Authenticating Lossy Surveillance Video

Ren, Y. J.; O’Gorman, Lawrence; Wu, Lili; Chang, Fangzhe; Wood, Thomas L.; Zhang, J. R.

doi:10.1109/tifs.2013.2279542

Cited by 8 publications

(4 citation statements)

References 28 publications

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“…A hash generation and signature based scheme is proposed to authenticate each set of videos in the streaming server [11]. In [12] a feature based fingerprint is first generated and then signed, in which security relies on the robustness of the fingerprint. It is necessary to further develop efficient stream level authentication schemes for H.264/AVC to achieve the goals of high authentication possibility and this provides low authentication overhead and high end-to-end quality.…”

Section: Related Workmentioning

confidence: 99%

Multifactor Authentication Scheme for Wireless H.264/AVC Video Streaming

Chandrasekar¹,

Manuprasad²

2016

IJCA

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Wireless communication channels are grown tremendously. Multimedia applications are using different wireless communication channels. Multimedia content verification and endorsement has become a rising issue for continuous video streaming. Especially this is a major issue over lossy/congested networks, which refers the network gives a lot of Timeout errors when packets are transmitted over it. Even though, several video coding standards are introduced to reduce the data size on the communication channel, the dependency of coding created new challenges and issues. Such video coding standards such as H.261, CCIR 723, MPEG-1 and MPEG-2 H.264/AVC has several challenges in inventing effective authentication scheme.In this proposal, we propose a multifactor authentication scheme that integrates authentication into source and channel coding components such as coderate, conventional length, which helps to efficiently address the coding reliance and to design the optimal rate allocation scheme for the sake of end-to-end video quality. The proposed multifactor authentication framework is able to authenticate the video streaming with low communication overhead. In general, the quality will get affected by the noise in wireless channel and unsuccessful authentication. We proposed a new channel, source and receiver authentication scheme named as VAP (Video Authenticity Protection). VAP provides continuous authentication with H.264 coding and channel rate allocation schemes. The experimental results on H.264/AVC video streaming confirm the effectiveness of this VAP and demonstrates that comparison with other video authentication schemes.

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Section: Related Workmentioning

confidence: 99%

Multifactor Authentication Scheme for Wireless H.264/AVC Video Streaming

Chandrasekar¹,

Manuprasad²

2016

IJCA

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“…Note that the proposed preprocessing is universal in the sense that it can be used together with virtually any robust feature extractor in existing video hashing methods. Next, we propose a new robust feature extractor called flow hashing (FH), which tries to blend the frame averaging operation in [4] with HOOF in [6]. Finally, we propose a fusion technique called distance boosting which aims to combine (fuse) the measure given by DTW-based preprocessing and Euclidean distance between FH hashes.…”

Section: Contributions Of This Papermentioning

confidence: 99%

“…Methods of this type extract hash vectors not directly from video frames, but from correlations between nearby frames. One representative method in this type is HOOF [5,6], where Histogram of Orientations of Optical Flow is used to extract hash vectors. Other advances include the use of multiple hash vectors to generate binary hash bits using spectral hashing [7,8].…”

Section: Introductionmentioning

confidence: 99%

Twofold video hashing with automatic synchronization

Monga

2014

2014 IEEE International Conference on Image Processing (ICIP)

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Video hashing finds a wide array of applications in content authentication, robust retrieval and anti-piracy search. While much of the existing research has focused on extracting robust and secure content descriptors, a significant open challenge still remains: Most existing video hashing methods are fallible to temporal desynchronization. That is, when the query video results by deleting or inserting some frames from the reference video, most existing methods assume the positions of the deleted (or inserted) frames are either perfectly known or reliably estimated. This assumption may be okay under typical transcoding and frame-rate changes but is highly inappropriate in adversarial scenarios such as anti-piracy video search. For example, an illegal uploader will try to bypass the 'piracy check' mechanism of YouTube/Dailymotion etc by performing a cleverly designed non-uniform resampling of the video. We present a new solution based on dynamic time warping (DTW), which can implement automatic synchronization and can be used together with existing video hashing methods. The second contribution of this paper is to propose a new robust feature extraction method called flow hashing (FH), based on frame averaging and optical flow descriptors. Finally, a fusion mechanism called distance boosting is proposed to combine the information extracted by DTW and FH. Experiments on real video collections show that such a hash extraction and comparison enables unprecedented robustness under both spatial and temporal attacks.

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“…To generate the authentication code, the authors adopted a vector quantization method to encode textured blocks and a scalar quantization method to encode uniform blocks for each frame. In [31], a combination of robust fingerprinting and cryptographic hashing has been adopted. The proposed video authentication system has been shown to withstand transcoding and transrating operations.…”

Section: Introductionmentioning

confidence: 99%

Perceptual Video Hashing for Content Identification and Authentication

Khelifi

Bouridane

2019

IEEE Trans. Circuits Syst. Video Technol.

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Abstract-Perceptual hashing has been broadly used in the literature to identify similar contents for video copy detection. It has also been adopted to detect malicious manipulations for video authentication. However, targeting both applications with a single system using the same hash would be highly desirable as this saves the storage space and reduces the computational complexity. This paper proposes a perceptual video hashing system for content identification and authentication. The objective is to design a hash extraction technique that can withstand signal processing operations on one hand and detect malicious attacks on the other hand. The proposed system relies on a new signal calibration technique for extracting the hash using the discrete cosine transform (DCT) and the discrete sine transform (DST). This consists of determining the number of samples, called the normalizing shift, that is required for shifting a digital signal so that the shifted version matches a certain pattern according to DCT/DST coefficients. The rationale for the calibration idea is that the normalizing shift resists signal processing operations while it exhibits sensitivity to local tampering (i.e., replacing a small portion of the signal with a different one). While the same hash serves both applications, two different similarity measures have been proposed for video identification and authentication, respectively. Through intensive experiments with various types of video distortions and manipulations, the proposed system has been shown to outperform related state-of-the art video hashing techniques in terms of identification and authentication with the advantageous ability to locate tampered regions.

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Authenticating Lossy Surveillance Video

Cited by 8 publications

References 28 publications

Multifactor Authentication Scheme for Wireless H.264/AVC Video Streaming

Multifactor Authentication Scheme for Wireless H.264/AVC Video Streaming

Twofold video hashing with automatic synchronization

Perceptual Video Hashing for Content Identification and Authentication

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