12 research outputs found
Users' Information Security Awareness of Home Closed-Circuit Television Surveillance
No full textClosed-circuit television (CCTV) surveillance cameras are widely used in public and private areas around the world. It is primarily used for tracking individuals and preventing criminal activities. It is necessary to balance the benefits of video surveillance and the risks it poses to individuals' right to privacy. The existing studies raised privacy issues of installing CCTV in public places. However, there is a lack of studies investigating users’ awareness of information security and privacy limitations in installing CCTV in private places. Thus, in this study, the author evaluated users' information security awareness of the value of CCTV and other forms of video surveillance. In-person interviews were conducted in Riyadh province, Kingdom of Saudi Arabia. A total of 77 individuals responded to the interview. A qualitative analysis was conducted to evaluate the participants’ perception of CCTV usage. The outcome of the analysis revealed four themes: Privacy invasion, privacy awareness, dilemmas in implementing security, and preventive measures. The findings revealed that the participants required strict privacy policies for installing CCTV video monitoring systems in private areas. In addition, they understood that CCTV is effectively reducing the fear of crime. The research contributes to understanding users' general awareness of information security and offers the necessary steps to protect the user's privacy in a CCTV surveillance environment. In addition, a data-sharing framework is recommended to share the data in a secure environment. Furthermore, researchers can utilize the study findings in conducting further similar investigative studies
National ID Cards
No full textAbstract The September 11 terrorist attacks changed the world, governments and many people became more and more concerned about their security. A number of countries have considered or are considering again their approach to a form of ID card. Despite the support for ID cards, there are growing fears about the possible loss of privacy, freedom, and that the new technology could increase police power more than it should be. The main idea of this paper is to look at the main advantages and disadvantages of National ID cards, security properties of resident ID cards, possible threat and security features. Moreover, a number of alternative proposes to the National ID cards is mentioned
Adopting Automated Penetration Testing Tools: A Cost-Effective Approach to Enhancing Cybersecurity in Small Organizations
No full textModern society is heavily reliant upon the internet. Accordingly, it is vital to ensure that the data transmitted over the internet is safe. Several tools have been created for cybersecurity experts and organizations to test the security levels of organizational networks and websites. However, due to financial constraints, small organizations need to pay closer attention to managing data with limited resources. This study explores the role of automated penetration testing tools in providing small organizations with an effective and affordable data security system. This study employs a case-study approach using multiple data-gathering methods in a charitable organization. More specifically, data was collected using interviews and experiments evaluating penetration testing tools. The results revealed that cost-effective automated penetration testing tools could safeguard small organizations from cybersecurity threats. The penetration testing tools determined that the organization’s website had various vulnerabilities. The Nessus tool discovered no fewer than 37 vulnerabilities on the website application. The ZAP testing tool showed that the website application was critically failing, leading to the accumulation of vulnerabilities. The system had 3 medium-, 12 low-, and 4-informational-risk vulnerabilities. Through the evaluation of open ports, the NMAP tool identified various vulnerabilities. These findings have important implications for small organizations. First, automated penetration testing tools can be easily conducted by small organizations to safeguard their cybersecurity without obtaining costly expert help. Second, it is recommended in the light of the findings that automated penetration testing tools be used in multiple combinations as different tools have unique contributions to cybersecurity
Evaluating readability as a factor in information security policies
No full textThis thesis was previously held under moratorium from 26/11/19 to 26/11/21Policies should be treated as rules or principles that individuals can readily comprehend and follow as a pre-requisite to any organisational requirement to obey and enact regulations. This dissertation attempts to highlight one of the important factors to consider before issuing any policy that staff members are required to follow. Presently, there is no ready mechanism for estimating the likely efficacy of such policies across an organisation. One factor that has a plausible impact upon the comprehensibility of policies is their readability. Researchers have designed a number of software readability metrics that evaluate how difficult a passage is to comprehend; yet, little is known about the impact of readability on the interpretation of information security policies and whether analysis of readability may prove to be a useful insight.This thesis describes the first study to investigate the feasibility of applying readability metrics as an indicator of policy comprehensibility through a mixed methods approach, with the formulation and implementation of a seven phase sequential exploratory fully mixed methods design. Each one was established in light of the outcomes from the previous phase. The methodological approach of this research study is one of the distinguishing characteristics reported in the thesis, which was as follows:* eight policies were selected (from a combination of academia and industry sector institutes);* specialists were requested their insights on key policy elements;* focus group interviews were conducted;* comprehension tests were developed (Cloze tests);* a pilot study of comprehension