Compression image sharing using DCT- Wavelet transform and coding by Blackely method

The increased use of computer and internet had been related to the wide use of multimedia information. The requirement forprotecting this information has risen dramatically. To prevent the confidential information from being tampered with, one needs toapply some cryptographic techniques. Most of cryptographic strategies have one similar weak point that is the information is centralized.To overcome this drawback the secret sharing was introduced. It’s a technique to distribute a secret among a group of members, suchthat every member owns a share of the secret; but only a particular combination of shares could reveal the secret. Individual sharesreveal nothing about the secret. The major challenge faces image secret sharing is the shadow size; that's the complete size of the lowestneeded of shares for revealing is greater than the original secret file. So the core of this work is to use different transform codingstrategies in order to get as much as possible the smallest share size. In this paper Compressive Sharing System for Images UsingTransform Coding and Blackely Method based on transform coding illustration are introduced. The introduced compressive secretsharing scheme using an appropriate transform (Discrete cosine transform and Wavelet) are applied to de-correlate the image samples,then feeding the output (i.e., compressed image data) to the diffusion scheme which is applied to remove any statistical redundancy orbits of important attribute that will exist within the compressed stream and in the last the (k, n) threshold secret sharing scheme, where nis the number of generated shares and k is the minimum needed shares for revealing. For making a certain high security level, eachproduced share is passed through stream ciphering depends on an individual encryption key belongs to the shareholder

Text image secret sharing with hiding based on color feature

The Secret Sharing is a scheme for sharing data into n pieces using (k, n) threshold method. Secret Sharing becomes an efficient method to ensure secure data transmission. Some visual cryptography techniques don’t guarantee security transmission because the secret information can be retrieved if the hackers obtain the number of shares. This study present a secret sharing method with hiding based on YCbCr color space. The proposed method is based on hiding the secret text file or image into a number of the cover image. The proposed method passes through three main steps: the first is to convert the secret text file or image and all cover images from RGB to YCbCr, the second step is to convert each color band to binary vector, then divide this band in the secret image into four-part, each part is appended with a binary vector of each cover image in variable locations, the third step is converting the color space from YCbCr to RGB color space and the generated shares, hidden with covers, are ready for transmission over the network. Even if the hackers get a piece of data or even all, they cannot retrieve the whole picture because they do not know where to hide the information. The results of the proposed scheme guarantee sending and receiving data of any length. The proposed method provides more security and reliability when compared with others. It hides an image of size (234x192) pixels with four covers. The MSE result is 3.12 and PSNR is 43.74. The proposed method shows good results, where the correlation between secret and retrieved images is strong ranging from (0.96 to 0.99). In the proposed method the reconstructed image quality is good, where original and reconstructed images Entropy are 7.224, 7.374 respectively

Visual secret sharing and related Works -A Review

The accelerated development of network technology and internet applications has increased the significance of protecting digital data and images from unauthorized access and manipulation. The secret image-sharing network (SIS) is a crucial technique used to protect private digital photos from illegal editing and copying. SIS can be classified into two types: single-secret sharing (SSS) and multi-secret sharing (MSS). In SSS, a single secret image is divided into multiple shares, while in MSS, multiple secret images are divided into multiple shares. Both SSS and MSS ensure that the original secret images cannot be reconstructed without the correct combination of shares. Therefore, several secret image-sharing methods have been developed depending on these two methods for example visual cryptography, steganography, discrete wavelet transform, watermarking, and threshold. All of these techniques are capable of randomly dividing the secret image into a large number of shares, each of which cannot provide any information to the intrusion team.  This study examined various visual secret-sharing schemes as unique examples of participant secret-sharing methods. Several structures that generalize and enhance VSS were also discussed in this study on covert image-sharing protocols and also this research also gives a comparative analysis of several methods based on various attributes in order to better concentrate on the future directions of the secret image. Generally speaking, the image quality generated employing developed methodologies is preferable to the image quality achieved through using the traditional visual secret-sharing methodology

Blockchain-based secure and efficient secret image sharing with outsourcing computation in wireless networks

