Open Access Original Research Article

The paper described the least square regression line method has been improved as a novel method for tendency discrimination on future stock price. A new method is established, which is obtained from one dataset of known strain variables. The result is been calculated from 10 strain variables consist of one dataset through a few unique managing approaches to calculate out four different tendencies, and encode them. Those codes are added into the least square regression line method by the application software of MATLAB to develop a diagnostic method, which can predict the tendency by the text and graphics. The new method predicts trends more clearly and easily than the least square regression line method. In this paper, firstly establish any of the four standard graphics that can be generated from known data. Finally, it is verified by historical data and the graphics are compared. The result is consistent with both text recognition and graphics trend. The new novel method of the least square regression line was as accurate and alike as we had expected. So that it is enough to prove that it is not only easy to understand but also easy to operate for discriminating the trend of stock price in future.

Open Access Review Article

A State of Art for Smart Gateways Issues and Modification

Lozan M. Abdulrahman, Subhi R. M. Zeebaree, Shakir Fattah Kak, Mohammed A. M. Sadeeq, Adel AL-Zebari, Baraa Wasfi Salim, Karzan Hussein Sharif

Asian Journal of Research in Computer Science, Volume 7, Issue 4, Page 1-13
DOI: 10.9734/ajrcos/2021/v7i430184

The Internet of Things (IoT) is a collection of objects such as sensors, actuators, and processors, which interconnected within a specific network to perform a task collaboratively. The IoT is one of the prevalent technologies, which has developed dramatically in recent years. Its reputation derives from its relevance and role in employing things in the best way, starting with smartphones that opened new horizons in control technologies and later developing new ideas regarding cloud-computing services. A smart gateway plays an essential role in the IoT applications that responsible for enabling communication between the network layer and the ubiquitous sensors network layer. IoT gateways are methods that operate with influential data centers as a point of communication between lower-end users. IoT gateways connect the heterogeneous devices in use and carry out many tasks to accomplish the computing mission. This work searches how IoT gateway's function and how they interact. In particular, it lists interface issues related to IoT gateways. In this paper, we research IoT and Smart Gateways and address Smart Gateways problems and computing techniques to promote IoT programs' stable transition to the Smart Gateway.

Open Access Review Article

A Detailed Analysis of Benchmark Datasets for Network Intrusion Detection System

Mossa Ghurab, Ghaleb Gaphari, Faisal Alshami, Reem Alshamy, Suad Othman

Asian Journal of Research in Computer Science, Volume 7, Issue 4, Page 14-33
DOI: 10.9734/ajrcos/2021/v7i430185

The enormous increase in the use of the Internet in daily life has provided an opportunity for the intruder attempt to compromise the security principles of availability, confidentiality, and integrity. As a result, organizations are working to increase the level of security by using attack detection techniques such as Network Intrusion Detection System (NIDS), which monitors and analyzes network flow and attacks detection. There are a lot of researches proposed to develop the NIDS and depend on the dataset for the evaluation. Datasets allow evaluating the ability in detecting intrusion behavior. This paper introduces a detailed analysis of benchmark and recent datasets for NIDS. Specifically, we describe eight well-known datasets that include: KDD99, NSL-KDD, KYOTO 2006+, ISCX2012, UNSW-NB 15, CIDDS-001, CICIDS2017, and CSE-CIC-IDS2018. For each dataset, we provide a detailed analysis of its instances, features, classes, and the nature of the features. The main objective of this paper is to offer overviews of the datasets are available for the NIDS and what each dataset is comprised of. Furthermore, some recommendations were made to use network-based datasets.

Open Access Review Article

A Survey of Optical Fiber Communications: Challenges and Processing Time Influences

Fairoz Q. Kareem, Subhi R. M. Zeebaree, Hivi Ismat Dino, Mohammed A. M.Sadeeq, Zryan Najat Rashid, Dathar Abas Hasan, Karzan Hussein Sharif

Asian Journal of Research in Computer Science, Volume 7, Issue 4, Page 48-58
DOI: 10.9734/ajrcos/2021/v7i430188

Optical fibers are utilized widely for data transmission systems because of their capacity to carry extensive information and dielectric nature. Network architectures utilizing multiple wavelengths per optical fiber are used in central, metropolitan, or broad‐area applications to link thousands of users with a vast range of transmission speeds and capacities. A powerful feature of an optical communication link is sending several wavelengths through the 1300‐to‐1600‐ nm range of a fibre simultaneously. The technology of integrating several wavelengths onto a similar fiber is called wavelength division multiplexing (WDM). The principle of WDM utilized in concurrence with optical amplifiers has an outcome in communication links that permit rapid communications among users in the world's countries. This paper presents an overview of the challenges of fibre optic communication. This paper offers an outline of the areas to be the most relevant for the future advancement of optical communications. The invention of integrated optics and modern optical fibers takes place in the field of optical equipment and components.

Open Access Review Article

Efficiency of Malware Detection in Android System: A Survey

Maria A. Omer, Subhi R. M. Zeebaree, Mohammed A. M. Sadeeq, Baraa Wasfi Salim, Sanaa x Mohsin, Zryan Najat Rashid, Lailan M. Haji

Asian Journal of Research in Computer Science, Volume 7, Issue 4, Page 59-69
DOI: 10.9734/ajrcos/2021/v7i430189

Smart phones are becoming essential in our lives, and Android is one of the most popular operating systems. Android OS is wide-ranging in the mobile industry today because of its open-source architecture. It is a wide variety of applications and basic features. App users tend to trust Android OS to secure data, but it has been shown that Android is more vulnerable and unstable. Identification of Android OS malware has become an emerging research subject of concern. This paper aims to analyze the various characteristics involved in malware detection. It also addresses malware detection methods. The current detection mechanism utilizes algorithms such as Bayesian algorithm, Ada grad algorithm, Naïve Bayes algorithm, Hybrid algorithm, and other algorithms for machine learning to train the sets and find the malware.