tests was organised (preceded by a small-scale test);* a main study of comprehension tests was performed with 600 participants and reduce that for validation to 396;* a comparison was made of comprehension results against readability metrics.The results reveal that the traditional readability metrics are ineffective in predicting human estimation. Nevertheless, readability, as measured using a bespoke readability metric, may yield useful insight upon the likely difficulty that end-users may face in comprehending a written text. Thereby, our study aims to provide an effective approach to enhancing the comprehensibility of information security policies and afford a facility for future research in this area.The research contributes to our understanding of readability in general and offering an optimal technique to measure the readability in particular. We recommend immediate corrective actions to enhance the ease of comprehension for information security policies. In part, this may reduce instances where users avoid fully reading the information security policies, and may also increase the likelihood of user compliance. We suggest that the application of appropriately selected readability assessment may assist policy makers to test their draft policies for ease of comprehension before policy release. Indeed, there may be grounds for a readability compliance test that future information security policies must satisfy.Policies should be treated as rules or principles that individuals can readily comprehend and follow as a pre-requisite to any organisational requirement to obey and enact regulations. This dissertation attempts to highlight one of the important factors to consider before issuing any policy that staff members are required to follow. Presently, there is no ready mechanism for estimating the likely efficacy of such policies across an organisation. One factor that has a plausible impact upon the comprehensibility of policies is their readability. Researchers have designed a number of software readability metrics that evaluate how difficult a passage is to comprehend; yet, little is known about the impact of readability on the interpretation of information security policies and whether analysis of readability may prove to be a useful insight.This thesis describes the first study to investigate the feasibility of applying readability metrics as an indicator of policy comprehensibility through a mixed methods approach, with the formulation and implementation of a seven phase sequential exploratory fully mixed methods design. Each one was established in light of the outcomes from the previous phase. The methodological approach of this research study is one of the distinguishing characteristics reported in the thesis, which was as follows:* eight policies were selected (from a combination of academia and industry sector institutes);* specialists were requested their insights on key policy elements;* focus group interviews were conducted;* comprehension tests were developed (Cloze tests);* a pilot study of comprehension tests was organised (preceded by a small-scale test);* a main study of comprehension tests was performed with 600 participants and reduce that for validation to 396;* a comparison was made of comprehension results against readability metrics.The results reveal that the traditional readability metrics are ineffective in predicting human estimation. Nevertheless, readability, as measured using a bespoke readability metric, may yield useful insight upon the likely difficulty that end-users may face in comprehending a written text. Thereby, our study aims to provide an effective approach to enhancing the comprehensibility of information security policies and afford a facility for future research in this area.The research contributes to our understanding of readability in general and offering an optimal technique to measure the readability in particular. We recommend immediate corrective actions to enhance the ease of comprehension for information security policies. In part, this may reduce instances where users avoid fully reading the information security policies, and may also increase the likelihood of user compliance. We suggest that the application of appropriately selected readability assessment may assist policy makers to test their draft policies for ease of comprehension before policy release. Indeed, there may be grounds for a readability compliance test that future information security policies must satisfy
Evaluating readability as a factor in information security policies
No full textResearchers have designed a number of software readability metrics that evaluate how difficult a passage is to comprehend; yet, little is known about the impact of readability on the interpretation of information security policies (ISPs) and whether experiment of readability may prove to be a useful factor. This paper examines and compares eight ISP documents on nine mechanical readability formula results with outcomes from a human-based comprehension test. The primary focus is to identify if we might rely on a software readability measure for assessing the difficulty of a text document in the domain of Information Security Policies. Our results reveal that traditional readability metrics are ineffective in predicting the human estimation. Nevertheless, readability, as measured using a bespoke readability metric, may yield useful insight upon the likely difficulty that end-users face in comprehending an ISP document. Thereby, our study aims to provide a means to enhance the comprehensibility of ISPs
Readability as a basis for information security policy assessment
