Image steganography for authenticity of visual contents in social networks

Muhammad, Khan; Ahmad, Jamil; Rho, Seungmin; Baik, Sung Wook

doi:10.1007/s11042-017-4420-8

Cited by 61 publications

(30 citation statements)

References 32 publications

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“…In recent years, a convolution neural network (CNN) has had excellent performance in image and video recognition, [22][23][24] recommender system, 25,26 and nature language processing. 27,28 Compared to the traditional machine learning methods, which learn the hand-crafted features, [29][30][31] CNN is independent from prior knowledge and human effort in feature design.…”

Section: Methodsmentioning

confidence: 99%

Cerebral micro‐bleeding identification based on a nine‐layer convolutional neural network with stochastic pooling

Wang

Sun

Mehmood

et al. 2019

Concurrency and Computation

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Cerebral micro-bleedings are small chronic brain hemorrhages caused by structural abnormalities of the small vessels. CMBs can be found from individuals with stroke at memory clinics and even healthy elderly people. CMBs indicate hemorrhage-prone pathological states. Research shows that CMBs are associated with an increased risk of future ischemic stroke, intra-cerebral hemorrhage (ICH), dementia, and death. Considering that CMBs severely influence people's life, it is necessary to identify the CMBs in an early stage to prevent from further deterioration and to help people live a healthy life. In this paper, we proposed using CNN with stochastic pooling for the CMB detection. CNN has good performance in image and video recognition, recommender system, and nature language processing. Based on the collected subject, the experiment result shows that the six-convolution layer and three fully-connected layer CNN, nine-layers in total, achieved sensitivity, specificity, accuracy, and precision as 97.22%, and 97.35%, 97.28%, and 97.35% in average of ten runs, which shows better performance than five state-of-the-art methods. KEYWORDScerebral micro-bleeding, convolution neural network, detection, intra-cerebral hemorrhage, stochastic pooling, stroke INTRODUCTIONCerebral micro-bleedings (CMBs) are small chronic brain hemorrhages, which can be caused by structural abnormalities of the small vessels. CMBs can be found from individuals with stroke and memory clinics that is initially set up for research purposes. 1 CMBs indicate hemorrhage-prone pathological states. Research shows that CMBs are associated with an increased risk of future ischemic stroke, intra-cerebral hemorrhage (ICH), dementia, and death. 2 Previous studies show that, in a range of 18% to 68%, patients with ischemic stroke/transient ischemic attack have a high prevalence of CMBs. There are 23% of prevalence in patients with first-ever ischemic stroke and 44% in patients with recurrent ischemic stroke reported by a previous systematic review. 3 The strong relationship with CMBs and increased risk of ICH suggests that the antithrombotic drugs Concurrency Computat Pract Exper. 2020;32:e5130. wileyonlinelibrary.com/journal/cpe to test the performance of the proposed structure of CNN based on the stochastic pooling, we compared different pooling methods, including average pooling, max pooling, and stochastic pooling. Meanwhile, we compared CNN with different convolution number and the state-of-the-art method for CMB detection. The experiment result shows that our designed structure of CNN based on the stochastic pooling achieved the best performance in sensitivity as 97.22%, specificity as 97.35%, accuracy as 97.28%, and precision as 97.35%.The limitation of our work is that we may need to move the window from top to bottom and from left to right. This is time-consuming. It is better to use concurrent convolution in the future studies, and we may need to replace the fully connected layers with conv layers. Another limitation is that we have two labels (CMB and ...

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Section: Methodsmentioning

confidence: 99%

Cerebral micro‐bleeding identification based on a nine‐layer convolutional neural network with stochastic pooling

Wang

Sun

Mehmood

et al. 2019

Concurrency and Computation

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“…The disadvantage of this method is that it requires multiple cloud service providers to resist collusion attack. For authenticity of visual substance utilizing TLE (Three-Level Encryption), MS (Morton Scanning) coordinated substitution of LSB (Least Significant Bit), color model transformation, and picture Steganography, a safe cryptographic system was introduced by Khan Muhammad et al [23]. The disadvantage is to make the stego image resilience against image processing attacks; the Steganography technique must be implement using transform domain.…”

Section: Related Work: a Brief Reviewmentioning

confidence: 99%

XOR Reformed Paillier Encryption Method with Secure De-duplication for Image Scaling and Cropping in Reduced Cloud Storage

Singh¹,

Baburaj²

2019

IJIES

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In this modern world, most of people are using cloud computing due to its accessibility. Users are uploading plenty of images to the cloud every day. But still, data confidentiality is the major issue for the cloud storage. This paper proposes a new method of image encryption scheme with less storage in the cloud. The proposed method performs double encryption with de-duplication over the images for better security and also reduces the storage overhead problem using the scaling and cropping operation. In the first level, the modified Paillier encryption technique is used and an XOR encryption takes place in the second phase. After that, a secure block-level image de-duplication technique is performed to eliminate the identical images and protect the image confidentiality. The simulation result exhibits that the proposed encryption with secure de-duplication outperforms other state-of-art approaches with respect to the performance metrics like accuracy, sensitivity, specificity, encryption quality and runtime. In terms of accuracy, the performance of proposed method is better of 8.

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“…Nowadays, the internet is the most used medium to access desired information. However, the internet misused activities or cybercrimes such as security breaches [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] are also increasing exponentially. In order to overcome these attacks, cryptography and steganography algorithms are used.…”

Section: Introductionmentioning

confidence: 99%

“…The table is show that the lightweight cipher consume minimum area for s-boxes as compared to other the conventional ciphers but increase the computation time for encryption due to the large number of rounds In steganography, choosing multimedia file for data embedding has played an important role. The multimedia files include text, protocol, audio, image, and the video [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18]. Various characteristics of these multimedia files have been used for data hiding as shown in Table 2.…”

Section: Introductionmentioning

confidence: 99%

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Lightweight and Optimized Multi-Layer Data Hiding using Video Steganography Paper

Kamil

Abdullah

Ahmad³

2018

ijacsa

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The ever-escalating attacks on the internet network are due to rapid technological growth. In order to surmount such challenges, multi-layer security algorithms were developed by hybridizing cryptography and steganography techniques. Consequently, the overall memory size became enormous while hybridizing these techniques. On the other side, the least significant bit (LSB) and modified LSB replacing approaches could provide the variability as detected by steganalysis technique, most found to be susceptible to attack too due to numerous reasons. To overcome these issues, in this paper a lightweight and optimized data hiding algorithm is proposed which consume less memory, provide less variability, and robust against histogram attacks. The proposed steganography system was achieved in two stages. First, data was encrypted using lightweight BORON cipher that only consumed less memory as compared to conventional algorithm such as 3DES, AES. Second, the encrypted data was hidden in the complemented or noncomplemented form to obtain minimal variability. The performance of the proposed technique was evaluated in terms of avalanche effect, visual quality, embedding capacity and peak signal to noise ratio (PSNR). The results revealed that the lightweight BORON cipher could produce approximate same avalanche effect as the AES algorithm produced. Furthermore, the value of PSNR had shown much improvement in comparison to optimization algorithm GA.

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Image steganography for authenticity of visual contents in social networks

Cited by 61 publications

References 32 publications

Cerebral micro‐bleeding identification based on a nine‐layer convolutional neural network with stochastic pooling

Cerebral micro‐bleeding identification based on a nine‐layer convolutional neural network with stochastic pooling

XOR Reformed Paillier Encryption Method with Secure De-duplication for Image Scaling and Cropping in Reduced Cloud Storage

Lightweight and Optimized Multi-Layer Data Hiding using Video Steganography Paper

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