## 6 Conclusions  
In this paper, we propose a collaborative secure localization algorithm based on the trust model for UWSNs. CSLT includes five sub-processes: trust evaluation of anchor nodes, initial localization of unknown nodes, trust evaluation of reference nodes, selection of reference node, and secondary localization of unknown node. Based on the trust model, the trust values of the one-hop anchor nodes and the two-hop reference nodes are calculated. Then, only trusty anchor nodes and references nodes are selected to localize unknown nodes to avoid impact from malicious nodes. Simulation results indicate that CSLT can achieve a high detect ratio of malicious nodes. In addition, the localization security including localization accuracy and localization ratio is improved in UWSNs. However, there are many remaining issues that need to be further studied for secure localization in UWSNs. First, we cannot find each type of malicious nodes with 100%. For example, some malicious nodes may not mostly cause packet error or loss in their own communication but the surrounding nodes'. Is this case, we just use the trust model to avoid the attacks from the malicious nodes. The influenced surrounding nodes are assigned with lower trust values, since their communication behaviors are heavily impacted by surrounding real malicious node. They are not chosen to localize to unknown node to avoid the influence from nearby malicious node. However, the real malicious nodes cannot be detected efficiently. In our simulation, the number of this kind of malicious node is relatively small. If most malicious nodes launch this kind of malicious attack, our trust model may not work very well. So we will further study new trust model to solve this problem in the future research. In addition, we use MATLAB to evaluate the performances of the proposed algorithm in order to easily compare our new algorithm with our previous work in [29]. To make our simulation results more reliable, we will further study the new platforms, e.g., NS, Aquasim, etc., for underwater environment. Last but not least, we assume that all the anchor nodes can accurately obtain their positions from GPS as some previous underwater localization algorithms did. While in real application, it is hard for the anchor nodes to accurately obtain their positions from GPS, and the position accuracy of anchor nodes is heavily influence localization accuracy of unknown nodes. Therefore, we will further to study the GPS accuracy impacts in our future work.  
This work was supported in part by the Qing Lan Project, in part by the National Science Foundation of China under Grant 61572172,and Grant 61401107, in part by the Natural Science Foundation of Jiangsu Province of China under Grant BK20131137,in part by the Open Fund through the Guangdong Provincial Key Laboratory of Petrochemical Equipment Fault Diagnosis under Grant PEFD2015-06, in part by the Educational Commission of Guangdong Province, China, under Project 2013 KJCX0131, in part by the Guangdong High-Tech Development Fund under Grant 2013B010401035, in part by the 2013 Special Fund of Guangdong Higher School Talent Recruitment, and part by the Instituto de Telecomunicacoes, Next Generation Networks and Applications Group (NetGNA), Covilha Delegation, Portugal and by National Funding from the FCT - Fundacao para a Ciencia e a Tecnologia through the UID/EEA/500008/2013 Project.  
[PERSON] researched the literatures, conceived the study concepts, designed the calibration method, carried out the simulation, analyzed the simulation results, and took charge of the entire manuscripts. [PERSON] and [PERSON] assisted with the integrity of the entire study, provided the crucial intellectual support, and revised the manuscript. [PERSON] contributed to the manuscript preparation and drafted the paper. [PERSON] contributed to modify and polish the revised manuscript.  
The authors declare no conflict of interest.