Evaluating M-Commerce Systems Success: Measurement and Validation of the DeLone and McLean Model of IS Success in Arabic Society (GCC Case Study)

This study focused on testing and verifying the 2003 DeLone and McLean Model (otherwise known as the Information System Success [ISS] Model), which represents the achievement of success in electronic systems, including smartphone commercial applications. Previous studies indicated that the DeLone and McLean Model has not been validated experimentally in the context of m-commerce, as there exist some differences between m-commerce and e-commerce. Moreover, the ISS model, for the m-commerce field, has been highly debated in terms of constructs such as perceived usefulness and IS use. These constructs create discrepancies in the acceptance of the ISS Model for the m-commerce field, especially in communities that have different technological requirements than other global communities. Previous studies focusing on the relationship between culture and electronic systems indicated that there are differences in the communities’ requirements that will directly affect the success of those electronic systems in Arabic communities. According to previous studies, there are verification shortages in the ISS model used to evaluate the success of m-commerce systems. The ISS model consists of six dimensions, which are system quality, information quality, service quality, user satisfaction, intention to use, and net benefit. The structural equation modelling technique was applied to the data for this model, which was collected by questionnaire. Responses were gathered from 803 actual users of online purchasing systems from three Arabic Gulf countries (171 from Qatar, 246 from the United Arab Emirates [UAE], and 386 from Saudi Arabia [KSA]). According to empirical evidence on the intention to use construct, which in turn is affected significantly by system quality and information quality constructs, reusing m-commerce applications is associated with quality of systems and information requirements in commercial applications. The results of this study on Arabic society will be beneficial for many future studies, such as ones determining the target characteristics of Arabic technology users and, especially, what features can be added to increase the level of satisfaction with m-commerce applications. This paper contributes several important implications to the field and discusses the additions and limitations that should be addressed in future studies

Security management of BYOD and cloud environment in Saudi Arabia

The increasing trend of Bring Your Own Device (BYOD) to work has led to a significant surge in the risks related to network security. This trend is very beneficial to employers and employees alike in any organisation. The wide infiltration of spyware, malware and similarly suspicious downloads into personal devices has forced the government to reconsider its policies regarding data security. The malicious programs get downloaded onto the personal devices without the user even realising. This could disastrously affect the individuals and the governments. In the case of such an event, the BYODs become risky as they can make unauthorised policy changes and leak sensitive data into the public domain. This type of privacy breach leads to a domino effect with major legal and financial implications, and a decreased productivity for the organisations and governments. This presents a huge challenge as the governments have to consider the user rights and privacy laws and also protect the networks from these attacks. In this study, the researchers have proposed a novel technical framework that could assist the Saudi government. This framework was designed after determining the challenges that were faced by the government, based on the citizen perspectives, to control all risks challenging the use of the BYODs. This framework decreased the number of system restrictions and enforced access control policies for BYODs and cloud environments. The preliminary results of this study were positive and indicated that the framework could decrease the problems related to access control

Image steganography technique based on bald eagle search optimal pixel selection with chaotic encryption

In the digital era, information security becomes a challenging process that can be mitigated by the utilization of cryptography and steganography techniques. Earlier studies on steganography have the risk of exposing confidential data by an anonymous user. For resolving, the limitations related to the existing algorithms, one of the efficient solutions in encryption-based steganography. Encryption techniques act as an important part in protect actual data from illegal access. This study focuses on the design of Bald Eagle Search Optimal Pixel Selection with Chaotic Encryption (BESOPS-CE) based image steganography technique. The presented BESOPS-CE technique effectively hides the secret image in its encrypted version to the cover image. For accomplishing this, the BESOPS-CE technique employs a BES for optimal pixel selection (OPS) procedure. Besides, chaotic encryption was executed for encrypting the secret image, which is then embedded to choose pixel points of the cover image. Finally, embedding and extraction processes are carried out. The inclusion of the encryption process aids in accomplishing an added layer of security. A comprehensive simulation study was used to report on the BESOPS-CE approach's increased performance, and the results are examined from many angles. A thorough comparative analysis revealed that the BESOPS-CE model outperformed more contemporary methods

Factors Affecting Information Security and the Implementation of Bring Your Own Device (BYOD) Programmes in the Kingdom of Saudi Arabia (KSA)

