Reversible Information Hiding Algorithm Based On Compression Coding

With the rapid development of Internet 5g technology and cloud computing technology,the network transmission rate is greatly improved,which is convenient for the dissemination of multimedia information.There are also security problems such as digital information being stolen,tampered and attacked in the network transmission process.Therefore,how to ensure the integrity and security of a large amount of information in the process of transmission,reversible information hiding technology and encryption technology provide important technical means for information protection,compression coding technology provides high-capacity embedded space for reversible information hiding technology.Reversible information hiding technology is to hide the privacy data in the carrier,which is invisible to the outside world;encryption technology is to convert personal privacy data into non readable ciphertext form,which can be decrypted into readable information only when you have a key.In order to improve the compression ratio,the compression coding technology eliminates the duplication.Based on the advantages of the three technologies,this paper proposes a reversible information hiding algorithm of compression coding.(1)This paper first introduces the principle of information hiding and its performance evaluation index.In order to expand the reversible information hiding algorithm based on gray image compression coding,this paper introduces the common encryption algorithm,compression coding technology and reversible information hiding theory and technology in detail.(2)In order to solve the problems of image concealment,embedding rate and fidelity of reversible information hiding algorithm,the Logistic chaotic mapping matrix and the carrier image XOR operation are used to generate ciphertext image,and then the ciphertext image is processed by blocks.The improved quadratic prediction error is used in each block.The symbol bit sequence of the first compressed pixel value is recorded and the absolute value is taken,and the quadratic prediction difference is within the threshold The blocks within the value range are marked and compressed,and the space left by quadratic prediction error compression coding is used to embed auxiliary information and secret information.The results indicate that the improved algorithm improves the embedding capacity and ensures the information concealment,security and the integrity of the carrier image.(3)In the above improved algorithm,the block size and threshold range limit the selectivity,and only the information is embedded in the filter block.To solve this problem,in order to improve the embedding capacity of all blocks,the improved absolute matrix truncation coding compressed image is used as the carrier to compress the image after the block operation.The improved method quantizes the high mean and low mean of the image block into two levels,and forms five levels with the bitmap sequence table Then,every three sub vectors of high mean table,low mean table and bitmap sequence table of compressed carrier image are encrypted by Paillier homomorphism,and the ternary value of secret information is determined to be embedded in the encrypted sub vectors respectively.The sub vectors reconstruct the new high mean table,low mean table and bitmap sequence table to reconstruct the compressed image.The experimental results show that there is no overflow or underflow in the embedding process,and the improved algorithm greatly improves the hiding capacity,ensures that information is embedded in each block with high complexity.