Research On Optimization Methods Of Traitor Tracing Based On Digital Fingerprint

With the rapid development of the Internet,consumers of digital products can frequently share data through the network,and there is a hidden danger that sensitive information may be illegally leaked by users.In recent years,the incidents of traitors leaking plaintext sensitive information in the digital product distribution system show a high-speed growth trendency,which brings a great challenge to copyright protection.How to accurately and efficiently track traitors in the digital product distribution system has become a research hotspot in academia.Under these circumstances of big data age,traditional traitor tracing algorithms can no longer meet the needs of accurately and efficiently tracing traitors,and most of the existing traitor tracing algorithms focus on resisting related-key attack rather than plaintext attack.Traitor Tracking Algorithm based on Digital Fingerprint can effectively resist plaintext attack.This paper aims to optimize Traitor Tracking Algorithm based on Digital Fingerprint from the two aspects of tracing accuracy and tracing efficiency by using the data sharing relationship in the user’s community network.The main work is as follows:Firstly,aiming at the problem of low tracing accuracy of traditional traitor tracing algorithms,this paper optimizes Traitor Tracing Algorithm based on Concatenated Code from the perspectives of improving the traceability accuracy and reducing the misjudgement rate,and proposes Traitor Tracing Algorithm based on Anti-Neighbor Collusion Digital Fingerprint(ANCDFT).In order to solve the problem of low traceability accuracy when using Traitor Tracing Algorithm based on Concatenated Code to locate digital fingerprints of different sub-blocks,ANCDFT improves Network Representation Learning Algorithm by introducing the influence probability of neighbor structure,then generates user-code by using the improved Network Representation Learning Algorithm,so that the user-code can more completely store the neighbor relationship of the user in the community network,then we can search the neighborhood collusion traitors in the community network according to user-code,so as to improve the traceability accuracy of the algorithm.In order to solve the problem of high misjudgement rate of Traitor Tracing Algorithm based on Concatenated Code,ANCDFT separates anti-neighbor collusion digital fingerprint into extension code and user-code during tracing phase,most traitors are identified in the initial tracing stage through the extension code,and then the user-code is used to verify the traitor and exclude innocent users in the secondary authentication stage,so as to reduce the misjudgment rate and make ANCDFT resistant to different types of collusion attacks.In addition,this paper also considers that users in the same community are more likely to collude,so the extension code is improved according to the number of community users,so that the anti-neighbor collusion digital fingerprint is easy to expand,and the digital fingerprint can be distributed to multiple communities with different numbers of users,so as to traitors can be searched in the whole community during tracing,thus resisting conspiracy attacks with neighboring users in the community,expanding the anti-collusion scene.Secondly,aiming at the low efficiency of traditional dynamic traitor tracing algorithm.This paper optimizes the traditional dynamic traitor tracing algorithm from the perspective of reducing the number of broadcast message frames and the number of copies of broadcast message frames,and proposes Dynamic Traitor Tracing Algorithm based on Group Digital Fingerprint(GDFDT).In order to quickly locate the user subset where the traitor is located,GDFDT designs the group digital fingerprint with high generation efficiency and high extraction efficiency by combining the random probability code with short length and the attribute information of user subset.The group digital fingerprint is used as a reliable basis for quickly locating the user subset where the traitor is located.In order to reduce the number of broadcast message frames and the number of copies of broadcast message frames,this paper improves the way of equally dividing subsets in the traditional dynamic traitor tracing algorithm,that is,by introducing the Online Boosting target tracing,that is,classifying the user subset of traitors into suspicious user subset and innocent user subset with different number of users,which can reduce the number of broadcast message frames and their copies,and reduce the resource consumption of broadcast encryption distribution system,so as to quickly locate traitors and better protect copyrights.Finally,this paper verifies that ANCDFT has high tracing accuracy through experiments,which can be traced to conspiratory traitors in the same community under different types of collusion attacks,without reducing the distortion of data and tracing efficiency,so that optimize the tracing accuracy of traditional traitor tracing algorithms.This paper verifies GDFDT has high tracing efficiency through experiments,which can be adapted to broadcast encryption distribution system with frequent data distribution and dynamic changes in user capacity.GDFDT achieves the effect of optimizing the tracing efficiency of traditional dynamic traitor tracing algorithms.In general,both ANCDFT and GDFDT have good usability,expansibility,and broad application prospects.