Detection of frame deletion in HEVC-Coded video in the compressed domain

Hong, Jin; Yang, Yoonmo; Oh, Byung Tae

doi:10.1016/j.diin.2019.06.002

Cited by 19 publications

(6 citation statements)

References 17 publications

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“…Lastly, the study in [30] proposed an algorithm for detecting frame deletion in HEVCcoded videos that were classified by machine learning classifiers. The research employed the passive alteration detection technique of multimedia forensic methods.…”

Section: Discussionmentioning

confidence: 99%

Realising a Push Button Modality for Video-Based Forensics

et al. 2021

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Complexity and sophistication among multimedia-based tools have made it easy for perpetrators to conduct digital crimes such as counterfeiting, modification, and alteration without being detected. It may not be easy to verify the integrity of video content that, for example, has been manipulated digitally. To address this perennial investigative challenge, this paper proposes the integration of a forensically sound push button forensic modality (PBFM) model for the investigation of the MP4 video file format as a step towards automated video forensic investigation. An open-source multimedia forensic tool was developed based on the proposed PBFM model. A comprehensive evaluation of the efficiency of the tool against file alteration showed that the tool was capable of identifying falsified files, which satisfied the underlying assertion of the PBFM model. Furthermore, the outcome can be used as a complementary process for enhancing the evidence admissibility of MP4 video for forensic investigation.

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Section: Discussionmentioning

confidence: 99%

Realising a Push Button Modality for Video-Based Forensics

et al. 2021

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“…Intra-frame tampering detection [2] Yes (HEVC only) Yes (Deletion only) No [3] Yes (MPEG-2, MPEG-4, H.264 only)…”

Section: Methods Dependency On File Type Inter-frame Tampering Detectionmentioning

confidence: 99%

“…If an attacker wants to modify a genuine video stored in compressed form, he should decode, edit and then recompress it. Frame deletion in HEVC (High Efficiency Video Coding) coded videos can be detected from the picture type changes [2]. Deletion of the frame results in change in type of frames.…”

Section: Introductionmentioning

confidence: 99%

Chained Digital Signature for the Improved Video Integrity Verification

Lawrence

Shreelekshmi

2021

Frontiers in Artificial Intelligence and Applications

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The recorded videos from the surveillance cameras can be used as potential evidence in forensic applications. These videos can be easily manipulated or tampered with video editing tools without leaving visible clues. Hence integrity verification is essential before using the videos as evidence. Existing methods mostly depend on the analysis of video data stream and video container for tampering detection. This paper discusses an active video integrity verification method using Elliptic Curve Cryptography and blockchain. The method uses Elliptic Curve Digital Signature Algorithm for calculating digital signature for video content and previous block. The digital signature of the encoded video segment (video content with predetermined size) and that of previous block are kept in each block to form an unbreakable chain. Our method does not consider any coding or compression artifacts of the video file and can be used on any video type and is tested on public-available standard videos with varying sizes and types. The proposed integrity verification scheme has better detection capabilities towards different types of alterations like insertion, copy-paste and deletion and can detect any type of forgery. This method is faster and more resistant to brute force and collision attacks in comparison to existing recent blockchain method.

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“…Their technique improved the detection of relocated I-P frames by 4.59% in comparison to the SNPUPM feature [26]. Hong et al [32] developed a method for detecting frame deletion forgeries in HEVC encoded videos. They extracted three coding features, namely, intra CU area, residual energy of transform unit and statistics of TUs from the P-frame of each GOP.…”

Section: Double Compression: Non-aligned Gopmentioning

confidence: 99%

A Review on HEVC Video Forensic Investigation under Compressed Domain

Singla¹,

Nagpal²,

Singh³

2022

IJIGSP

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In recent years, video forensic investigation has become a prominent research area, due to the adverse effect of fake videos on networks, people and society. This paper summarizes all the existing methodologies used for forgery detection in H.265/HEVC videos. HEVC video forgery is generally classified into two categories as video quality forgery and video content forgery. The occurrence of various forgeries such as transcoding, fake-bitrate, inter-frame forgery and intra-frame forgery is deeply analyzed based on features extracted from the HEVC compression domain. The major findings of this research are (i) Less focus on transcoding detection, (ii) Non-availability of HEVC forged video dataset (iii) More focus on double compression detection for forgery detection, and (iv) Non-consideration of adaptive-GOP structure. The forgery detection in the video is critically important due to its wide use as the primary source of information in criminal investigations and proving the authenticity of contents. So, the forgery detection accuracy is of major concern at the present time. Although, various forgery detection methods are developed in past but the findings of this review point out the need of developing more effective detection methods with high accuracy.

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Detection of frame deletion in HEVC-Coded video in the compressed domain

Cited by 19 publications

References 17 publications

Realising a Push Button Modality for Video-Based Forensics

Realising a Push Button Modality for Video-Based Forensics

Chained Digital Signature for the Improved Video Integrity Verification

A Review on HEVC Video Forensic Investigation under Compressed Domain

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