Robust Image Hashing With Ring Partition and Invariant Vector Distance

Tang, Zhenjun; Zhang, Xianquan; Li, Xianxian

doi:10.1109/tifs.2015.2485163

Cited by 206 publications

(112 citation statements)

References 32 publications

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“…On the other hand, the positions of zero values do not provide any visible information, compared to the features used in [10], [11], [14]- [16]. Besides, the proposed scheme can identify images under various coding conditions, although schemes which Moreover, several image-hashing schemes have been proposed for image retrieval [18]- [20]. However, they can not guarantee that there are not any false negative matches as shown later, although the proposed scheme guarantees it in principle.…”

Section: A Feature Extraction Processmentioning

confidence: 99%

“…So far, several identification schemes and image hash functions have been developed for compressed images [6]- [20]. They can be broadly classified into two types according to a difference in extracted features: compression method-depended type, to which the proposed scheme corresponds, and compression method-independent type.…”

Section: Introductionmentioning

confidence: 99%

“…They can be broadly classified into two types according to a difference in extracted features: compression method-depended type, to which the proposed scheme corresponds, and compression method-independent type. Image hashing-based schemes [18]- [20] which correspond to the latter one have the robustness against the lossy compres- sion, but it is not guaranteed that the identification is performed without any false negative matches. Moreover, they need to decompress images before carrying out the identification.…”

Section: Introductionmentioning

confidence: 99%

“…tamper detection. The proposed scheme allows not only to identify JPEG images under the use of different initial quantization matrices and quality factors but also to provide no visible information.So far, several identification schemes and image hash functions have been developed for compressed images [6]- [20]. They can be broadly classified into two types according to a difference in extracted features: compression method-depended type, to which the proposed scheme corresponds, and compression method-independent type.…”

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Robust Image Identification without Visible Information for JPEG Images

Iida

Kiya

2018

IEICE Trans. Inf. & Syst.

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Kenta IIDA† , Student Member and Hitoshi KIYA †a) , Fellow SUMMARY A robust identification scheme for JPEG images is proposed in this paper. The aim is to robustly identify JPEG images that are generated from the same original image, under various compression conditions such as differences in compression ratios and initial quantization matrices. The proposed scheme does not provide any false negative matches in principle. In addition, secure features, which do not have any visual information, are used to achieve not only a robust identification scheme but also secure one. Conventional schemes can not avoid providing false negative matches under some compression conditions, and are required to manage a secret key for secure identification. The proposed scheme is applicable to the uploading process of images on social networks like Twitter for image retrieval and forensics. A number of experiments are carried out to demonstrate that the effectiveness of the proposed method. The proposed method outperforms conventional ones in terms of query performances, while keeping a reasonable security level. key words: image identification, JPEG, social networks IntroductionThe growth of popularity of social networks(SNs) like twitter and Facebook have opened new perspectives in many research fields, including the emerging area of Multimedia Forensics. The huge amount of images have been uploaded on social networks, and generally stored in a compressed form as JPEG images, after being re-compressed with different compression parameters from those of uploaded im-This paper proposes a new robust identification scheme for JPEG images that are generated from the same original image, under various compression parameters, aiming at producing evidence on the integrity of images e.g. tamper detection. The proposed scheme allows not only to identify JPEG images under the use of different initial quantization matrices and quality factors but also to provide no visible information.So far, several identification schemes and image hash functions have been developed for compressed images [6]- [20]. They can be broadly classified into two types according to a difference in extracted features: compression method-depended type, to which the proposed scheme corresponds, and compression method-independent type. not only are robust against a difference in compressed ratios but also do not produce false negative matches in various compression ratios, due to the use of the positive and negative signs of DCT coefficients. However, they need to be combined with a security technique with a secret key such as the fuzzy commitment scheme [14]- [16], to securely protect the features which have some visible information. In addition, the security technique is not useful for the robust identification when various initial quantization matrices and quality factors are used.Due to such situations, this paper proposes a robust scheme for identifying images compressed under the various compression parameters. The strategy to robustly identify JPEG images is to ...

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Section: A Feature Extraction Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Robust Image Identification without Visible Information for JPEG Images

Iida

Kiya

2018

IEICE Trans. Inf. & Syst.

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“…So far, several identification schemes and image hash functions have been developed for authenticating images [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. They can be broadly classified into two types according to a difference in extracted features: compression method-depended type, to which the proposed scheme corresponds, and compression methodindependent type.…”

Section: Introductionmentioning

confidence: 99%

[Paper] Fuzzy Commitment Scheme-Based Secure Identification for JPEG XR Images under Various Compression Ratios

Iida

Kiya

2017

MTA

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A secure identification scheme for JPEG XR images is proposed in this paper.The aim is to securely identify JPEG XR images which are generated from the same original image under various compression levels. The positive and negative signs of lapped biorthogonal transform coefficients are used as features.The proposed scheme is robust against a difference in compression levels, and does not produce false negative matches in any compression level. In addition, to construct a secure identification system, we propose a novel identification system that consists of an error correction technique and a fuzzy commitment scheme, which is a well-known biometric cryptosystem. There is no existing scheme having these properties for JPEG XR images. Moreover, a way for speeding up the identification is also proposed. The experimental results show the proposed scheme is effective for identifying JPEG XR images in terms of true positive matches.

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A generalized detection framework for covert timing channels based on perceptual hashing

Zhuang,

Chen,

Tian

2024

Trans Emerging Tel Tech

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Network covert channels use network resources to transmit data covertly, and their existence will seriously threaten network security. Therefore, an effective method is needed to prevent and detect them. Current network covert timing channel detection methods often incorporate machine learning methods in order to achieve generalized detection, but they consume a large amount of computational resources. In this paper, we propose a generalized detection framework for covert channels based on perceptual hashing without relying on machine learning methods. And we propose a one‐dimensional data feature descriptor for feature extraction of perceptual hash for the data characteristics of covert timing channels. We first generate the hash sequence of the corresponding channel to get the average hash, which is used for comparison in the test phase. The experimental results show that the feature descriptor can capture the feature differences of one‐dimensional data well. When compared to machine learning methods, this perceptual hashing algorithms enable faster traffic detection. Meanwhile, our method is able to detect the effectiveness with the smallest coverage window compared with the latest solutions. Moreover, it exhibits robustness in jitter network environment.

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Robust Image Hashing With Ring Partition and Invariant Vector Distance

Cited by 206 publications

References 32 publications

Robust Image Identification without Visible Information for JPEG Images

Robust Image Identification without Visible Information for JPEG Images

[Paper] Fuzzy Commitment Scheme-Based Secure Identification for JPEG XR Images under Various Compression Ratios

A generalized detection framework for covert timing channels based on perceptual hashing

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