A secure true edge based 4 least significant bits steganography

Khan, Sahib; Ahmad, Nasir; Ismail, Muhmmad; Minallah, Nasru; Khan, Tawab

doi:10.1109/icet.2015.7389227

Cited by 17 publications

(7 citation statements)

References 15 publications

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“…This section compares the proposed data hiding technique with state-of-the-art data hiding methods. The comparison is made based on hiding capacity HC, peak signal to noise ratio PSNR, and structure similarity index SSI M. The proposed technique is compared with well-know data hiding techniques of Honsinger et al [9], Macq and Dewey [50], Fridrich et al [8], Lin and Li [51], Jaiswal et al [52], Goljan et al [53], Vleeschouwer et al [54], Khan et al [55], Alam et al [56], Wang et al [57], Khan and Tiziano [20], Khamrui and Mandal [58], Chang et al [28], Lee and Chen [59], Lin and Shiu [29], Koikara and Goswami [60], Hou et al [61], Wang et al [62], and Huang et al [63]. The comparison is made using three different cover images (Lena, Mandrill, and Pepper).…”

Section: Comparisonmentioning

confidence: 99%

A Modulo Function-Based Robust Asymmetric Variable Data Hiding Using DCT

Khan

Arif

et al. 2020

Symmetry

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This work presents a new asymmetric data hiding technique that hides a variable number of secret message bits in the discrete cosine transform (DCT) coefficients of a cover image using a modular distance technique. Prior to data hiding, the proposed framework transforms a cover image from a spatial domain to various frequency coefficients using DCT. The DCT coefficients are arranged in two groups: one with low-frequency coefficient, and the other with the medium and high-frequency coefficients. The medium and higher frequency coefficients are processed for variable data hiding asymmetrically. The proposed technique hides variable sets of secret information bits in different coefficients. The variation in hidden secret information is maintained using a key developed based on the modulo of distance of a coefficient from the reference point. The same key is also used to retrieve the confidential information at the receiver ends. The results reveal that the presented framework does not create any visually significant distortion, and thus the hidden information does not attract the human visual system (HVS). The technique also results in high data hiding efficiency.

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Section: Comparisonmentioning

confidence: 99%

A Modulo Function-Based Robust Asymmetric Variable Data Hiding Using DCT

Khan

Arif

et al. 2020

Symmetry

Self Cite

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“…The proposed technique is compared with well-known data hiding techniques of Honsinger et al [4], Macq and Dewey [35], Fridrich et al [3], Lin and Li [36], Jaiswal et al [37], Goljan et al [38], Vleeschouwer et al [39], Khan et al [16] and Khan and Tiziano [30]. The same cover images of Lena and Mandrill are used for experiments to make a comprehensive comparison.…”

Section: Comparisonmentioning

confidence: 99%

“…The hidden information creates no noticeable variation [14] and does not attract the human visual system (HVS) [15]. The HVS has some limitations, as reported in the literature [16]. The HVS is more sensitive to changes introduced in the smooth region of the cover image relative to the complex region.…”

Section: Introductionmentioning

confidence: 99%

ACO Based Variable Least Significant Bits Data Hiding in Edges Using IDIBS Algorithm

et al. 2020

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This work presents a double asymmetric data hiding technique. The first asymmetry is created by hiding secret data in the complex region of the cover image and keep the smooth region unaffected. Then another asymmetry is developed by hiding a different number of secret bits in the various pixels of the complex region. The proposed technique uses the ant colony optimization (ACO) based technique for the classification of complex and smooth region pixels. Then, the variable least significant bits (VLSB) data hiding framework is used to hide secret bits in the complex region of the cover image. A distance-based substitution technique, namely increasing distance increasing bits substitution algorithm, is used to ensure the asymmetry in the number of hidden bits. The double asymmetric framework enhances the security of the hidden secret data and makes the retrieval of hidden information difficult for unauthorized users. The algorithm results in high-quality stego images, and the hidden information does not attract the human visual system (HVS).

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“…It has become very challenging to detect the image modifications, which cannot be detected by naked eye. There are various powerful and extremely sophisticated software tools that can modify a digital image, not to attract the human visual system (HVS) (Khan et al, 2016;Khan et al, 2015). The modification can be of different types, e.g., pixel modification, bit modification, image enhancement, image rotation, and truncation.…”

Section: Introductionmentioning

confidence: 99%

CLIFD: A novel image forgery detection technique using digital signatures

Khan

Ali²

2021

JER is an international, peer-reviewed journal that publishes f

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The paper presents a new image forgery detection technique. The proposed technique uses digital signatures; it generates a digital signature for each column and embeds the signature in the least significant bits of each corresponding column’s selected pixels. The message digest algorithm 5 (MD5) is used for digital signature generation, and the fourleast-significant-bit substitution mechanism is used to embed the signature in the designated pixels. The embedding of the digital signature in the selected pixel remains completely innocent and undetectable for the human visual system. The proposed forgery detection technique has demonstrated significant results against different types of forgeries introduced to digital images and successfully detected and pointed out the forged columns.

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A secure true edge based 4 least significant bits steganography

Cited by 17 publications

References 15 publications

A Modulo Function-Based Robust Asymmetric Variable Data Hiding Using DCT

A Modulo Function-Based Robust Asymmetric Variable Data Hiding Using DCT

ACO Based Variable Least Significant Bits Data Hiding in Edges Using IDIBS Algorithm

CLIFD: A novel image forgery detection technique using digital signatures

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