4 research outputs found
āļāļēāļĢāļĢāļ§āļĄāļāļąāļāļāļāļāļ§āļīāļāļĒāļēāļāļēāļĢāļāļģāļāļĢāļēāļāļāđāļāļĄāļđāļĨāļāļąāļāļ§āļīāļāļĒāļēāļāļēāļĢāđāļāđāļēāļĢāļŦāļąāļŠāļĨāļąāļ āļŠāļģāļŦāļĢāļąāļāļ āļēāļāļāļēāļāļāļēāļĢāđāļāļāļĒāđ
Get PDFāļāļāļāļąāļāļĒāđāļ āļāļēāļāļ§āļīāļāļąāļĒāļāļĩāđāļāļģāđāļŠāļāļāļāļēāļĢāļĢāļ§āļĄāļāļąāļāļāļāļāļŠāļāļāļāļąāđāļāļāļāļāļ§āļīāļāļĩāļāļĢāļ°āļāļāļāļāđāļ§āļĒāļāļēāļĢāļāļģāļāļĢāļēāļāļāđāļāļĄāļđāļĨāđāļāļāļāļĩāđāļŠāļēāļĄāļēāļĢāļāļāļđāđāļāļ·āļāļāļĨāļąāļāđāļāđ (Reversible Data Hiding: RDH) āđāļĨāļ°āļāļēāļĢāđāļāđāļēāļĢāļŦāļąāļŠāļĨāļąāļ (Advanced Encryption Standard: AES) āđāļāļ·āđāļāđāļāļīāđāļĄāļāļĢāļ°āļŠāļīāļāļāļīāļ āļēāļāļāļ§āļēāļĄāļāļĨāļāļāļ āļąāļĒāđāļāļāļēāļĢāđāļāđāļēāļāļķāļāļāđāļāļĄāļđāļĨ āļŦāļĨāļēāļĒāđāļāļāļāļīāļāļāļāļ RDH āļāļđāļāđāļāđāļĢāđāļ§āļĄāļāļąāļāđāļāļ·āđāļāđāļŦāđāđāļāđāļĢāļąāļāļāļ§āļēāļĄāļāļīāļāđāļāļ·āļāļāļāđāļģāļŠāļļāļāļŠāļģāļŦāļĢāļąāļāļāļēāļĢāļāđāļāļāļāđāļāļĄāļđāļĨ āļŦāļāļķāđāļāļāļąāļ§āļāļģāļāļēāļĒ Linear Fitting Rhombus Pattern (LFRP) āļāļđāļāđāļāđāļŠāļģāļŦāļĢāļąāļāļāļēāļĢāļāļģāļāļēāļĒ, Local variance āđāļāđāļŠāļģāļŦāļĢāļąāļāļāļēāļĢāđāļĢāļĩāļĒāļāļāđāļēāļāļ§āļēāļĄāļāļīāļāļāļĨāļēāļāļāļēāļāļāļēāļĢāļāļģāļāļēāļĒ, Double Modification Testing (DMT) āđāļāđāđāļāļ·āđāļāļāļēāļĢāļāļĢāļ§āļāļŠāļāļāļŠāļāļēāļāļ°āļāļāļāļāļīāļāđāļāļĨ āđāļĨāļ°āđāļāļāļāļīāļ Histogram Shifting āđāļāđāđāļāļāļēāļĢāļāļąāļ āļĄāļēāļāđāļāļāļ§āđāļēāļāļąāđāļ āļāļąāđāļāļāļāļāļ§āļīāļāļĩ AES āļāļđāļāļāļĢāļ°āļĒāļļāļāļāđāđāļāđāļĢāđāļ§āļĄāđāļāļāļēāļāļāļĩāđāļŠāļģāļŦāļĢāļąāļāļāļēāļĢāđāļāđāļēāļĢāļŦāļąāļŠāļĨāļąāļāļāļĩāļāļāļąāđāļāļŦāļāļķāđāļāļŠāļģāļŦāļĢāļąāļāļāđāļāļĄāļđāļĨ Header 128 āļāļīāļ āļāļāļāļāļąāđāļāļāļāļāļ§āļīāļāļĩāļāļēāļĢāđāļāđāļēāļĢāļŦāļąāļŠ RDH āđāļāļ·āđāļāđāļŦāđāđāļāđāđāļāļŠāļģāļŦāļĢāļąāļāļāļēāļĢāļāđāļāļāļāļąāļāļāļēāļĢāđāļāđāļēāļāļķāļāļāđāļāļĄāļđāļĨāđāļāļĒāļāļļāļāļāļĨāļāļĩāđāđāļĄāđāđāļāđāļĢāļąāļāļāļāļļāļāļēāļ āļāļēāļĢāļāļāļŠāļāļāļ āļēāļāđāļāļāđāļāļāļēāļĢāļĩāļŦāļĨāļēāļĒāļāļāļēāļāļāļđāļāđāļāđāļāļąāļāļĨāļāđāļāļ āļēāļāļāļēāļāļāļēāļĢāđāļāļāļĒāđāļāļķāđāļāđāļāđāļĢāļąāļāļĄāļēāļāļēāļāđāļāļĢāļ·āđāļāļāļĄāļ·āļāļāļĩāđāđāļāļāļāđāļēāļāļāļąāļ āļāļēāļāļīāđāļāđāļ Magnetic Resonance Image (MRI) Ultrasound (US) āđāļĨāļ° X-ray āļāļĨāļĨāļąāļāļāđāļāļąāđāļāļāļāļāļ§āļīāļāļĩāļāļĩāđāļāļģāđāļŠāļāļāđāļŠāļāļāđāļŦāđāđāļŦāđāļāļāļ§āļēāļĄāļāļīāļāđāļāļ·āļāļāļāļāļāļāļēāļĢāļāļąāļāļāļĩāđāļāđāļģ āđāļĨāļ°āļāļ§āļēāļĄāļāļĨāļāļāļ āļąāļĒāļāļāļāļāļēāļĢāđāļāđāļēāļāļķāļāļāđāļāļĄāļđāļĨāļāļĩāđāļŠāļđāļāļāļķāđāļ āļāļģāļŠāļģāļāļąāļ: āļāļēāļĢāļāļģāļāļĢāļēāļāļāđāļāļĄāļđāļĨāđāļāļāļāļĩāđāļŠāļēāļĄāļēāļĢāļāļāļđāđāļāļ·āļāļāļĨāļąāļāđāļāđ (RDH) āļāļēāļĢāđāļāđāļēāļĢāļŦāļąāļŠāļĨāļąāļ (AES) ABSTRACT This paper presents two algorithms, Reversible Data Hiding (RDH) and Advanced Encryption Standard (AES) to enhance the security of unauthorized data access. Many techniques of RDH can be shared to achieve minimal distortion when hiding information. A Linear Fitting Rhombus Pattern Predictor (LFRPP) was used for prediction, with, local variance to sort prediction error values. Double Modification Testing (DMT) was used to check the status of pixels with Histogram Shifting (HS) employed for data embedding. The AES algorithm was applied for encryption 128 bit RDH encoder algorithm Header to ensure data protection and restrict access by unauthorized persons. Various quantities of binary information embedded into medical imaging and derived from the diverse sources of Magnetic Resonance Image (MRI), Ultrasound (US) and X-ray were tested. Results showed a distortion between embedding low and higher data security. Â Keyword: Reversible Data Hiding, Advanced Encryption Standar
Applied Metaheuristic Computing
Get PDFFor decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC
Applied Methuerstic computing
Get PDFFor decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC
