The wormhole attack is a severe threat to wireless sensor networks. Most existing countermeasures for detecting and locating wormhole links either require extra hardware or are too complex for the inherently capability-constrained sensor nodes. Actually, wormhole links can enormously change the original sensor network topology. In this paper, we introduce the HCA4DW mechanism for detecting and locating wormholes in wireless sensor networks. It is based on the basic idea that the change of topology can be detected through neighborhood validation. We discover the maximum necessary hop count between the sensors in the same neighbor set for neighborhood validation. We describe the detail procedure of HCA4DW in this paper and test the performance of the HCA4DW mechanism rigorously through simulative experiments.

Cloud computing enables users with limited resources to accomplish complex computation. Meanwhile, the massive human body sensing data generated by Wireless Body Area Network (WBAN) can be stored in cloud servers. However, cloud storage of human body sensing data is challenged by some issues. Users need to ensure that cloud servers can return the results and that they are correct. To address this problem, based on the argument system of commitment scheme, this paper designs a DMP verification algorithm. By compiling the hash of the header node into a constraint set and verifying the accuracy of the data of the intermediate node through a hash list, the algorithm reduces the compiling time of the intermediate node and improves the verification efficiency.

This paper presents an efficient approach for top-k query processing in wireless sensor networks (WSN) called FaVN-K. Our approach is similar to the FILA proposed by Wu et al. in that each sensor node is assigned with a value range called filter. What is different is that in FaVN-K virtual node is introduced to solve the problem of overlapping ranges. FaVN-K can achieve exact top-k result if all the nodes follow the filtering rules strictly. The experimental results show that FaVN-K can reduce transmission volume dramatically, which is especially important to WSN

Cloud computing enables users with limited resources to accomplish complex computation. Meanwhile, the massive human body sensing data generated by Wireless Body Area Network (WBAN) can be stored in cloud servers. However, cloud storage of human body sensing data is challenged by some issues. How can users ensure that cloud servers can return computing results and at the same time confirm that the results returned are correct? To address this problem, based on the argument system of commitment scheme, this paper designs a DMP verification algorithm. By compiling the hash of the header node into a constraint set and verifying the accuracy of the data of the intermediate node through a hash list, the algorithm reduces the compiling time of the intermediate node and improves the verification efficiency.