No full textMost organisations now impose information security policies (ISPs) or 'conditions of use' agreements upon their employees. The need to ensure that employees are informed and aware of their obligations toward information security is apparent. Less apparent is the correlation between the provision of such policies and their compliance. In this paper, we report our research into the factors that determine the efficacy of information security policies (ISPs). Policies should comprise rules or principles that users can easily understand and follow. Presently, there is no ready mechanism for estimating the likely efficacy of such policies across an organisation. One factor that has a plausible impact upon the comprehensibility of policies is their readability. The present study investigates the effectiveness of applying readability metrics as an indicator of policy comprehensibility. Results from a preliminary study reveal variations in the comprehension test results attributable to the difficulty of the examined policies. The pilot study shows some correlation between the software readability formula results and human comprehension test results and supports our view that readability has an impact upon understanding ISPs. These findings have important implications for users’ compliance with information security policies and suggest that the application of suitably selected readability metrics may allow policy designers to evaluate their draft policies for ease of comprehension prior to policy release. Indeed, there may be grounds for a readability compliance test that future ISPs must satisfy
A comprehensive survey of techniques for developing an Arabic question answering system
No full textThe question-answering system (QAS) aims to produce a response to a query using information from a text corpus. Arabic is a complex language. However, it has more than 450 million native speakers across the globe. The Saudi Arabian government encourages organizations to automate their routine activities to provide adequate services to their stakeholders. The performance of current Arabic QASs is limited to the specific domain. An effective QAS retrieves relevant responses from structured and unstructured data based on the user query. Many QAS studies categorized QASs according to factors, including user queries, dataset characteristics, and the nature of the responses. A more comprehensive examination of QASs is required to improve the QAS development according to the present QAS requirements. The current literature presents the features and classifications of the Arabic QAS. There is a lack of studies to report the techniques of Arabic QAS development. Thus, this study suggests a systematic literature review of strategies for developing Arabic QAS. A total of 617 articles were collected, and 40 papers were included in the proposed review. The outcome reveals the importance of the dataset and the deep learning techniques used to improve the performance of the QAS. The existing systems depend on supervised learning methods that lower QAS performance. In addition, the recent development of machine learning techniques encourages researchers to develop unsupervised QAS
Developing an Image-Based Dyslexia Detection Model Using the Deep Learning Technique
No full textDyslexia is a neurological disorder. Across the globe, children are primarily affected by dyslexia. Deep learning (DL) approaches have been applied in dyslexia detection (DD). However, these approaches demand substantial computational resources to generate a meaningful outcome. In addition, healthcare centers face challenges in interpreting the DL-based DD models. Thus, this study aimed to build an effective DD model to support physicians in detecting dyslexic individuals using functional magnetic resonance imaging (FMRI). The authors applied extensive image preprocessing techniques to overcome the FMRI image complexities. They built a convolutional neural network model for extracting the key features from the FMRI images using the weights of the ShuffleNet V2 model. Random forest is ensembled to classify the extracted features. The authors evaluated the proposed model using a real-time dataset comprising 606 multidimensional FMRI images. The findings revealed that the recommended DD model outperformed the existing DD models. The proposed DD model achieved an accuracy of 98.9 and an F1-Score of 99.0. In addition, the proposed model generated an outcome with a minimum loss of 1.2, a standard deviation of 0.0002, and a confidence interval range between 98.2 and 98.7. The experimental outcome supported the effectiveness of the proposed model in detecting dyslexic individuals with few computational resources. The proposed model can be extended using graph convolutional networks for classifying complex images with optimal prediction accuracy
Deep Learning-Based Model for Detecting Dyslexia Using Handwritten Images
No full textAcross the globe, dyslexia and dysgraphia are two frequent learning disorders identified in classrooms. This condition is characterized by difficulties in age-appropriate reading without any sociocultural restrictions. Children with this disorder have difficulty recognizing word and letter patterns. Early identification of dyslexic children (DC) is crucial for providing them with the most effective educational opportunities. Researchers proposed a deep learning-based dyslexia detection system (DDS). However, there is a demand for a practical, lightweight framework for identifying DC. Thus, the proposed study intends to build a framework for detecting dyslexia. The proposed framework encompasses image processing, feature extraction, and classification models. The image-processing model enhances the image quality using contrast-limited adaptive histogram equalization and resizes the images into 512 × 512 pixels. For feature extraction, the authors employ you only look once V7 to extract features in a limited time. In addition, the MobileNet V2 with single shot detection lite is used to classify the handwritten images into normal and abnormal classes, respectively. The authors utilized the publicly available dyslexia dataset for performance evaluation. The test set contains 19,557 normal and 17,882 reversal (abnormal) images. The baseline models are employed for comparative analysis. The experimental study revealed that the proposed framework outperformed the baseline models by achieving exceptional precision, recall, F1-Score, accuracy, and mean average precision of 97.9, 97.3, 97.6, 99.2, and 97.6, respectively. In addition, the proposed model obtained an exceptional mean intersection over union of 88.6. It can be implemented in educational institutions and healthcare centers. In the future, the authors can extend the research to build an integrated framework using biomedical images
