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This paper presents an anti-geometric attacks algorithm of color image watermarking based on the scale-invariant feature transformation (SIFT). Firstly, the method detects SIFT feature points in the red component of a true color image and filters out the feature points information. Then three-level Discrete Integer Wavelet Transform (DIWT) is performed on the blue and green component of the color image to extract the low-frequency component coefficient. Finally, a binary watermark which has been scrambled is embedded in the low-frequency wavelet coefficients of the blue component. The simulation results show that the algorithm is robust against signal processing and geometric attacks.

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The Internet of Things (IoT) is a dispersed network system that connects the world through the Internet. The architecture of IoT consists of more gateways and resources which cannot be allocated in a manual process. The allocation of resources in IoT is a challenging process due to the higher consumption of energy and high latency rate. To overcome the challenges in existing works, this research introduced an Improved Reptile Search Algorithm (IRSA) to solve the optimization problem which occurs during the time of allocation resources among IoT networks. IRSA employs the methodology of levy flight and cross-over to update the candidate position and enhance the search speed in a single iteration. The proposed method consumes less energy and has low latency during data transmission from User equipment (UE) to the base station.IRSA has been compared with the existing Scalable Resource Allocation Framework (SRAF) and Improved Chaotic Firefly Algorithm (ICFA). The obtained experimental results show that the proposed IRSA attained better performance with an allocation rate of 96.40% which is comparatively higher than SRAF and ICFA with 92.40% and 91.67% respectively.