mechanism enhances the reliability and security of SDA while conserving node resources,making it applicable to a wider range of application scenarios.In addition,a secure clustering and data slicing scheme is proposed to further ensure the confidentiality and integrity of data transmission from sensor nodes to aggregation nodes,building upon the previous research content.This scheme incorporates an enhanced Stable Election Protocol(SEP)for the dynamic selection of Cluster Head(CH)nodes.The CH election process takes into account the current energy level of nodes,increasing the likelihood of selecting nodes with higher remaining energy as CHs,thus prolonging the network’s lifespan.During the data transmission process,the scheme involves data slicing and generating fake interference information to protect data confidentiality.Simulation and analysis demonstrate that this scheme performs well in terms of communication cost and privacy protection performance.By combining the improved SEP and data slicing techniques,this scheme enhances both the energy efficiency and security of the WSN,making it an effective solution for real-world applications.Finally,a UAV data acquisition model and UAV trajectory optimization method suitable for WSNs are proposed.Building upon the previous research,the model utilizes the solution to the Traveling Salesman Problem with Neighborhoods(TSNP)to determine the UAV’s visiting order between clusters.This ensures that the UAV can collect data from all CH nodes at a low cost.An approximation algorithm is proposed to solve the UAV’s intra-cluster flight trajectory.It optimizes the UAV’s hovering points to minimize flight time,achieving the research objective.The effectiveness of the algorithm is validated through simulation experiments simulating UAV data collection.By integrating the TSNP-based visiting order determination and the optimization of intra-cluster flight trajectory,this model enables efficient and effective UAV data collection in WSNs.The simulation results demonstrate the validity of the proposed algorithm in achieving the objective of minimizing flight time.