Design and analysis of algorithms Algorithmic graph Network Science Image Processing and Data Security
اللغات
English (Proficient)
Arabic (Advanced)
Kurdish (Native)
الروابط الاجتماعية
المؤتمرات العلمية
2023
An enhanced ElGamal cryptosystem for image encryption and decryption
2023-08
2022 International Conference on Computer Science and Software Engineering (CSASE)
ElGamal cryptosystem is one of the well-known public-key algorithms for its ability to generate different ciphertexts for the same plaintext on successive runs. However, this algorithm results in a ciphertext occupying a larger memory space than its plaintext due to its encryption nature. As a result, it is pretty infeasible to use data that require their encrypted form to have the same size, such as image data. To overcome this issue, we propose an enhanced ElGamal cryptosystem that can be used for any given digital data message, including image, text, and video. The proposed approach mainly tests image data, consisting of three stages: key pair generation, image encryption, and image decryption. First, we generate as many random bytes as required for encrypting or decrypting images using the sender or receiver's public key information. Then, we use an XOR operation between each pixel in the image and each randomly generated byte to obtain the encrypted or decrypted image. Experimental results revealed that the proposed approach gives excellent results in various evaluation metrics tested on four different color images.
2021
Fellow Travelers Phenomenon Present in Real-World Networks
2021-11
International Conference on Complex Networks and Their Applications
We investigate a metric parameter “Leanness” of graphs which is a formalization of a well-known Fellow Travelers Property present in some metric spaces. Given a graph G = (V,E), the leanness of G is the smallest λ such that, for every pair of vertices x, y ∈ V , all shortest (x, y)-paths stay within distance λ from each other. We show that this parameter is bounded for many structured graph classes and is small for many real-world networks. We present efficient algorithms to compute or estimate this parameter and evaluate the performance of our algorithms on a number of real-world networks.