A new chaotic complex map for robust video watermarking

Ayubi, Peyman; Barani, Milad Jafari; Valandar, Milad Yousefi; Irani, Behzad Yosefnezhad; Sadigh, Reza Sedagheh Maskan

doi:10.1007/s10462-020-09877-8

Cited by 57 publications

(18 citation statements)

References 74 publications

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“…Simulation tests and experimentation prove that the method has high performance and is highly efficient. A novel video watermarking scheme using a two-dimensional complex chaotic map is presented in [50]. The simulation results showed that the scheme has good visual quality using standard criteria.…”

Section: Related Workmentioning

confidence: 99%

A Provably Secure IBE Transformation Model for PKC Using Conformable Chebyshev Chaotic Maps under Human-Centered IoT Environments

Meshram¹,

Imoize

Aljaedi

et al. 2021

Sensors

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The place of public key cryptography (PKC) in guaranteeing the security of wireless networks under human-centered IoT environments cannot be overemphasized. PKC uses the idea of paired keys that are mathematically dependent but independent in practice. In PKC, each communicating party needs the public key and the authorized digital certificate of the other party to achieve encryption and decryption. In this circumstance, a directory is required to store the public keys of the participating parties. However, the design of such a directory can be cost-prohibitive and time-consuming. Recently, identity-based encryption (IBE) schemes have been introduced to address the vast limitations of PKC schemes. In a typical IBE system, a third-party server can distribute the public credentials to all parties involved in the system. Thus, the private key can be harvested from the arbitrary public key. As a result, the sender could use the public key of the receiver to encrypt the message, and the receiver could use the extracted private key to decrypt the message. In order to improve systems security, new IBE schemes are solely desired. However, the complexity and cost of designing an entirely new IBE technique remain. In order to address this problem, this paper presents a provably secure IBE transformation model for PKC using conformable Chebyshev chaotic maps under the human-centered IoT environment. In particular, we offer a robust and secure IBE transformation model and provide extensive performance analysis and security proofs of the model. Finally, we demonstrate the superiority of the proposed IBE transformation model over the existing IBE schemes. Overall, results indicate that the proposed scheme posed excellent security capabilities compared to the preliminary IBE-based schemes.

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Section: Related Workmentioning

confidence: 99%

A Provably Secure IBE Transformation Model for PKC Using Conformable Chebyshev Chaotic Maps under Human-Centered IoT Environments

Meshram¹,

Imoize

Aljaedi

et al. 2021

Sensors

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show abstract

“…e steps of the extraction module are illustrated in Figure 2. us, the process starts by normalizing the watermarked 3D object and then computing the DCT transform decomposition of (11) for j � 1 to length(Msg vector) do (12) [Coefficient 1 , Coefficient 2 , Coefficient 3 ] � DC T(Vertex x(j), Vertex y(j), Vertex z(j)) (12) Embed the Enc Msg value within the Coefficients values as the following equation system: the vertices. So, the encrypted grayscale image pixel can be extracted using the parameters β and the 3 D obj( 􏽢 C) coefficients according to the following equation:…”

Section: E Extraction Procedurementioning

confidence: 99%

“…In [38][39][40][41], the presented methods were based on embedding the QR code and binary bits into images based on various domains. Moreover, Ayubi et al in [12] presented a video watermarking method using 2D binary image. On the other hand, in [42,43], the proposed methods watermarked the 3D printed object, and in [18,[44][45][46], the presented methods were based on watermarking the 3D object using a different watermark sequence.…”

Section: Computational Intelligence and Neurosciencementioning

confidence: 99%

“…In modern times, watermarking techniques for a wide range of digital media were utilized as a host cover to hide or embed a piece of information message in such a way that it is imperceptible to a human observer. Usually, the digital media covers can take any form such as images [1][2][3][4][5][6][7], videos [8][9][10][11][12], audio [13][14][15], and DNA sequences [16,17]. Even so the 3D objects are widely available and important, there are a few existing watermarking techniques.…”

Section: Introductionmentioning

confidence: 99%

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A Blind Watermarking Model of the 3D Object and the Polygonal Mesh Objects for Securing Copyright

Al-Saadi

Ghareeb

Elhadad

2021

Computational Intelligence and Neuroscience

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In this paper, we propose a novel model for 3D object watermarking. The proposed method is based on the properties of the discrete cosine transform (DCT) of the 3D object vertices to embed a secret grayscale image three times. The watermarking process takes place by using the vertices coefficients and the encrypted image pixels. Moreover, the extraction process is totally blind based on the reverse steps of the embedding process to recover the secret grayscale image. Various performance aspects of the method are measured and compared between the original 3D object and the watermarked one using Euclidean distance, Manhattan distance, cosine distance, and correlation distance. The obtained results show that the proposed model provides better performances in terms of execution time and invisibility.

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“…Generally, such schemes are computationally complex [28] and unable to recover the lossless watermark image due to shiftvariant property [29]. Moreover, few schemes are based on linear wavelet transform (LWT) [17][18][19]. The LWT-based video-watermarking schemes are resistant to both image processing attacks and temporal video attacks such as impulse noise, Gaussian noise, filtering, compression attacks, but fails against geometric attacks [25][26][27][28]30].…”

Section: Introductionmentioning

confidence: 99%

Optimal keyframe selection-based lossless video-watermarking technique using IGSA in LWT domain for copyright protection

Singh

Mittal

Pal

2021

Complex Intell. Syst.

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Video piracy is a challenging issue in the modern world. Approximately $$90\%$$ 90 % of newly released films were illegally distributed around the world via the Internet. To overcome this issue, video watermarking is an effective process that integrates a logo in video frames as a watermark. Therefore, this paper presents an efficient lossless video-watermarking scheme based on optimal keyframe selection using an intelligent gravitational search algorithm in linear wavelet transform. This technique obtains color motion and motionless frames from the cover video by the histogram difference method. One-level linear wavelet transform is performed on the chrominance channel of motion frames and a low-frequency sub-band LL opts for watermark embedding. The performance of the proposed technique has been evaluated against 12 video processing attacks in terms of imperceptibility and robustness. Experiments demonstrate that the proposed technique outperforms five state-of-the-art schemes on the considered attacks.

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A new chaotic complex map for robust video watermarking

Cited by 57 publications

References 74 publications

A Provably Secure IBE Transformation Model for PKC Using Conformable Chebyshev Chaotic Maps under Human-Centered IoT Environments

A Provably Secure IBE Transformation Model for PKC Using Conformable Chebyshev Chaotic Maps under Human-Centered IoT Environments

A Blind Watermarking Model of the 3D Object and the Polygonal Mesh Objects for Securing Copyright

Optimal keyframe selection-based lossless video-watermarking technique using IGSA in LWT domain for copyright protection

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