Journal of Geo-information Science ›› 2020, Vol. 22 ›› Issue (3): 379-388.doi: 10.12082/dqxxkx.2020.190336

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A Perceptual Hash Algorithm for DEM Data Authentication and Tamper Localization

ZHANG Xingang1,2,3, YAN Haowen1,2,3,*(), ZHANG Liming1,2,3   

  1. 1. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
    2. National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China
    3. Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China
  • Received:2019-06-26 Revised:2019-12-29 Online:2020-03-25 Published:2020-05-18
  • Contact: YAN Haowen
  • Supported by:
    National Natural Science Foundation of China(71563025);National Natural Science Foundation of China(41761080);Industrial Support and Guidance Projects of Colleges and Universities in Gansu Province(2019C-04);Funded by Lanzhou Jiaotong University Excellent Platform(201806)


As a type of fundamental and important geographic data, the integrity of DEM data cannot be ignored. The commonly used technology for data integrity authentication is mainly based on traditional cryptography and digital watermarking technology. The former is very sensitive to the change of every bit of data, suitable for accurate authentication of text data; while latter is mostly based on data carrier for authentication, seldom considers if DEM data content changes or not, and needs additional secure channels and communication media. In this paper, based on the requirement of authenticity and integrity of DEM data and the shortcomings of related authentication algorithms, a DEM data authentication algorithm was designed based on the Perceptual Hashing technology, which can achieve tamper localization. Perceptual hashing is a kind of method that maps multimedia data unidirectionally into perceptual summary sets (i.e. hash sequences). It inherits the characteristics of traditional Hash functions such as unidirectionality, anti-collision, and summarization, and is robust to the operation of content preservation, so it can better meet the requirements of DEM data authentication. The main ideas of this algorithm are as follows: Based on the characteristics of a large amount of DEM data and abundant details, the DEM data is divided into regular and non-overlapping grids. Feature extraction is the key of Perceptual Hashing algorithm. In this paper, the discrete cosine transform was used to extract features and generate the eigenvector matrix. Then the eigenvector matrix was digested. Next, the simplified eigenvector matrix was scrambled by using a Logistic chaotic system to meet the security requirements of authentication. Followingly, the scrambled matrix was quantized and coded to generate perceptual hash sequence. In the data authentication stage, the relative error of elevation between the original data and the data to be validated was calculated firstly. Subsequently, the perceptual hash sequence of the original data and the data to be validated was normalized to measure the Hamming distance. Combined with the determination threshold, the DEM data was authenticated. The scope of tampering would be located on the "grid unit" mentioned above. The algorithm has strong robustness against DEM data format conversion, watermarking embedding and other attacks. It is sensitive to various operations of changing contents, and can recognize and locate minor tampering of DEM data. Compared with the traditional DEM authentication algorithm, this algorithm innovatively regards "content" as the sole criterion of identity determination, which effectively compensates for the traditional digital watermarking method's excessive dependence on information carriers.

Key words: DEM, perceptual hash, grid partitioning, discrete cosine transform, data authentication, root mean square error of elevation