LIGHTWEIGHT CRYPTOGRAPHY METHOD IN THE INTERNET OF THINGS USING ELLIPTIC CURVE AND CROW SEARCH ALGORITHM

The Internet of Things (IoT) as an important technology consists of a heterogeneous and huge number of devices that generates an enormous amount of data in various applications. However, generating and transmitting huge amount of data in the IoT makes it crucial to implement a secure and safe data transmission scheme. Cryptography methods can secure the confidentiality, data integrity, access control, and authentication. Due to constrained resources in IoT devices, providing classical cryptography schemes isn’t efficient for IoT applications, so a lightweight cryptography scheme is one of the most important solutions to overcome security challenges in IoT. In this paper, a new security scheme called ECCCSASHA256 based on Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm (SHA-256) using Crow Search Algorithm (CSA) has been proposed for secure data transmission in IoT devices. The ECCCSASHA256 model uses the CSA for generating a private key to encode the elliptic curve. Furthermore, the proposed scheme uses SHA-256 model for hashing the incoming encoded data using ECC. The simulation results indicate that the average throughput of the proposed model was about 8.22% and 8.97% higher in encryption and 8.72% and 9.81% higher in decryption compared to 3DES&ECC&SHA-256 and RC4&ECC&SHA-256, respectively

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