Yazar "Ismael, O.A." seçeneğine göre listele
Listeleniyor 1 - 4 / 4
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe Exploring Lightweight Blockchain Solutions for Internet of Things: Review(Springer Science and Business Media Deutschland GmbH, 2024) Ismael, O.A.; Abdulrazzaq, M.M.; Ramaha, N.T.A.; Mukhlif, Y.A.; Al, Zakitat, M.A.S.The world is witnessing a major digital transformation and is moving towards more interaction, connectivity, ease, and intelligence through the Internet of Things (IoT). The IoT offers these advantages to the world by linking necessary devices with each other, making it easier to manage and deal with those devices. However, the IoT faces many challenges, such as authentication, privacy, security, and access management. The application of blockchain technology may provide a solution to these challenges. Nevertheless, applying blockchain technology may face limitations, such as the limited resources of the IoT devices used and the resource-intensive requirements of the blockchain. Therefore, to overcome these limitations, several studies have proposed using a lightweight blockchain; this blockchain is specifically designed for resource-limited IoT devices. In this paper, a comprehensive review has been made on the uses of lightweight blockchain in the IoT. Moreover, we identified some of the challenges facing the application of blockchain technologies in the IoT and the future directions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Öğe Harnessing Advanced Techniques for Image Steganography: Sequential and Random Encoding with Deep Learning Detection(Springer Science and Business Media Deutschland GmbH, 2024) Al, Zakitat, M.A.S.; Abdulrazzaq, M.M.; Ramaha, N.T.A.; Mukhlif, Y.A.; Ismael, O.A.This study delves into the intricacies of steganography, a method employed for concealing information within a clandestine medium to enhance data security during transmission. Given that information is often represented in various forms, such as text, audio, video, or images, steganography offers a distinctive advantage over conventional cryptography by focusing on concealing the very existence of the message, rather than merely its content. This research introduces a novel steganographic technique that places equal emphasis on both message concealment and security enhancement. This study highlights two primary steganographic methods: sequential encoding and random encoding. By employing both encryption and image compression, these techniques fortify data security while preserving the visual integrity of cover images. Advanced deep learning models, namely Vgg-16 and Vgg-19, are proposed for the detection of image steganography, with their accuracy and loss rates rigorously evaluated. The significance of steganography extends across various sectors, including the military, government, and online domains, underscoring its pivotal role in contemporary data communication and security. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Öğe Information Retrieval System of Arabic Alphabetic Characters by Using Hidden Markov Model(Institute of Electrical and Electronics Engineers Inc., 2022) Shaker, A.S.; Khaleel, M.F.; Ismael, O.A.; Majeed, R.S.; Ahmed, M.R.In this paper, recognizing Arabic printed text is presented. A long time ago Recognizing the Arabic text has received great interest in information technology applications, as the Arabic language is among the different languages, and what distinguishes it from other languages is also shared by the Persian language and the ancient Turkish language (Ottoman) the difficulty of recognizing the letter because the letter has several forms in The beginning of the word and a shape in its middle and a shape at the end of the word. In languages other than the letters are written, the shape of the letter is one in the word, so it is easy to manipulate it through ready-made Optical Character Recognition (OCR) programs as letters A to Z. As a result, this study proposes a method for distinguishing Arabic printed text from other printed text. He's been looking forward to this moment for a long time. We demonstrate an off-line system that recognizes printed Arabic text by employing a Hidden Markov Model and an algorithm that divides the recognize reviews literature into sections and characters. © 2022 IEEE.Öğe A New Approach to Arabic Spam Tweet Detection in Twitter Using Machine Learning Algorithms(American Institute of Physics Inc., 2022) Ismael, O.A.; Çelik, Ö.Ü.Y.Artificial intelligence is involved in all aspects of life and with the development of social media, the methods used in sending spam have evolved and it becomes difficult to detect and control it manually. Therefore, due to the need to use artificial intelligence in language processing and the detection of propaganda messages by classifying posts and tweets that carry a disturbing message on Twitter in this study, We propose a new system to detect spam in Twitter for the Arabic language, based on the trend of hashtags, using artificial intelligence algorithms and extracting properties. It contains three data collection stages, image and text characteristics extraction, and classification stage based on combination of CNN algorithm and SVM algorithm. In addition to this search, annoying text and images, in addition to combining two classification algorithms. The classification accuracy is 98% and the results indicate the best compared to the rest of the models when tested after the testing process on four samples of the data collected from Twitter. © 2022 American Institute of Physics Inc.. All rights reserved.
