On Real-valued Visual Cryptographic Basis Matrices

Visual cryptography (VC) encodes an image into noise-like shares, which can be stacked to reveal a reduced quality version of the original. The problem with encrypting colour images is that they must undergo heavy pre-processing to reduce them to binary, entailing significant quality loss. This paper proposes VC that works directly on intermediate grayscale values per colour channel and demonstrates real-valued basis matrices for this purpose. The resulting stacked shares produce a clearer reconstruction than in binary VC, and to the best of the authors’ knowledge, is the first method posing no restrictions on colour values while maintaining the ability to decrypt with human vision. Grayscale and colour images of differing entropies are encrypted using fuzzy OR and XOR, and their PSNR and structural similarities are compared with binary VC to demonstrate improved quality. It is compared with previous research and its advantages highlighted, notably in high quality reconstructions with minimal processing

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

Cellular Automata Based Image Authentication Scheme Using Extended Visual Cryptography

Most of the Visual Cryptography based image authentication schemes hide the share and authentication data into cover images by using an additional data hiding process. This process increases the computational cost of the schemes. Pixel expansion, meaningless shares and use of codebook are other challenges in these schemes. To overcome these issues, an authentication scheme is proposed in which no embedding into the cover images is performed and meaningful authentication shares are created using the watermark and cover images. This makes the scheme completely imperceptible. The watermark can be retrieved just by superimposing these authentication shares, thus reducing the computational complexity at receiver's side. Cellular Automata is used to construct the master share that provides self-construction ability to the shares. The meaningful authentication shares help in enhancing the security of the scheme while size invariance saves transmission and storage cost. The scheme possesses the ability of tamper detection. Experimental results demonstrate the improved security and quality of the generated shares of the proposed scheme as compared to existing schemes

New Designs for Friendly Visual Cryptography Scheme

NSC101-2221-E-032-047[[abstract]]Different from conventional cryptography, visual cryptography is an image cryptographic technique proposed by Naor and Shamir. It encodes a secret image into n pieces of noise-like shares. When k or more than k pieces of shares are gathered from participants, human visual system will disclose the secret image on the stacked image easily. Neither complicated mathematical computation nor any knowledge of cryptography are needed are the main advantages of visual cryptography. In this paper, we propose a new design for friendly visual cryptography scheme. The secret will be hiding into two meaningful shares. The black-appearing ratio in each block of the shares for the corresponding black (rep. white) secret pixel is the same. Therefore, it is impossible for one to disclose any information related to the secret image on each share, which achieves the goal of improving security. When shares are superimposed, the contours of the cover image will disappear on the stacked image, which will only reveal the secret image. According to our experimental results, the contrasts of the shares or the stacked images are good which can reveal the contents of the cover images and the secret image clearly.[[notice]]補正完畢[[journaltype]]國外[[ispeerreviewed]]Y[[booktype]]紙本[[countrycodes]]SG

Coexistence of multiuser entanglement distribution and classical light in optical fiber network with a semiconductor chip

Building communication links among multiple users in a scalable and robust way is a key objective in achieving large-scale quantum networks. In realistic scenario, noise from the coexisting classical light is inevitable and can ultimately disrupt the entanglement. The previous significant fully connected multiuser entanglement distribution experiments are conducted using dark fiber links and there is no explicit relation between the entanglement degradations induced by classical noise and its error rate. Here we fabricate a semiconductor chip with a high figure-of-merit modal overlap to directly generate broadband polarization entanglement. Our monolithic source maintains polarization entanglement fidelity above 96% for 42 nm bandwidth with a brightness of 1.2*10^7 Hz/mW. We perform a continuously working quantum entanglement distribution among three users coexisting with classical light. Under finite-key analysis, we establish secure keys and enable images encryption as well as quantum secret sharing between users. Our work paves the way for practical multiparty quantum communication with integrated photonic architecture compatible with real-world fiber optical communication network

On Improving Robustness of Hardware Security Primitives and Resistance to Reverse Engineering Attacks

The continued growth of information technology (IT) industry and proliferation of interconnected devices has aggravated the problem of ensuring security and necessitated the need for novel, robust solutions. Physically unclonable functions (PUFs) have emerged as promising secure hardware primitives that can utilize the disorder introduced during manufacturing process to generate unique keys. They can be utilized as \textit{lightweight} roots-of-trust for use in authentication and key generation systems. Unlike insecure non-volatile memory (NVM) based key storage systems, PUFs provide an advantage -- no party, including the manufacturer, should be able to replicate the physical disorder and thus, effectively clone the PUF. However, certain practical problems impeded the widespread deployment of PUFs. This dissertation addresses such problems of (i) reliability and (ii) unclonability. Also, obfuscation techniques have proven necessary to protect intellectual property in the presence of an untrusted supply chain and are needed to aid against counterfeiting. This dissertation explores techniques utilizing layout and logic-aware obfuscation. Collectively, we present secure and cost-effective solutions to address crucial hardware security problems

Grid Analysis of Radiological Data

IGI-Global Medical Information Science Discoveries Research Award 2009International audienceGrid technologies and infrastructures can contribute to harnessing the full power of computer-aided image analysis into clinical research and practice. Given the volume of data, the sensitivity of medical information, and the joint complexity of medical datasets and computations expected in clinical practice, the challenge is to fill the gap between the grid middleware and the requirements of clinical applications. This chapter reports on the goals, achievements and lessons learned from the AGIR (Grid Analysis of Radiological Data) project. AGIR addresses this challenge through a combined approach. On one hand, leveraging the grid middleware through core grid medical services (data management, responsiveness, compression, and workflows) targets the requirements of medical data processing applications. On the other hand, grid-enabling a panel of applications ranging from algorithmic research to clinical use cases both exploits and drives the development of the services