• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.8
• /
• pp.4076-4092
• /
• 2019

Nowadays, most users access internet through mobile applications. The common way to authenticate users through websites forms is using passwords; while they are efficient procedures, they are subject to guessed or forgotten and many other problems. Additional multi modal authentication procedures are needed to improve the security. Behavioral authentication is a way to authenticate people based on their typing behavior. It is used as a second factor authentication technique beside the passwords that will strength the authentication effectively. Keystroke dynamic rhythm is one of these behavioral authentication methods. Keystroke dynamics relies on a combination of features that are extracted and processed from typing behavior of users on the touched screen and smart mobile users. This Research presents a novel analysis in the keystroke dynamic authentication field using two features categories: timing and no timing combined features. The proposed model achieved lower error rate of false acceptance rate with 0.1%, false rejection rate with 0.8%, and equal error rate with 0.45%. A comparison in the performance measures is also given for multiple datasets collected in purpose to this research.

• International Journal of Computer Science & Network Security
• /
• v.21 no.9
• /
• pp.275-280
• /
• 2021

With the development of communication networks, the processes of exchanging and transmitting information rapidly developed. As millions of images are sent via social media every day, also wireless sensor networks are now used in all applications to capture images such as those used in traffic lights, roads and malls. Therefore, there is a need to reduce the size of these images while maintaining an acceptable degree of quality. In this paper, we use Python software to apply K-mean Clustering algorithm to compress RGB images. The PSNR, MSE, and SSIM are utilized to measure the image quality after image compression. The results of compression reduced the image size to nearly half the size of the original images using k = 64. In the SSIM measure, the higher the K, the greater the similarity between the two images which is a good indicator to a significant reduction in image size. Our proposed compression technique powered by the K-Mean clustering algorithm is useful for compressing images and reducing the size of images.

• International Journal of Computer Science & Network Security
• /
• v.21 no.8
• /
• pp.167-176
• /
• 2021

This is the world of computer science and innovations. In this modern era, every day new apps, webs and software are being introduced. As well as new apps and software are being introduced, similarly threats and vulnerable security matters are also increasing. Web apps are software that can be used by customers for numerous useful tasks, and because of the developer experience of good programming standards, web applications that can be used by an attacker also have multiple sides. Web applications Security is expected to protect the content of critical web and to ensure secure data transmission. Application safety must therefore be enforced across all infrastructure, including the web application itself, that supports the web applications. Many organizations currently have a type of web application protection scheme or attempt to build/develop, but the bulk of these schemes are incapable of generating value consistently and effectively, and therefore do not improve developers' attitude in building/designing stable Web applications. This article aims to analyze the attacks on the website and address security scanners of web applications to help us resolve web application security challenges.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.4
• /
• pp.673-685
• /
• 2021

This study aims to determine theoretically the best workers layoff/training strategy that entrepreneurs should apply to manage the COVID-19 crisis successfully. It also examines the impacts of the Saudi government's emergency measures on firm performance. The paper develops a theoretical framework in which the optimal control technics is applied to model the entrepreneur's hiring, layoff, and training behaviors. The results show that, during the current COVID-19 pandemic, the entrepreneur should first lay off the less productive workers to reduce labor costs. As more and more inefficient workers quit and profit increases, the entrepreneur starts expanding his activity and training workers. In the long run, only the training activity allows the firm efficiency to grow at a constant rate. This finding suggests that the key to long-run economic recovery in Saudi Arabia will rely on training, innovation, and adaptability to the new digital environment. The paper also shows that the Saudi government initiative of covering 60% of salaries for the small- and medium-sized entrepreneurs during the COVID-19 pandemic will enhance training activities in small- and medium-sized enterprises and improve their efficiency in both the short and long run. This policy will also prevent Saudi entrepreneurs from laying off half of their staff.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.3
• /
• pp.31-38
• /
• 2021

The study investigates the diversification behavior of Islamic stocks against US financial uncertainty. Considering limitations found in the literature, a comprehensive index of financial uncertainty (FU) is used, developed by Jurado, Ludvigson, and Ng (2015). The empirical analysis uses monthly data from four Islamic markets - Saudi Arabia, Malaysia, Indonesia, and Turkey - for the period from January 2010 to September 2019. Results of the bivariate EGARCH models show that Islamic stocks can be used for diversification purpose against the financial uncertainty of the US because the volatility of US uncertainty does not propagate in the Islamic stock markets. Moreover, findings show that the spillover effect of financial uncertainty varies with the FU forecast horizon. The spillover effect of FU increases with an increase in the FU forecast horizon and becomes significant over 3-month and 12-month periods in the case of Saudi Arabia. The current volatility of Islamic stock returns is independent of the size of shocks in past volatility. The leverage effect and asymmetry have been found in Saudi Arabia and Malaysia. The findings validate the arguments of the literature that Islamic markets are resilient facing uncertainties and perform well during crisis periods. The findings are important for investors in making better portfolio decisions.

