Research On Electronic Voting Scheme Based On Negative Surveys

Electronic voting is one of the common social activities today,it is faster and more efficient than voting scheme by paper.But the security of the electronic voting system is also particularly prominent.It is one of the key issues in the field of electronic voting to protect the privacy of voters while ensuring the correctness of voting results.Most traditional electronic voting schemes are based on cryptography to protect the privacy of voters,and most of these methods rely on a trusted third party.The management and negotiation of the key requires a certain price,and it has a risk of leakage.On the other hand,electronic voting schemes that do not rely on trusted third parties are mostly based on block chain technology,which usually has a higher computational cost.Negative survey is a method used to collect sensitive information,the participants are asked to choose an option which is not meet their wishes(negative option).The overall distribution of the original data can be reconstructed through the corresponding reconstruction algorithm,and negative survey has a good application prospect in the field of privacy protection.The application of negative survey to electronic voting can ensure that the data submitted by participants have been protected for privacy.This scheme does not require keys and trusted third parties,and it is simple and efficient to implement.Therefore,this thesis proposes a scheme based on negative survey to vote.The main work of this thesis is as follows:(1)This thesis gives the electronic voting model based on uniform negative survey and the confidence calculation method of the voting results based on this model.In this model,the voters select a positive option(the candidate that meets their own intention)on the local client.Then the local client selects a negative option with the same probability,and it is treated as the voting result and submitted to the server.At last the local client deletes the positive options.The server counts the voting results of all voters and applies the corresponding reconstruction algorithm to obtain the estimated value of the actual voting results.Based on the voting model,this thesis gives:1)The confidence calculation method for the estimated value of the voting result.2)The confidence calculation method for the estimated value of the voting result when a confidence domain is given.3)The calculation method of confidence domain of voting results under given confidence.By simulating the process of electronic voting based on uniform negative survey,this thesis preliminary analyzes the feasibility of applying negative survey to the field of electronic voting.(2)In order to improve the accuracy of the negative survey model applied to electronic voting,this thesis proposes a grouped negative survey model and apply it to electronic voting.In the grouped negative survey model,it is assumed that the number of participants in the survey is N,the number of candidates is c.Then all participants will be divided into[N?(c-1)]groups,and the number of participants in each group will not exceedc-1.Participants in the same group select negative options in order,and the options that have been selected cannot be selected again in the same group.In the electronic voting model based on grouped negative survey,voters vote according to the implementation rules of grouped negative survey.Experimental results show that the electronic voting model based on grouped negative survey has higher accuracy than the electronic voting model based on uniform negative survey?(3)This thesis proposes a reconstruction algorithm for the grouped negative survey model,named NStoPS-G algorithm.In the grouped negative survey model,the negative selection probability matrix of each voter is related to the negative option selected by the previous voter,so that the different voters have different negative selection matrices,and this feature cannot be fully utilized by existing negative survey reconstruction algorithms.Therefore,this paper proposes a reconstruction algorithm based on group negative survey.Firstly,calculating all negative selection matrices in the grouped negative survey model,then calculating the probability that each negative selection probability matrix is applied.Further,the negative selection matrix of the entire vote can be calculated.When the overall negative selection matrix is reversible,it is substituted into the NStoPS algorithm to reconstruct the voting results,otherwise it is substituted into the NStoPS-MLE algorithm to reconstruct the voting results.In this thesis,it is verified that applying NStoPS-G algorithm to reconstruct positive data can further improve the accuracy of voting results.This thesis uses 10 sets of real voting data to simulate the electronic voting based on the grouped negative survey model.The experimental results show that the voting accuracy of all data can reach more than 99.8%...