Secret Image Sharing (SIS) is the technology that shares any given secret image by generating and distributing n shadow images in the way that any subset of k shadow images can restore the secret image. However, in the existing SIS schemes, the shadow images will be easily tampered and corrupted during the communication, which will pose serious security issues. Recently, blockchain has emerged as a promising paradigm in the field of data communication and information security. To securely communicate and effectively protect the secret image data in wireless networks, we propose a Blockchain-based Secure and Efficient Secret Image Sharing (BC-SESIS) scheme with outsourcing computation in wireless networks. In the proposed BC-SESIS scheme, the shadow images are encrypted and stored in the blockchain to prevent them from being tampered and corrupted. The identity authentication-enabled smart contract is deployed to achieve the ( k, n ) threshold for secret image restoring. Furthermore, to reduce the computational burden of smart contract and users, an efficient outsourcing computation method is designed to outsource the restoring task, which is securely implemented by agent miners in the encryption domain. Theoretical analysis and extensive experiments demonstrate that the BC-SESIS scheme can achieve desirable communication security and high computational efficiency in the wireless networks

Selected Papers from the First International Symposium on Future ICT (Future-ICT 2019) in Conjunction with 4th International Symposium on Mobile Internet Security (MobiSec 2019)

The International Symposium on Future ICT (Future-ICT 2019) in conjunction with the 4th International Symposium on Mobile Internet Security (MobiSec 2019) was held on 17–19 October 2019 in Taichung, Taiwan. The symposium provided academic and industry professionals an opportunity to discuss the latest issues and progress in advancing smart applications based on future ICT and its relative security. The symposium aimed to publish high-quality papers strictly related to the various theories and practical applications concerning advanced smart applications, future ICT, and related communications and networks. It was expected that the symposium and its publications would be a trigger for further related research and technology improvements in this field

Image steganography applications for secure communication

To securely communicate information between parties or locations is not an easy task considering the possible attacks or unintentional changes that can occur during communication. Encryption is often used to protect secret information from unauthorised access. Encryption, however, is not inconspicuous and the observable exchange of encrypted information between two parties can provide a potential attacker with information on the sender and receiver(s). The presence of encrypted information can also entice a potential attacker to launch an attack on the secure communication. This dissertation investigates and discusses the use of image steganography, a technology for hiding information in other information, to facilitate secure communication. Secure communication is divided into three categories: self-communication, one-to-one communication and one-to-many communication, depending on the number of receivers. In this dissertation, applications that make use of image steganography are implemented for each of the secure communication categories. For self-communication, image steganography is used to hide one-time passwords (OTPs) in images that are stored on a mobile device. For one-to-one communication, a decryptor program that forms part of an encryption protocol is embedded in an image using image steganography and for one-to-many communication, a secret message is divided into pieces and different pieces are embedded in different images. The image steganography applications for each of the secure communication categories are discussed along with the advantages and disadvantages that the applications have over more conventional secure communication technologies. An additional image steganography application is proposed that determines whether information is modified during communication. CopyrightDissertation (MSc)--University of Pretoria, 2012.Computer Scienceunrestricte

Is Vertical Logistic Regression Privacy-Preserving? A Comprehensive Privacy Analysis and Beyond

We consider vertical logistic regression (VLR) trained with mini-batch gradient descent -- a setting which has attracted growing interest among industries and proven to be useful in a wide range of applications including finance and medical research. We provide a comprehensive and rigorous privacy analysis of VLR in a class of open-source Federated Learning frameworks, where the protocols might differ between one another, yet a procedure of obtaining local gradients is implicitly shared. We first consider the honest-but-curious threat model, in which the detailed implementation of protocol is neglected and only the shared procedure is assumed, which we abstract as an oracle. We find that even under this general setting, single-dimension feature and label can still be recovered from the other party under suitable constraints of batch size, thus demonstrating the potential vulnerability of all frameworks following the same philosophy. Then we look into a popular instantiation of the protocol based on Homomorphic Encryption (HE). We propose an active attack that significantly weaken the constraints on batch size in the previous analysis via generating and compressing auxiliary ciphertext. To address the privacy leakage within the HE-based protocol, we develop a simple-yet-effective countermeasure based on Differential Privacy (DP), and provide both utility and privacy guarantees for the updated algorithm. Finally, we empirically verify the effectiveness of our attack and defense on benchmark datasets. Altogether, our findings suggest that all vertical federated learning frameworks that solely depend on HE might contain severe privacy risks, and DP, which has already demonstrated its power in horizontal federated learning, can also play a crucial role in the vertical setting, especially when coupled with HE or secure multi-party computation (MPC) techniques