112 research outputs found
SURVEY : CRYPTOGRAPHY OPTIMIZATION ALGORITHMS
With the advent of e-commerce, it has become extremely essential to tackle the sensitive issues of affording data security, especially in the ever-blooming open network environment of the modern era. The encrypting technologies of the time-honored cryptography are generally employed to shelter data safety extensively. The term ‘cryptography’ refers to the process of safeguarding the secret data against access by unscrupulous persons in scenarios where it is humanly impossible to furnish physical protection. It deals with the methods which convert the data between intelligible and unintelligible forms by encryption/decryption functions with the management of key(s). Nowadays cryptographic key management issues that arise due to the distributed nature of IT resources, as well the distributed nature of their control. Recently these issues are solved by optimization algorithms utilized in the cryptographic algorithms. The purpose of this paper is to give a survey of optimal cryptographic keys that can be developed with the help of optimization algorithms, and to address their merits to the real-worldscenarios.AbstractWith the advent of e-commerce, it has become extremely essential to tackle the sensitive issues of affording data security, especially in the ever-blooming open network environment of the modern era. The encrypting technologies of the time-honored cryptography are generally employed to shelter data safety extensively. The term ‘cryptography’ refers to the process of safeguarding the secret data against access by unscrupulous persons in scenarios where it is humanly impossible to furnish physical protection. It deals with the methods which convert the data between intelligible and unintelligible forms by encryption/decryption functions with the management of key(s). Nowadays cryptographic key management issues that arise due to the distributed nature of IT resources, as well the distributed nature of their control. Recently these issues are solved by optimization algorithms utilized in the cryptographic algorithms. The purpose of this paper is to give a survey of optimal cryptographic keys that can be developed with the help of optimization algorithms, and to address their merits to the real-worldscenarios. Keywords:Cryptography; Encryption; Decryption; Key Management; Optimization algorithm
HIGH CAPACITY AND OPTIMIZED IMAGE STEGANOGRAPHY TECHNIQUE BASED ON ANT COLONY OPTIMIZATION ALGORITHM
The tremendous development of digital technology, it is mandatory to address the security while transmitting information over network in a way that observer couldn’t depict it. Measures to be taken to provide the security by establishing hidden communication using steganography principle which is help to camouflage the secret information in some carrier file such as text, image, audio and video. In this era of hidden data communication, image becoming an effective tool on account of their frequency, capability and accuracy. Image steganography uses an image as a carrier medium to hide the secret data. The main motive of this article is that the uses the combination of frequency domain and optimization method inorder to increasing in robustness. In this article, Integer Wavelet transform is performed into the host image and coefficients have been transformed. ACO optimization algorithm is used to find the optimal coefficients where to hide the data. Furthermore, sample images and information having been demonstrated which proved the increased robustness as well as high level of data embedding capacity
Lightweight encryption technique to enhance medical image security on internet of medical things applications
The importance of image security in the field of medical imaging is challenging. Several research works have been conducted to secure medical healthcare images. Encryption, not risking loss of data, is the right solution for image confidentiality. Due to data size limitations, redundancy, and capacity, traditional encryption techniques cannot be applied directly to e-health data, especially when patient data are transferred over the open channels. Therefore, patients may lose the privacy of data contents since images are different from the text because of their two particular factors of loss of data and confidentiality. Researchers have identified such security threats and have proposed several image encryption techniques to mitigate the security problem. However, the study has found that the existing proposed techniques still face application-specific several security problems. Therefore, this paper presents an efficient, lightweight encryption algorithm to develop a secure image encryption technique for the healthcare industry. The proposed lightweight encryption technique employs two permutation techniques to secure medical images. The proposed technique is analyzed, evaluated, and then compared to conventionally encrypted ones in security and execution time. Numerous test images have been used to determine the performance of the proposed algorithm. Several experiments show that the proposed algorithm for image cryptosystems provides better efficiency than conventional techniques
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A novel robust watermarking algorithm for encrypted medical image based on DTCWT-DCT and chaotic map
In order to solve the problem of patient information security protection in medical images, whilst also taking into consideration the unchangeable particularity of medical images to the lesion area and the need for medical images themselves to be protected, a novel robust watermarking algorithm for encrypted medical images based on dual-tree complex wavelet transform and discrete cosine transform (DTCWT-DCT) and chaotic map is proposed in this paper. First, DTCWT-DCT transformation was performed on medical images, and dot product was per-formed in relation to the transformation matrix and logistic map. Inverse transformation was undertaken to obtain encrypted medical images. Then, in the low-frequency part of the DTCWT-DCT transformation coefficient of the encrypted medical image, a set of 32 bits visual feature vectors that can effectively resist geometric attacks are found to be the feature vector of the encrypted medical image by using perceptual hashing. After that, different logistic initial values and growth parameters were set to encrypt the watermark, and zero-watermark technology was used to embed and extract the encrypted medical images by combining cryptography and third-party concepts. The proposed watermarking algorithm does not change the region of interest of medical images thus it does not affect the judgment of doctors. Additionally, the security of the algorithm is enhanced by using chaotic mapping, which is sensitive to the initial value in order to encrypt the medical image and the watermark. The simulation results show that the pro-posed algorithm has good homomorphism, which can not only protect the original medical image and the watermark information, but can also embed and extract the watermark directly in the encrypted image, eliminating the potential risk of decrypting the embedded watermark and extracting watermark. Compared with the recent related research, the proposed algorithm solves the contradiction between robustness and invisibility of the watermarking algorithm for encrypted medical images, and it has good results against both conventional attacks and geometric attacks. Under geometric attacks in particular, the proposed algorithm performs much better than existing algorithms
A Secure Image Steganography Using Shark Smell Optimization and Edge Detection Technique
The stegangraphic system supply premium secrecy and ability of conserving the mystery information from gaining stalked or cracked. The suggested method consists of three phases which are edge detection, embedding and extraction. This paper concentrated on three basic and significant parts which are payload, quality, and security also introduces a new steganography method by using edge detection method and shark smell optimization to effectively hide data with in images. Firstly, to promote the hiding ability and to realize altitude standard of secrecy the mystery message is separated into four parts and the cover image is masked and also divided into four sections, then the edge detection algorithm and shark smell optimization is performed on each section respectively. Edge prospectors were utilized to produce edge pixels in every section to hide mystery message and attain the best payload. To increase security, the shark smell optimization is used to select the best pixels among edge pixels based on its nature in motion, then reflect these pixels above original carrier media. Finally the mystery message bits are hidden in the selected edge pixels by using lest significant bit technique. The experimental outcomes appreciated utilizing several image fitness appreciation fashion, it displays best hiding ability, achieve higher image quality with least standard of deformation and provide altitude standard of secrecy, also the results shows that the suggested method exceeds previous approaches in idioms of the PSNSR, MSE also demonstrate that the mystery information cannot be retrieved of the stego image without realizing the algorithms and the values of parameters that are used in hidden proces
Intelligent Circuits and Systems
ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society. This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering
Applied Metaheuristic Computing
For 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
Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts-Volume II
The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications, such as hybrid and microgrid power systems based on the Energy Internet, Blockchain technology, and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above
Applied Methuerstic computing
For 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
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