GAME THEORY BASED SOLUTION FOR NETWORK SECURITY
الباحثونRaghad I. Hussein، Nasrullah Pirzada
المجلةJournal of Hunan University ( Natural Sciences)
مختصر البحثAbstract— Today in this modern age, network security is the hottest and trendy topic of research.
Features of network security globally change due to rapid developments in computer networks, mobile
applications and wireless computer networks. Open computer system networks do not have any
protection and privacy due to fraudulent attacks and the Internet attacks on computer networks or an
organization. Network security can be maintained through the firewalls and encryption software’s.
Many organizations developed intranet to remain connected with network for their business.
SOFTWARE REQUIREMENT INSPECTION AND DEFECT DETECTION TECHNIQUES
الباحثونRaghad I. Hussein ، .
المجلةJournal of Hunan University Natural Sciences
مختصر البحثoftware requirement is something which is required or we can say that it is something
wanted or needed from the software. In Webster’s dictionary requirements are basically, that is
difference between needed and wanted, are called requirements? Software requirement defects are
those which an inspector found in any aspect of the software during the inspection. There are many
different types of defect detection techniques some are based on reading, some on the language used
for requirement specifications and some are experimental replication, etc. When we talk about reading-
based techniques then we found that Perspective Based Reading (PBR) is one of the best techniques
for software inspection and to find defects and errors in it. PBR has been anticipated to advance the
efficiency of software requirement inspection
Performance of Differential CSK under Color Noise: A Comparison with CSK
الباحثونRaghad Imad Hussain ، Zahir Hussain
Salah-Albermany2
المجلةJournal of Engineering and Applied Sciences
مختصر البحثAbstract: In this research, we present a comprehensive study on the performance of chaotic communication
systems under Gaussian and color noise. We selected the most useful systems for short range communications:
Chaos Shift Key (CSK) and Differential Chaos Shift Key (DCSK) systems. Logistic map and tent map have
been used to generate Chaos in these systems. Color noise has been generated by filtering Gaussian noise via.
an FIR digital filter. Various spreading factors have been used. Although, DCSK outperforms CSK in
complexity, it is shown that CSK outperforms DCSK under Gaussian and color noise and various spreading
Factors (SF) in terms of Bit Error Rate (BER). In addition, it is shown that CSK is more secure than DCSK.
both systems have been simulated using MATLAB R2018a.
A new approach of cryptography using taylor series of logarithm function
الباحثونBashar Ahmed Sharba، Roaa Razaq Al-Khalidy &
Raghad I. Hussein
المجلةJournal of Discrete Mathematical Sciences and Cryptography
التاريخ2023-10-30
مختصر البحثThis study investigated a novel cryptographic approach involving the encryption of plaintext using the coefficients of a Taylor series for the logarithm function multiplied by its corresponding index. The decryption process utilized the Laplace transform of the logarithm function and its inverse. Through this methodology, several innovative mathematical encryptions and decryption formulas were derived. The study also includes a practical example to demonstrate the broader implications of the findings.
Graph-Based Architecture for Consumer-Based Image & Video Analysis in the Internet of Everything Using Advanced Learning Algorithms
الباحثونAmeer N. Onaizah، Raghad I. Hussein
المجلةIEEE Transactions on Consumer Electronics
التاريخ2025-03-21
مختصر البحثThe Internet of Everything (IoE) era has witnessed to a rapid increase in interconnected devices, leading to an exponential growth of image and video data. Efficient multimedia content analysis is crucial for applications such as surveillance systems and autonomous vehicles. This study proposes a novel hybrid architecture, fusing Convolutional Neural Networks (CNNs) with Graph Convolutional Networks (GCNs), for efficient multimedia analysis within the burgeoning Internet of Everything (IoE) landscape. By synergistically leveraging the strengths of both CNNs for local feature extraction and GCNs for capturing global data relationships, this approach aims to significantly enhance the accuracy and robustness of image and video analysis tasks in diverse IoE applications. Evaluated on challenging datasets like YouTube-8M and ImageNet, our approach demonstrates significant improvements in accuracy, loss, and computational efficiency compared to traditional methods. These results highlight the potential of this hybrid framework to address the demands of the IoE by enabling more efficient and accurate analysis of the ever-growing volume of image and video data