Ensuring security, integrity, and reliability of the election process consider as the main challenges in the electronic voting system. This paper describes the e-voting system by integrating the biometric authentication, advanced encryption, and watermarking techniques towards meeting such challenges. The system employs the fingerprint authentication by utilizing the Scale-Invariant Feature Transform (SIFT) for verifying the identity of the voter to ensure genuineness and non-repudiation of the service. The vote will be encrypted with the AES-GCM technique to be employed in securing the voting process, thus ensuring both data privacy and integrity. Hybrid Blind Watermarking employs the technique of Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) for embedding the encrypted vote into the colored watermark cover image. Increased robustness against attacks with maintained vote confidentiality is achieved through this approach. The experimental results proved its imperceptibility to reach a Peak Signal-to-Noise Ratio (PSNR) of 40.7 and Normalized Correlation (NC) of 1. Thus, the proposed system enhances the theoretical foundation of secure e-voting and provides an implementation strategy for a reliable and tamper-proof voting system.
In this paper, we designed a new efficient stream cipher cryptosystem that depend on a chaotic map to encrypt (decrypt) different types of digital images. The designed encryption system passed all basic efficiency criteria (like Randomness, MSE, PSNR, Histogram Analysis, and Key Space) that were applied to the key extracted from the random generator as well as to the digital images after completing the encryption process.
Secured multimedia data has grown in importance over the last few decades to safeguard multimedia content from unwanted users. Generally speaking, a number of methods have been employed to hide important visual data from eavesdroppers, one of which is chaotic encryption. This review article will examine chaotic encryption methods currently in use, highlighting their benefits and drawbacks in terms of their applicability for picture security.
Gastroesophageal reflux disease (GERD) is a prevalent clinical condition, that affects millions of individuals worldwide. Objective: To assess the level of soluble HLA-E (sHLA-E) as a biomarker in the diagnosis and immunopathogenesis of GERD patients. Methods: The case-control prospective study included 40 GERD patients who were consulted at the Gastroenterology Unit of AlKindy Teaching Hospital, as along with 40 healthy control subjects. The study period extended from January 2023 to May 2024. Blood was drawn from both groups and serum was separated to assesssHLA-E using a sandwich enzyme-linked immunosorbent assay (ELISA) kit. Results: There was a statistically significant difference in sHLA-E levels between GERD patients and healthy cont
... Show MoreEstimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes
... Show MoreKE Sharquie, AA Noaimi, ER Shwail, J Clin Exp Dermatol Res, 2012 - Cited by 41