Design And Implementation Of A Traitor Tracking System For Digital Teaching Resources

The rise of digital teaching resources has improved the dissemination and utilization efficiency of literature,and also brought about the problems of piracy,illegal reproduction and secondary distribution,which have become the primary problems affecting the use of digital teaching resources.In order to solve the above problems,this paper designs and develops a traitor tracking system for the copyright protection of digital teaching resources.The main work is as follows:First,a traitor tracking system of digital teaching resources is developed.This paper analyzes the functional requirements for the illegal duplication and secondary distribution of digital teaching resources.Through the analysis,the author designs the user's digital fingerprint generation and embedding,teaching picture management,user's digital fingerprint extraction and tracking,user information management,fingerprint management,consensus supervision and user authentication into the corresponding eight specific functional modules.The development of the system was based on the B/S architecture,and was carried out in Windows 7 64-bit environment.Based on python3.6 language Django framework and pycharm2019.1 tool,the main functions of the system are: user fingerprint generation and embedding,user fingerprint extraction,consensus monitoring and traitor tracking.At last,the system is tested.Secondly,a consensus monitoring mechanism of asymmetric tracking scheme is proposed.Through the authentication authorization and the user information privacy protection function,this mechanism realizes the distributor to supervise the trusted third party authority and the user information modification function.This function limits the joint attack between trusted third parties and users on the distributor and the distributor's behavior of falsely accusing users,thus protecting the legitimate rights and interests of the distributor and users.At the end of this paper,the trusted third party was tested to increase the permission of third party fingerprint modification.As a result,the distributor checked the permission interface and showed that Can change permission was added to the third party permission table.At the same time,the bottom 0of the user's fingerprint and the bottom 5 of the user's id information in the background database were changed to 1 and 7,respectively.More than half of the ciphertext characters after encryption could be observed in the distribution business,and the test results showed a good consensus monitoring effect.Finally,a traitor tracking algorithm based on digital fingerprint is proposed.The algorithm consists of three parts: digital fingerprint generation algorithm,improved LSB digital fingerprint embedding extraction algorithm and traitor tracking protocol.The algorithm of digital fingerprintgeneration is based on time stamp and last name.The improved LSB algorithm is used for digital fingerprint embedding and extraction.The idea is as follows: using the discrete b-channel pixel points in the picture as the carrier,the system automatically determines the position key according to the size of the picture and the number of pixels that meet certain conditions,and then inserts the fingerprint into the picture in a continuous way.All extraction algorithms are extracted at the lowest order.The traitor tracking protocol tracks the conspirators by comparing the extracted digital fingerprint with the calculated bit error rate and the set bit error rate threshold.In the end of this paper,relevant robustness and tracking tests were conducted.After cutting the original hidden pictures for 7 groups of different sizes,the bit error rate of fingerprint calculation and 3 groups of different screenshots were kept at 28% and 36% respectively,which proved that the system had good robustness.In the tracking experiment,4 users 2 conspirators,6users 3 conspirators and 8 users 4 conspirators were designed to engage in or attack.The experimental results show that all the conspirators can be tracked with the bit error rate threshold ranging from 7.23% to 10.84% under the premise of not falsely accusing innocent people,which has better tracking characteristics than previous schemes.