In recent years, desktop computer use has decreased while smartphone use has increased. This trend is also prevalent in the Middle East, particularly in the Kingdom of Saudi Arabia (KSA). Therefore, the Saudi government has prioritised overcoming the challenges that smartphone users face as smartphones are considered critical infrastructure. The high number of information security (InfoSec) breaches and concerns has prompted most government stakeholders to develop comprehensive policies and regulations that introduce inclusive InfoSec systems. This has, mostly, been motivated by a keenness to adopt digital transformations and increase productivity while spending efficiently. This present study used quantitative measures to assess user acceptance of bring your own device (BYOD) programmes and identifies the main factors affecting their adoption using the unified theory of acceptance and use of technology (UTAUT) model. Constructs, such as the perceived business (PT-Bs) and private threats (PT-Ps) as well as employer attractiveness (EA), were also added to the UTAUT model to provide the public, private, and non-profit sectors with an acceptable method of adopting BYOD programmes. The factors affecting the adoption of BYOD programmes by the studied sectors of the KSA were derived from the responses of 857 participants

Factors Affecting Information Security and the Implementation of Bring Your Own Device (BYOD) Programmes in the Kingdom of Saudi Arabia (KSA)

In recent years, desktop computer use has decreased while smartphone use has increased. This trend is also prevalent in the Middle East, particularly in the Kingdom of Saudi Arabia (KSA). Therefore, the Saudi government has prioritised overcoming the challenges that smartphone users face as smartphones are considered critical infrastructure. The high number of information security (InfoSec) breaches and concerns has prompted most government stakeholders to develop comprehensive policies and regulations that introduce inclusive InfoSec systems. This has, mostly, been motivated by a keenness to adopt digital transformations and increase productivity while spending efficiently. This present study used quantitative measures to assess user acceptance of bring your own device (BYOD) programmes and identifies the main factors affecting their adoption using the unified theory of acceptance and use of technology (UTAUT) model. Constructs, such as the perceived business (PT-Bs) and private threats (PT-Ps) as well as employer attractiveness (EA), were also added to the UTAUT model to provide the public, private, and non-profit sectors with an acceptable method of adopting BYOD programmes. The factors affecting the adoption of BYOD programmes by the studied sectors of the KSA were derived from the responses of 857 participants

Classification and Prediction of Significant Cyber Incidents (SCI) Using Data Mining and Machine Learning (DM-ML)

The rapid growth in technology and several IoT devices make cyberspace unsecure and eventually lead to Significant Cyber Incidents (SCI). Cyber Security is a technique that protects systems over the internet from SCI. Data Mining and Machine Learning (DM-ML) play an important role in Cyber Security in the prediction, prevention, and detection of SCI. This study sheds light on the importance of Cyber Security as well as the impact of COVID-19 on cyber security. The dataset (SCI as per the report of the Center for Strategic and International Studies (CSIS)) is divided into two subsets (pre-pandemic SCI and post-pandemic SCI). Data Mining (DM) techniques are used for feature extraction and well know ML classifiers such as Naïve Bayes (NB), Support Vector Machine (SVM), Logistic Regression (LR) and Random Forest (RF) for classification. A centralized classifier approach is used to maintain a single centralized dataset by taking inputs from six continents of the world. The results of the pre-pandemic and post-pandemic datasets are compared and finally conclude this paper with better accuracy and the prediction of which type of SCI can occur in which part of the world. It is concluded that SVM and RF are much better classifiers than others and Asia is predicted to be the most affected continent by SCI

Recognizing Brain Tumors Using Adaptive Noise Filtering and Statistical Features

The human brain, primarily composed of white blood cells, is centered on the neurological system. Incorrectly positioned cells in the immune system, blood vessels, endocrine, glial, axon, and other cancer-causing tissues, can assemble to create a brain tumor. It is currently impossible to find cancer physically and make a diagnosis. The tumor can be found and recognized using the MRI-programmed division method. It takes a powerful segmentation technique to produce accurate output. This study examines a brain MRI scan and uses a technique to obtain a more precise image of the tumor-affected area. The critical aspects of the proposed method are the utilization of noisy MRI brain images, anisotropic noise removal filtering, segmentation with an SVM classifier, and isolation of the adjacent region from the normal morphological processes. Accurate brain MRI imaging is the primary goal of this strategy. The divided section of the cancer is placed on the actual image of a particular culture, but that is by no means the last step. The tumor is located by categorizing the pixel brightness in the filtered image. According to test findings, the SVM could partition data with 98% accuracy