A novel quality assessment for visual secret sharing schemes

To evaluate the visual quality in visual secret sharing schemes, most of the existing metrics fail to generate fair and uniform quality scores for tested reconstructed images. We propose a new approach to measure the visual quality of the reconstructed image for visual secret sharing schemes. We developed an object detection method in the context of secret sharing, detecting outstanding local features and global object contour. The quality metric is constructed based on the object detection-weight map. The effectiveness of the proposed quality metric is demonstrated by a series of experiments. The experimental results show that our quality metric based on secret object detection outperforms existing metrics. Furthermore, it is straightforward to implement and can be applied to various applications such as performing the security test of the visual secret sharing process

AN EFFICIENT THRESHOLD SECRET SHARING SCHEME USING FAST FOURIER TRANSFORM

Secret Sharing is a robust key management method which is having applications in password management, secure multi party computation, e-voting etc. Threshold secret sharing is a method in which out of all the parties only predefined or certain number of parties can reconstruct the secret. In this paper we will describe the most popular Shamir’s secret sharing scheme along with its limitations. In Shamir’s scheme each shareholder receives one share per secret. We can use alternative way ramp (packed variant) scheme which overcomes this limitation and reduces load on each individual shareholder. But this impacts on efficiency as degree of polynomial is increased. Either we must adjust the privacy threshold or number of shares needed to reconstruct. There is need of advance technique. An efficient secret sharing needs faster polynomial evaluation and interpolation. Here is an efficient secret sharing scheme using Fast Fourier Transform (FFT). In this polynomial evaluation as well as interpolation both speeds up. It has time complexity O(n log n)

Chaotic Encryption and Privilege Based Visual Secret Sharing Model for Color Images

In the Privilege-based Visual Secret Sharing Model (PVSSM), each share has a unique privilege and a higher-privilege share contributes with more privilege to reveal the secret image. However, in PVSSM, when several shares with the higher priority are stacked, the secret image can be visibly displayed. This security problem is solved by applying a two-dimensional Logistic-Adjusted Sine Map (2D-LASM) to each share. This method is called Chaotic Encryption-based PVSSM. In this paper, we aim to present how Chaotic Encryption-based PVSSM is applied to color images. In order to assess the efficiency of this method, histogram analysis, data loss attack, salt-pepper noise attack, differential attack, chi-square analysis and correlation analysis tests were applied. The performance of this method has been evaluated according to NCPR, UACI, PSNR, SSIM and CQM. The proposed method achieved a good test values and showed better results compared to similar studies in literature

Unified Ciphertext-Policy weighted attribute-based encryption for sharing data in cloud computing

© 2018 by the authors. With the rapid development of cloud computing, it is playing an increasingly important role in data sharing. Meanwhile, attribute-based encryption (ABE) has been an effective way to share data securely in cloud computing. In real circumstances, there is often a mutual access sub-policy in different providers' access policies, and the significance of each attribute is usual diverse. In this paper, a secure and efficient data-sharing scheme in cloud computing, which is called unified ciphertext-policy weighted attribute-based encryption (UCP-WABE), is proposed. The weighted attribute authority assigns weights to attributes depending on their importance. The mutual information extractor extracts the mutual access sub-policy and generates the mutual information. Thus, UCP-WABE lowers the total encryption time cost of multiple providers. We prove that UCP-WABE is selectively secure on the basis of the security of ciphertext-policy weighted attribute-based encryption (CP-WABE). Additionally, the results of the implementation shows that UCP-WABE is efficient in terms of time

A Hybrid Approach to Privacy-Preserving Federated Learning

Federated learning facilitates the collaborative training of models without the sharing of raw data. However, recent attacks demonstrate that simply maintaining data locality during training processes does not provide sufficient privacy guarantees. Rather, we need a federated learning system capable of preventing inference over both the messages exchanged during training and the final trained model while ensuring the resulting model also has acceptable predictive accuracy. Existing federated learning approaches either use secure multiparty computation (SMC) which is vulnerable to inference or differential privacy which can lead to low accuracy given a large number of parties with relatively small amounts of data each. In this paper, we present an alternative approach that utilizes both differential privacy and SMC to balance these trade-offs. Combining differential privacy with secure multiparty computation enables us to reduce the growth of noise injection as the number of parties increases without sacrificing privacy while maintaining a pre-defined rate of trust. Our system is therefore a scalable approach that protects against inference threats and produces models with high accuracy. Additionally, our system can be used to train a variety of machine learning models, which we validate with experimental results on 3 different machine learning algorithms. Our experiments demonstrate that our approach out-performs state of the art solutions

SURVEY : CRYPTOGRAPHY OPTIMIZATION ALGORITHMS

With the advent of e-commerce, it has become extremely essential to tackle the sensitive issues of affording data security, especially in the ever-blooming open network environment of the modern era. The encrypting technologies of the time-honored cryptography are generally employed to shelter data safety extensively. The term ‘cryptography’ refers to the process of safeguarding the secret data against access by unscrupulous persons in scenarios where it is humanly impossible to furnish physical protection. It deals with the methods which convert the data between intelligible and unintelligible forms by encryption/decryption functions with the management of key(s). Nowadays cryptographic key management issues that arise due to the distributed nature of IT resources, as well the distributed nature of their control. Recently these issues are solved by optimization algorithms utilized in the cryptographic algorithms. The purpose of this paper is to give a survey of optimal cryptographic keys that can be developed with the help of optimization algorithms, and to address their merits to the real-worldscenarios.AbstractWith the advent of e-commerce, it has become extremely essential to tackle the sensitive issues of affording data security, especially in the ever-blooming open network environment of the modern era. The encrypting technologies of the time-honored cryptography are generally employed to shelter data safety extensively. The term ‘cryptography’ refers to the process of safeguarding the secret data against access by unscrupulous persons in scenarios where it is humanly impossible to furnish physical protection. It deals with the methods which convert the data between intelligible and unintelligible forms by encryption/decryption functions with the management of key(s). Nowadays cryptographic key management issues that arise due to the distributed nature of IT resources, as well the distributed nature of their control. Recently these issues are solved by optimization algorithms utilized in the cryptographic algorithms. The purpose of this paper is to give a survey of optimal cryptographic keys that can be developed with the help of optimization algorithms, and to address their merits to the real-worldscenarios. Keywords:Cryptography; Encryption; Decryption; Key Management; Optimization algorithm