A series of previously conducted experiments pertaining to various chemicals and drugs uncover a natural linkage between the molecular structures and the bio-medical and pharmacological characteristics The forgotten topological index computed for the molecular structures of various chemical compounds and drugs has proven significant in medical and pharmaceutical fields by predicting biological features of new chemical compounds and drugs A topological index can be considered as the transformation of chemical structure into a real number Dendrimers are highly-branched star-shaped macromolecules with nanometer-scale dimensions Dendrimers are defined by three components: a central core, an interior dendritic structure (the branches), and an exterior surface with functional surface groups In this paper, we determine forgotten topological indices of poly(propyl) ether imine, porphyrin, and zinc-porphyrin dendrimers

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On Forgotten Topological Indices of Some Dendrimers Structure.

Recent study shows that substitution box (S-box) only cannot be reliably used in image encryption techniques. We, in this paper, propose a novel and secure image encryption scheme that utilizes the combined effect of an algebraic substitution box along with the scrambling effect of the Arnold transform. The underlying algorithm involves the application of S-box, which is the most imperative source to create confusion and diffusion in the data. The speciality of the proposed algorithm lies, firstly, in the high sensitivity of our S-box to the choice of the initial conditions which makes this S-box stronger than the chaos-based S-boxes as it saves computational labour by deploying a comparatively simple and direct approach based on the algebraic structure of the multiplicative cyclic group of the Galois field. Secondly the proposed method becomes more secure by considering a combination of S-box with certain number of iterations of the Arnold transform. The strength of the S-box is examined in terms of various performance indices such as nonlinearity, strict avalanche criterion, bit independence criterion, linear and differential approximation probabilities etc. We prove through the most significant techniques used for the statistical analyses of the encrypted image that our image encryption algorithm satisfies all the necessary criteria to be usefully and reliably implemented in image encryption applications.

A Novel Image Encryption Based on Algebraic S-box and Arnold Transform

Image steganography is the art of hiding secret message onto the source image. A good approach to steganography must provide two attributes: high stego image quality and high embedding capacity. In this paper, a frequency domain steganography based information hiding technique using Fresnelet transform (FT), has been proposed. In this method, the Fresnelet coefficients of the Least Significant Bit (LSB) at high frequency subbands are used to embed the QR coded secret message. This approach yields an average PSNR of 45.40 dB and an embedding capacity of 352,332 bits. These results validate the practical feasibility of the proposed method for security applications.

Frequency domain QR code based image steganography using Fresnelet transform

A new blind data hiding scheme is proposed in which data is decomposed using the Fresnelet transform. The inverse Fresnelet transform is performed on decomposed subbands by choosing different key parameters, and the coded pattern of the information data is obtained. This coded pattern is embedded into particular subbands of the cover image using the wavelets. The proposed method has good imperceptibility and large capacity of the information embedded data. Using the Fresnelet transform with a family of wavelet transforms makes the scheme more efficient in terms of extracted accuracy of hidden information. Moreover, the hidden data can be recovered without access to the original cover data. The proposed method is used to resolve privacy and security issues raised with respect to emerging internet applications for the effective handling of confidential data.

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Blind data hiding technique using the Fresnelet transform.

Image steganography is the art of hiding highly sensitive information onto the cover image. An ideal approach to image steganography must satisfy two factors: high quality of stego image and high embedding capacity. Conventionally, transform based techniques are widely preferred for these applications. The commonly used transforms for steganography applications are Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) etc. In this work, frequency domain transforms such as Fresnelet Transform (FT) and Contourlet Transform (CT) are used for the data hiding process. The secret data is normally hidden in the coefficients of these transforms. However, data hiding in transform coefficients yield less accurate results since the coefficients used for data hiding are selected randomly. Hence, in this work, optimization techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used for improving the performance of the steganography system. GA and PSO are used to find the best coefficients in order to hide the Quick Response (QR) coded secret data. This approach yields an average PSNR of 52.56 dB and an embedding capacity of 902,136 bits. These experimental results validate the practical feasibility of the proposed methodology for security applications.

Performance enhanced image steganography systems using transforms and optimization techniques

Medical images are commonly stored in digital media and transmitted via Internet for certain uses. If a medical information image alters, this can lead to a wrong diagnosis which may create a serious health problem. Moreover, medical images in digital form can easily be modified by wiping off or adding small pieces of information intentionally for certain illegal purposes. Hence, the reliability of medical images is an important criterion in a hospital information system. In this paper, Fresnelet transform is employed along with appropriate handling of the Arnold transform and the discrete cosine transform to provide secure distribution of medical images. This method presents a new data hiding system in which steganography and cryptography are used to prevent unauthorized data access. The experimental results exhibit high imperceptibility for embedded images and significant encryption of information images.

A Fresnelet-Based Encryption of Medical Images using Arnold Transform

Medical images are commonly stored in digital media and transmitted via Internet for certain uses. If a medical information image alters, this can lead to a wrong diagnosis which may create a serious health problem. Moreover, medical images in digital form can easily be modified by wiping off or adding small pieces of information intentionally for certain illegal purposes. Hence, the reliability of medical images is an important criterion in a hospital information system. In this paper, the Fresnelet transform is employed along with appropriate handling of the Arnold transform and the discrete cosine transform to provide secure distribution of medical images. This method presents a new data hiding system in which steganography and cryptography are used to prevent unauthorized data access. The experimental results exhibit high imperceptibility for embedded images and significant encryption of information images.

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Bibi Nargis

Papers

A Fresnelet-Based Encryption of Medical Images using Arnold Transform

A Fresnelet-Based Encryption of Medical Images using Arnold Transform