Two Step Share Visual Cryptography Algorithm for Secure Visual Sharing

This paper re - examines the problem of visual secret sharing for general access structures by using visual cryptograms of random grids (VCRG). Given a binary or color secret image shared by a set of n participants with a strong access structure, we devise t wo effective algorithms to produce a set of VCRG so that the members in each qualified set can reconstruct the secret image by superimposing their sh ares, while those in any forbidden set cannot. The basic 2 out of 2 visual cryptography model consists of a secret message encoded into two transparencies, one transparency representing the cipher text and the other acting as a secret key. Both transparencies appear to be random dots when inspected individually and provide no information about the original clea r text. However, by carefully aligning the transparencies, the original secret message is reproduced. The actual decoding is accomplished by the human visual system. Our algorithms do not require any extr a pixel expansion, which is indispensable and grows exponentially as n increases in conventional visual cryptographic schemes

A Survey on Random Grid based Cryptography Schemes

A random grid based non-expanded Visual cryptography scheme used to generate meaningful as well as meaningless shares. First, analyze the distribution of pixels on the share image and stack image. A probability allocation method is introduced which is capable of producing the better visual quality in share image and stack image. With this method, it not only hide the secret image by using different cover images, but also visual quality of images is improve as needed. The important part is improvement of contrast of both secret and stack images to their theoretical maximum. This method is superior to past methods for visual secret sharing

Efficient Random Grid Visual Cryptographic Schemes having Essential Members

In this paper we consider ``OR based monochrome random grid visual cryptographic schemes (RGVCS) for $t$-$(k,n)^*$ access structure which is a generalization of the threshold $(k,n)$ access structure in the sense that in all the successful attempts to recover the secret image, the $t$ essential participants must always be present. Up to the best of our knowledge, the current proposed work is the first in the literature of RGVCS which provides efficient direct constructions for the $t$-$(k,n)^*$-RGVCS for ``OR based model. Finding the closed form of light contrast is a challenging work. However, in this paper we come up with the closed form of the light contrast for the ``OR based model. In literature, there are visual cryptographic schemes where the secret reconstruction is done by binary ``XOR operation instead of ``OR operation to increase the relative contrast of the decoded image. In this paper, we also propose an extended grid based $t$-$(k,n)^*$-RGVCS in which we replace the traditional ``OR operation by ``XOR operation. Note that the use of XOR operation indicates that the decoding must be performed computationally and not visually. We justified our schemes using both experimental as well as simulation based data

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

Building Machines That Learn and Think Like People

Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn, and how they learn it. Specifically, we argue that these machines should (a) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (b) ground learning in intuitive theories of physics and psychology, to support and enrich the knowledge that is learned; and (c) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes towards these goals that can combine the strengths of recent neural network advances with more structured cognitive models.Comment: In press at Behavioral and Brain Sciences. Open call for commentary proposals (until Nov. 22, 2016). https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/information/calls-for-commentary/open-calls-for-commentar

Towards Cyber Security for Low-Carbon Transportation: Overview, Challenges and Future Directions

In recent years, low-carbon transportation has become an indispensable part as sustainable development strategies of various countries, and plays a very important responsibility in promoting low-carbon cities. However, the security of low-carbon transportation has been threatened from various ways. For example, denial of service attacks pose a great threat to the electric vehicles and vehicle-to-grid networks. To minimize these threats, several methods have been proposed to defense against them. Yet, these methods are only for certain types of scenarios or attacks. Therefore, this review addresses security aspect from holistic view, provides the overview, challenges and future directions of cyber security technologies in low-carbon transportation. Firstly, based on the concept and importance of low-carbon transportation, this review positions the low-carbon transportation services. Then, with the perspective of network architecture and communication mode, this review classifies its typical attack risks. The corresponding defense technologies and relevant security suggestions are further reviewed from perspective of data security, network management security and network application security. Finally, in view of the long term development of low-carbon transportation, future research directions have been concerned.Comment: 34 pages, 6 figures, accepted by journal Renewable and Sustainable Energy Review

Parallel Processing of RSAAlgorithm Using MPI Library

This report explains the project of developing Parallel Processing of RSA Algorithm Using MPI Library. RSA Algorithm is a public-key cryptosystem that offers encryption technique which security is based on the difficulty of factoring large prime integers. The computation of RSA is performed by a series of intensive computational of modular multiplications. The scope of this project is developing a parallel system to generate public and private key, and to encrypt and decrypt files using the algorithm of RSA. The system is needed to be parallel as to overcome the problem of intensive computational by the RSA algorithm. This parallel system is going to be embedded on grid or cluster computing environment. The language and library that are going to be used for the system is C++ and Message Passing Interface (MPI). This project is completed phase by phase and for the system development, the method used is evolutionary development approach. The end result of this project is a parallel algorithm of RSA cryptosystem.

On security and privacy of consensus-based protocols in blockchain and smart grid

In recent times, distributed consensus protocols have received widespread attention in the area of blockchain and smart grid. Consensus algorithms aim to solve an agreement problem among a set of nodes in a distributed environment. Participants in a blockchain use consensus algorithms to agree on data blocks containing an ordered set of transactions. Similarly, agents in the smart grid employ consensus to agree on specific values (e.g., energy output, market-clearing price, control parameters) in distributed energy management protocols. This thesis focuses on the security and privacy aspects of a few popular consensus-based protocols in blockchain and smart grid. In the blockchain area, we analyze the consensus protocol of one of the most popular payment systems: Ripple. We show how the parameters chosen by the Ripple designers do not prevent the occurrence of forks in the system. Furthermore, we provide the conditions to prevent any fork in the Ripple network. In the smart grid area, we discuss the privacy issues in the Economic Dispatch (ED) optimization problem and some of its recent solutions using distributed consensus-based approaches. We analyze two state of the art consensus-based ED protocols from Yang et al. (2013) and Binetti et al. (2014). We show how these protocols leak private information about the participants. We propose privacy-preserving versions of these consensus-based ED protocols. In some cases, we also improve upon the communication cost