Penerapan Metode Localization Tampering dan Hashing untuk Deteksi Rekayasa Video Digital

Indonesia

  • Alfiansyah Imanda Putra Alfian Universitas Ahmad Dahlan
  • Rusydi Umar Universitas Ahmad Dahlan
  • Abdul Fadlil Universitas Ahman Dahlan
Keywords: Forensics, Video, Localization tampering, Manipulation.

Abstract

The development of digital video technology which is increasingly advanced makes digital video engineering crimes prone to occur. The change in digital video has changed information communication, and it is easy to use in digital crime. One way to solve this digital crime case is to use the NIST (National Institute of Standards and Technology) method for video forensics. The initial stage is carried out by collecting data and carrying out the process of extracting the collected results. A local hash and noise algorithm can then be used to analyze the resulting results, which will detect any digital video interference or manipulation at each video frame, and perform hash analysis to detect the authenticity of the video. In digital video engineering, histogram analysis can be performed by calculating the histogram value metric, which is used to compare the histogram values ​​of the original video and video noise and make graphical comparisons. The results of the difference in frame analysis show that the results of the video show that the 2nd to 7th frames experience an attack while the histogram calculation of the original video centroid value and video tampering results in different values ​​in the third frame, namely with a value of 124.318 and the 7th frame of the video experiencing a difference in the value of 105,966 videos. tampering and 107,456 in the original video. Hash analysis on video tampering results in an invalid SHA-1 hash, this can prove that the video has been manipulated.

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Published
2021-04-29
How to Cite
Alfian, A. I. P., Umar, R., & Fadlil, A. (2021). Penerapan Metode Localization Tampering dan Hashing untuk Deteksi Rekayasa Video Digital. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 5(2), 400 - 406. https://doi.org/10.29207/resti.v5i2.3015
Section
Artificial Intelligence