Digital Image Authentication From JPEG Headers

203 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Digital image forgery detection using passive techniques: A survey (2013, methodology): “Kee et al. (2011) described a technique which extracts camera signature (9163 camera configurations) from a JPEG image consisting of information about quantization tables, Huffman codes, thumbnails, and EXIF format to determine if an image has been modified in any way.”
Media Forensics and DeepFakes: An Overview (2020, methodology): “A further approach is to exploit the model-specific implementations of the JPEG standard, including customized quantization tables and post-processing steps [80], [15].”
Photo forensics from JPEG dimples (2017, methodology): “…values used to quantize the discrete cosine transform (DCT) coefﬁcients are used to identify the recording camera manufacturer and model [2]–[4]; anomalies in the distribution of DCT coefﬁcients are used to reveal multiple JPEG compressions [5]–[7]; and artifacts introduced by the JPEG…”
Photo Forensics From Rounding Artifacts (2020, methodology): “…values used to quantize the discrete cosine transform (DCT) coeicients are used to identify the recording camera man-ufacturer and model [16, 22, 23]; anomalies in the distribution of DCT coeicients or the irst digit of DCT coeicients are used to reveal multiple JPEG compressions [2, 6, 7,…”