Over many years, in order to provide powerful techniques for protecting digital copyrights, digital watermarking techniques have been developed. This research focuses on proposing an efficient blind hybrid digital image watermarking technique based on the transformation of Daubechies wavelet (DW) and Block Bitmap modification (BBM). DW represents an effective multi-determination frequency domain for including the watermarks. The BBM is used to afford an enhanced capability of embedding and minimize distortion. Two layers of security have been added to the proposed technique for protecting digital images from theft by using the logistic chaotic mapping to select the position of the blocks for the embedding process and Lorenz chaotic mapping for scrambling the watermark image. In the experiments, high values of peak signal to noise ratio (PSNR) and structural similarity index (SSIM) are obtained, and all the obtained results illustrate that the presented technique is highly imperceptible, secure, and robust.

<p>Wireless sensor nodes consist of tiny electronic devices that can sense, transmit, and measure data from physical environments such as the field of minter surveillance. These sensor nodes significantly depend on batteries to gain energy which is used to operations associated with communication and computation. Generally, designing communication protocols is feasible to achieve effective usage of these energy resources of the sensor node. Both reported medium access control and routing can achieve energy-saving that supporting real time functionality. This paper emphasizes the use of hybrid modified PEGASIS-Ant lion optimization. Several steps are entailed in this research. First is random distribution of node followed by clustering the map as a circular region. Then, the nodes are connected to the closest node in that region. In consequence, PEGASIS-Ant lion optimization is applied to enhance the connection of the nodes and accomplish the maximum life batter of the sensor. At last, the experiments performed in this work demonstrate that the proposed optimization technique operates well in terms of network latency, power duration and energy’s consumption. Furthermore, the life span of the nodes has improved greatly by 87% over the original algorithm that accomplished a rate of life nodes of 60%.</p>

No abstract