• International Journal of Computer Science & Network Security
• /
• v.21 no.1
• /
• pp.184-191
• /
• 2021

The amount of information and data in the digital era is increasing tremendously. Continuous online connectivity is generating a massive amount of data that needs to store in computers and be made available as and when required. Cloud computing technology plays a pivotal role in this league. Cloud computing is a term that refers to computer systems, resources and online services that aim to protect and manage data in an effective, more efficient and easy way. Cloud computing is an important standard for maintaining the integrity and security of sensitive data and information for organizations and individuals. Cloud security is one of the most important challenges that the security of the entire cloud system depends on. Thus, the present study reviews the security challenges that exist in cloud computing, including attacks that negatively affect cloud resources. The study also addresses the most serious threats that affect cloud security. We also reviewed several studies, specifically those from 2017-20, that cited effective mechanisms to protect authentication, availability and connection security in the cloud. The present analysis aims to provide solutions to the problems and causes of cloud computing security system violations, which can be used now and developed in the future.

• International Journal of Computer Science & Network Security
• /
• v.21 no.3
• /
• pp.103-111
• /
• 2021

Obesity affects individuals of all gender and ages worldwide; consequently, several studies have performed great works to define factors causing it. This study develops an effective method to trace obesity levels based on supervised data mining techniques such as Random Forest and Multi-Layer Perception (MLP), so as to tackle this universal epidemic. Notably, the dataset was from countries like Mexico, Peru, and Colombia in the 14- 61year age group, with varying eating habits and physical conditions. The data includes 2111 instances and 17 attributes labelled using NObesity, which facilitates categorization of data using Overweight Levels l I and II, Insufficient Weight, Normal Weight, as well as Obesity Type I to III. This study found that the highest accuracy was achieved by Random Forest algorithm in comparison to the MLP algorithm, with an overall classification rate of 96.7%.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.2
• /
• pp.747-757
• /
• 2021

The primary purpose of the study is to investigate the volatility spillover from financial uncertainty (FU) of the United States (US) to the stock markets of SAARC member countries including India, Sri-Lanka, Pakistan, and Bangladesh. The empirical literature overlooked SAARC countries and the FU index. Based on the estimation method, the data of FU is available for three different forecast horizons including 1-month, 3-months, and 12-months. For empirical analysis, monthly data is used from February 2013 to September 2019. EGARCH model is employed to investigate the volatility spillover effects. The findings of the study show that the spillover effect of FU varies with the forecast horizon. The FU with a higher forecast horizon has a significant spillover effect on more countries. The spillover effect of US financial uncertainty is negative in most of the SAARC countries. Bangladesh stock market is influenced by FU with all three forecast horizons whereas the volatility of the Pakistan stock market is not influenced by FU with any forecast horizon. The findings are consistent with the concept of "limited trade openness" in the financial markets of emerging economies. The emerging economies avoid financial market openness to minimize the risk of spillover of other countries.

• Structural Engineering and Mechanics
• /
• v.83 no.1
• /
• pp.45-51
• /
• 2022

The need to account for accidental torsion in seismic design is no longer debatable, however, the seismic codes' requirement for accidental eccentricity has recently faced criticism. In order to get as close to real conditions as possible, this study investigated the impact of accidental torsion in symmetric RC multistory buildings caused by one of its many sources, the torsional earthquake component, and compared the results to those obtained by using the accidental eccentricity recommended by the codes (shifting the center of mass). To cover a wide range of frequencies and site conditions, two types of torsion seismic components were used: a recorded torsion accelerogram and five others generated using translation accelerograms. The main parameters that govern seismic responses, such as the number of stories (to account for the influence of all modes of vibration) and the frequency ratio (Ω) variation, were studied in terms of inter-story drift and displacement responses, as well as torsional moment. The results show that the eccentricity ratio of 5% required by most codes for accidental torsion should be reexamined and that it is prudent for computer analysis to use the static moment approach to implement the accidental eccentricity while waiting for new seismic code recommendations on the subject.

• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.4
• /
• pp.399-408
• /
• 2022

Corporate governance and innovation have been a hot topic in recent boardroom talks, whether in the trade or manufacturing industries. Governance innovations are highly significant for the survival of the motor vehicle industry like Honda, Nissan, New General Motors, and Toyota. The study chooses the motor vehicle industry which crosses the age of a century and sufficient corroborative support exists with the perspective of distinctive objectives. Using the population of all the automobile companies listed on the Pakistan stock exchange (PSX), we distill automobile companies to evaluate the firm performance using the panel data regression approach. The results show that there is a significant relationship between gender diversity, audit committees, and firm performance. Further, board size also has a positive impact on firm performance. We identify that the governance mechanism of firms found in default of the frequency of audit committee meetings. By considering results, only limited knowledge of finance directors and also very few numbers of female directors are on the board. Empirical findings of this work might be useful for policymakers in attempting to draft a corporate governance framework better able to monitor the financial performance of firms through female directors and also serve as a catalyst for the regulators of electric vehicles.