Conventional visual secret sharing (VSS) schemes hide secret images in shares that are either printed on transparencies or are encoded and stored in a digital form. The shares can appear as noise-like pixels or as meaningful images; but it will arouse suspicion and increase interception risk during transmission of the shares. Hence, VSS schemes suffer from a transmission risk problem for the secret itself and for the participants who are involved in the VSS scheme. To address this problem, we proposed a natural-image-based VSS scheme (NVSS scheme) that shares secret images via various carrier media to protect the secret and the participants during the transmission phase. The proposed (n,n)- NVSS scheme can share one digital secret image over n-1 arbitrary selected natural images (called natural shares) and one noise-like share. The natural shares can be photos or hand-painted pictures in digital form or in printed form. The noise-like share is generated based on these natural shares and the secret image. The unaltered natural shares are diverse and innocuous, thus greatly reducing the transmission risk problem. We also propose possible ways to hide the noise-like share to reduce the transmission risk problem for the share. Experimental results indicate that the proposed approach is an excellent solution for solving the transmission risk problem for the VSS schemes.

Visual cryptography schemes (VCSs) generate random and meaningless shares to share and protect secret images. Conventional VCSs suffer from a transmission risk problem because the noise-like shares will raise the suspicion of attackers and the attackers might intercept the transmission. Previous research has involved in hiding shared content in halftone shares to reduce these risks, but this method exacerbates the pixel expansion problem and visual quality degradation problem for recovered images. In this paper, a binocular VCS (BVCS), called the (2,n)-BVCS, and an encryption algorithm are proposed to hide the shared pixels in the single image random dot stereograms (SIRDSs). Because the SIRDSs have the same 2D appearance as the conventional shares of a VCS, this paper tries to use SIRDSs as cover images of the shares of VCSs to reduce the transmission risk of the shares. The encryption algorithm alters the random dots in the SIRDSs according to the construction rule of the (2,n)-BVCS to produce nonpixel-expansion shares of the BVCS. Altering the dots in a SIRDS will degrade the visual quality of the reconstructed 3D objects. Hence, we propose an optimization model that is based on the visual quality requirement of SIRDSs to develop construction rules for a (2,n)-BVCS that maximize the contrast of the recovered image in the BVCS.

Conventional visual cryptography (VC) suffers from a pixel-expansion problem, or an uncontrollable display quality problem for recovered images, and lacks a general approach to construct visual secret sharing schemes for general access structures. We propose a general and systematic approach to address these issues without sophisticated codebook design. This approach can be used for binary secret images in non-computer-aided decryption environments. To avoid pixel expansion, we design a set of column vectors to encrypt secret pixels rather than using the conventional VC-based approach. We begin by formulating a mathematic model for the VC construction problem to find the column vectors for the optimal VC construction, after which we develop a simulated-annealing-based algorithm to solve the problem. The experimental results show that the display quality of the recovered image is superior to that of previous papers.

Conventional visual secret sharing schemes generate noise-like random pixels on shares to hide secret images. It suffers a management problem, because of which dealers cannot visually identify each share. This problem is solved by the extended visual cryptography scheme (EVCS), which adds a meaningful cover image in each share. However, the previous approaches involving the EVCS for general access structures suffer from a pixel expansion problem. In addition, the visual cryptography (VC)-based approach needs a sophisticated codebook design for various schemes. In this paper, we propose a general approach to solve the above- mentioned problems; the approach can be used for binary secret images in noncomputer-aided decryption environments. The pro- posed approach consists of two phases. In the first phase, based on a given access structure, we construct meaningless shares using an optimization technique and the construction for conventional VC schemes. In the second phase, cover images are added in each share directly by a stamping algorithm. The experimental results indicate that a solution to the pixel expansion problem of the EVCS for GASs is achieved. Moreover, the display quality of the recovered image is very close to that obtained using conventional VC schemes.

Reducing the pixel expansion and improving the display quality of recovered images are still major issues in visual cryptography schemes (VCSs), particularly for largekandn. Moreover, the development of a systematic and practical approach for threshold VCSs is a challenge. In this paper, a pixel-expansion-free threshold VCSs approach based on an optimization technique is proposed in order to encrypt binary secret images. In addition to contrast, we consider blackness as a performance metric in the evaluation of the display quality of recovered images. We first formulate the problem as a mathematical optimization model in order to maximize the contrast of recovered images that are subject to density-balance and blackness constraints. We then develop a simulated-annealing-based algorithm to solve this problem. Furthermore, we try to promote the contrast by slightly relaxing the density-balance constraint. The experimental results show that the proposed optimization-based approach significantly outperforms previous methods in terms of both the pixel expansion factor and the display quality of recovered images.

In this paper, we develop a novel algorithm to deploy an energy-efficient wireless sensor network (WSN) for the target-location service that is one of the major applications of sensor networks. Such sensor network has to be designed to achieve complete coverage quality of surveillance and full discrimination for predetermined resolution on the sensor field. To extend lifetime of sensor network, the duplicate deployment approach is a simple and intuitive way. However, such approach will result in increasing too much deployment cost. In this paper, we propose a novel strategy to cope with the problem. We consider deploying K independent sets of sensors to monitoring the area in turn and locating the intruder together. With this strategy, the duty cycle of each sensor is only 1/K and the lifetime of the sensor network will be extended up to K times. Such sensor placement problem is a variant of the set K-cover problem, which is NP-complete. We formulate the problem as a 0/1 integer-programming problem. A Lagrangean relaxation based heuristic then is proposed for solving the optimization problem. The experimental results show that the proposed strategy gets a significant improvement in the lifetime of sensor network compared to the duplicate deployment approach under the deployment cost constraint. The proposed algorithm is highly effective in terms of the overall deployment cost. Furthermore, the algorithm is very efficient and scalable in terms of the solution time. I. INTRODUCTION The rapid growth in sensor technology and wireless com- munication has led to the development of wireless sensor networks (WSNs). A wireless sensor network comprises sev- eral sensors, sink nodes, and back-end systems. These tiny, low-cost, and low power sensors are deployed in an ad hoc manner in an interested area. These sensors collect physical information from the area, process and forward the information to the sink nodes. Afterward, the back-ends can obtain global views according to the information provided by the sink nodes

In this paper, we develop an algorithm to deploy an energy efficient sensor network such that it provides surveillance and target-positioning services. We consider to place K independent sets of sensors on a sensor field. These sets monitor the field in turn and work together when intrusion events occur. The lifetime of the sensor network is therefore prolonged up to K times. The problem is therefore a variant of the set K-cover problem, which is NP-complete. We formulate such sensor deployment problem, as a 0/1 integer programming problem. A simulated annealing based heuristic then is proposed for solving the optimization problem. The experimental results show that the proposed algorithm indicates a significant improvement in the sensor lifetime compared to the intuitive approach. Furthermore, the proposed algorithm is highly effective and efficient in terms of the overall deployment cost.