Research On Traffic Image Encryption Algorithm Based On Compressive Sensing

With the popularization,advancement and application of information and network technology,the information construction of transportation has been rapidly developed in our country.Intelligent Transportation System(ITS)can manage traffic systematically and share the different kinds of information via network.However,it is facing more and more severe challenges of information security.The following scenarios are possible,for example,the network is maliciously attacked,the computer virus is spread through an on-line service,and various types of traffic data are illegally copied,tampered,stolen and so on.Therefore,the information security problem in ITS has been an important issue that must be solved.This thesis focuses on the information security of traffic image,and exploits the encryption technique to protect the image data more effectively in the common transport channel.Combining the characteristics of traffic image and demands for encryption,compressive sensing(CS)is utilized to develop some secure,compressible,efficient and robust cryptosystems due to its advantages,such as high encryption efficiency,combined compression-encryption and robustness against noise attack and data loss.First,given the security flow of standard CS-based encryption scheme,CS framework is improved and combined with other classic cryptosystems to achieve superior security and better compression performance.On the other hand,considering that the traffic image with bulk information capacity is usually transmitted in a complexity environment,the running efficiency and robustness are equally remarkable performance indicators.Furthermore,a visually secure encryption algorithm is investigated to protect the privacy of traffic image more effectively.The main research work and contributions can be summarized as follows:(1)From the aspect of security,three image encryption models based on secret keys updating mechanism are presented to effectively resist the chosen plaintext attack(CPA).To achieve the balanced performance of compression,robustness and running efficiency,the related algorithms are analyzed,compared and summarized.The results provide the guidelines and technical routes for developing the image encryption algorithm.(2)A traffic image encryption algorithm based on parallel compressive sensing(PCS)is presented.To enhance the secrecy,SHA-256 hash function of the plain image is utilized to generate the secret keys,and hyper-chaotic Lorenz system is adopted to generate the secret code streams for the encryption algorithm.In the compression stage,permutation operation and threshold policy are employed to achieve better compression performance.In the re-encryption process,the forward and backward diffusion algorithms based on modular addtion are exploited to achieve better diffusion effect and preserve the robustness.The simulation results demonstrate that the proposed algorithm is more suitable for processing the traffic image,and it could achieve better compression performance and robustness under assurance of security.(3)To address the issue that PCS framework consumes much reconstruction time,especially for the medium and large images,a traffic image encryption algorithm based on nonuniform sampling in block compressive sensing(BCS)is designed.The plaintext-related permutation is employed in re-encryption process to resist CPA,and the control strategy is introduced to solve the problem that cryptosystem is not sensitive to the BCS key.Moreover,the nonuniform sampling strategy is introduced in the traditional BCS framework.Specifically,to improve the construction performance of low frequency component of traffic image,the different frequency components of image are classified and recombined,and then compressed as different tactics.The simulation results indicate that the compression performance,robustness and running efficiency could be effectively enhanced.(4)To generate a meaningful cipher image,an efficient visually secure traffic image encryption algorithm is developed by combining block compressive sensing and singular value decomposition(SVD)embedding.To assure the security,counter mode is adopted to update the secret keys.Besides,the compression performance is further enhanced under the BCS and coefficient random permutation(CRP)architecture.In the steganography stage,the modified SVD embedding is utilized to increase the embedding capacity,as well as effectively improve the robustness against the different types of noise and cropping attack.The simulation results and comprehensive analyses indicate the proposed algorithm could achieve the balanced performance of visual security,compression,robustness and running efficiency.The thesis provides a referential solution to encrypt the traffic image within limited bandwidth and storage space.Additionally,it promotes the privacy protection level of traffic image.