Video Inter-frame Forgery Detection: A Survey

Kingra, Staffy; Aggarwal, Naveen; Singh, Raahat Devender

doi:10.17485/ijst/2016/v9i44/105142

Cited by 11 publications

(6 citation statements)

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“…It refers to cropping and enlarging the outer portion of a video frame to remove an area or object that might represent any evidence of incriminating events [50], [51]. Figure 11 depicts an example of an upscale crop video tampering where Figure 11 (a) shows the original scene whilst Figure 11 (b) illustrates the fake video created in Figure 11 (a) where the walking lady has been removed.…”

Section: Upscale Crop Forgerymentioning

confidence: 99%

Video Forgery Detection for Surveillance Cameras: A Review

Tayfor,

Rashid,

Qader

et al. 2023

Preprint

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Although video recording is now a standard feature in smartphones and other digital devices, digital records are affordable and straightforward to take and distribute on social media. Furthermore, digital recordings have recently become an essential part of our daily lives, ranging from personal experiences to surveillance footage that may now be utilised as evidence of proof. Thus, it is essential to create detection algorithms for this kind of captured video because the number of high-standard counterfeit videos on social networks and other media is increasing exponentially. Evaluating the integrity of surveillance videos is crucial with the advanced equipment of surveillance systems. As a result, the rapid increase in surveillance cameras has made progress in physical security, including in building homes, stores, governmental buildings, agencies, etc. Moreover, surveillance videos have lately been extensively used as significant evidence in the courts. The evidence from the video can be crucial for a court of justice and investigators to comprehend the incidents as they happened. Unfortunately, due to the widespread of video editing programs, the video forgery/ tampering process has become incredibly simple. Consequently, the courts refuse to accept these videos as evidence because there is some margin of doubt about their authenticity and integrity. Therefore, to avoid such a situation in the future, more efforts are needed in video forensics. For this reason, this paper reviews primarily all the techniques and methods proposed so far to find out forgery in surveillance recordings and how the authenticity of such videos is proven.

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Section: Upscale Crop Forgerymentioning

confidence: 99%

Video Forgery Detection for Surveillance Cameras: A Review

Tayfor,

Rashid,

Qader

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…More recently, the advent of deep learning techniques has enhanced the capabilities of image integrity detection and verification, outperforming traditional methods in several image-related tasks, especially in these where anti-forensic tools were used [109], [110], [115]. In the context of video files, we can find surveys on video steganalysis [109], [110], [116], video forgery detection [91], [92], [94], [110], [117], [118], video forensic tools [91], [109], [119], [120], video surveillance analysis [121], [122], and video content authentication [123]. Finally, digital audio forensics has also been studied in [124].…”

Section: Challenge/limitation Referencesmentioning

confidence: 99%

“…Standardized evaluation procedures and benchmarks [90], [94]- [96], [98], [100], [101], [104], [109]- [114], [116], [117], [123] Explore the use of novel AI methods and novel data types [88], [91], [93], [95], [99], [100], [103], [104], [106], [107], [109], [110], [112], [113], [115], [118], [121]- [124] Robust pre-processing and feature extraction [90], [91], [94], [97], [99], [101], [102], [105], [106], [109], [115], [117], [118], [121], [123], [124] Reduce training and data acquisition overheads [89], [91]…”

Section: Challenge/limitation Referencesmentioning

confidence: 99%

Research Trends, Challenges, and Emerging Topics in Digital Forensics: A Review of Reviews

et al. 2022

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This work was supported by the European Commission under the Horizon 2020 Programme (H2020), as part of the projects LOCARD (https://locard.eu) (Grant Agreement no. 832735) and CyberSec4Europe (https://www.cybersec4europe.eu) (Grant Agreement no. 830929). F. Casino was supported by the Beatriu de Pinós programme of the Government of Catalonia (Grant No. 2020 BP 00035). The content of this article does not reflect the official opinion of the European Union. Responsibility for the information and views expressed therein lies entirely with the authors.

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“…A warning is made in [35], where authors state that multiple compressions were an under-explored topic and that it is risky to make assumptions regarding the authenticity of digital content simply on the basis of the presence of double compression. Their claim was supported by the simple fact that digital content available on the Internet generally undergoes more than one compression, even if video is only transmitted, uploaded, downloaded or watched.…”

Section: Recompression Detectionmentioning

confidence: 99%

Digital Video Manipulation Detection Technique Based on Compression Algorithms

Fernández

Orozco

Villalba

2022

IEEE Trans. Intell. Transport. Syst.

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Digital images and videos play a very important role in everyday life. Nowadays, people have access the affordable mobile devices equipped with advanced integrated cameras and powerful image processing applications. Technological development facilitates not only the generation of multimedia content, but also the intentional modification of it, either with recreational or malicious purposes. This is where forensic techniques to detect manipulation of images and videos become essential. This paper proposes a forensic technique by analysing compression algorithms used by the H.264 coding. The presence of recompression uses information of macroblocks, a characteristic of the H.264-MPEG4 standard, and motion vectors. A Vector Support Machine is used to create the model that allows to accurately detect if a video has been recompressed.

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Video Inter-frame Forgery Detection: A Survey

Cited by 11 publications

References 0 publications

Video Forgery Detection for Surveillance Cameras: A Review

Video Forgery Detection for Surveillance Cameras: A Review

Research Trends, Challenges, and Emerging Topics in Digital Forensics: A Review of Reviews

Digital Video Manipulation Detection Technique Based on Compression Algorithms

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