Biblio
Cancelable biometric is a new era of technology that deals with the protection of the privacy content of a person which itself helps in protecting the identity of a person. Here the biometric information instead of being stored directly on the authentication database is transformed into a non-invertible coded format that will be utilized for providing access. The conversion into an encrypted code requires the provision of an encryption key from the user side. Both invertible and non-invertible coding techniques are there but non-invertible one provides additional security to the user. In this paper, a non-invertible cancelable biometric method has been proposed where the biometric image information is canceled and encoded into a code using a user-provided encryption key. This code is generated from the image histogram after continuous bin updation to the maximal value and then it is encrypted by the Hill cipher. This code is stored on the database instead of biometric information. The technique is applied to a set of retinal information taken from the Indian Diabetic Retinopathy database.
In our time the rapid growth of internet and digital communications has been required to be protected from illegal users. It is important to secure the information transmitted between the sender and receiver over the communication channels such as the internet, since it is a public environment. Cryptography and Steganography are the most popular techniques used for sending data in secrete way. In this paper, we are proposing a new algorithm that combines both cryptography and steganography in order to increase the level of data security against attackers. In cryptography, we are using affine hill cipher method; while in steganography we are using Hybrid edge detection with LSB to hide the message. Our paper shows how we can use image edges to hide text message. Grayscale images are used for our experiments and a comparison is developed based on using different edge detection operators such as (canny-LoG ) and (Canny-Sobel). Their performance is measured using PSNR (Peak Signal to Noise ratio), MSE (Mean Squared Error) and EC (Embedding Capacity). The results indicate that, using hybrid edge detection (canny- LoG) with LSB for hiding data could provide high embedding capacity than using hybrid edge detection (canny- Sobel) with LSB. We could prove that hiding in the image edge area could preserve the imperceptibility of the Stego-image. This paper has also proved that the secrete message was extracted successfully without any distortion.