Efficiency-Aware Watermarking using Different Wavelet Families for the Internet of Things

Efficient image transfer in the Internet of Things (IoT) Era, has many requirements that need to be satisfied based on the nature of each underlying application. Internet of Things is a research paradigm that empowers data, data fusion and encompasses embedded images, which need to be transmitted to numerous interconnected devices. The risks of contravention of owner's rights are increasing, while data transfer creates new demands for securing the Internet of Things. In this respect, watermarking schemes can be used to save those rights from illegal usage and copying of digital image data. For IoT applications digital watermarking can be used to guarantee that the data used is protected and the rights of the owner are secured (i.e. both user and machine generated). This work proposes a novel watermarking scheme based on the biorthogonal family, (biorthogonal 2.2, biorthogonal 3.5 and biorthogonal 5.5) wavelet transform, while it uses a convolution for symlets wavelet transform and coiflets wavelet transform. These wavelet family approaches are highly robust against various types of attacks (both passive and active), for the prevention of the piracy and authentication of the data over IoT ecosystems. The proposed framework is thoroughly evaluated showing great robustness against attacks and allowing a higher level of protection compared to other available frameworks and schemes.