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Exploring High-Power Distance Among Other Variables in Information Security Policy Compliance
Get PDFInformation security threat is one of the significant challenges organizations must deal with, and one component of that challenge is information security policy compliance. Data breaches sometimes happen because employees do not adhere to information security policies. The purpose of the exploratory study was to determine if power distance had a role in information security policy compliance; power distance is the understanding that power distribution is unequal. The research required survey data collected from a high-power distance index country, Nigeria. The Nigerian working class was the population sample; a model was developed based on compliance, descriptive norms, moral beliefs, normative beliefs, power distance, self-efficacy, sanctions as the independent variables, and intent to comply as the dependent variable. General deterrence theory, protection motivation theory, rational choice theory, theory of reasoned action, and theory of planned behavior were the applicable theories. The analysis was performed using Partial least squares-structural equation modeling, and the preferred software was SmartPLS version 3.3.3. The significance of power distance playing a role in information security compliance would mean that organizations could cultivate the idea of using employees with the cultural characteristic as influencers and could incorporate power distance into the training program. The results showed that power distance was significant in information security policy compliance
Cybersecurity Education for Non-Technical Learners
Get PDFToday’s world is increasingly reliant on technology for school, work, entertainment, and general home use. Many jobs today could not be performed without the use of computer systems or other technology. As lives become intertwined with technology, everyone will inevitably encounter malicious, vulnerable, or privacy-compromising devices or services. Unfortunately, knowledge of how to deal with these cybersecurity and privacy issues is not something that falls within the domain of common knowledge for the everyday person. Additionally, there is a lack of work being done to understand the educational needs of various groups within the general public and educate them. This quantitative survey research study seeks to add to this knowledge base by looking to better understand what university students at the Southeastern Louisiana University comprehend regarding cybersecurity and privacy protection best practices and associated standard technologies. Furthermore, this work will examine whether the student’s academic major has any effect on their responses. This research examines the responses from university students to a survey using nontechnical questions in cybersecurity, privacy protection, and some standard, related technologies. The combination of answers to these questions and the major given by the student provides conclusions of what is common knowledge for the university population and if their major had any effect on their ability to answer the questions correctly. Based on 810 responses to the survey, it can be concluded that there are participants who are unsure or incorrect in their knowledge of a given idea for any of the examined subjects. Additionally, majoring in computer science or information technology results in students having an increased likelihood to answer correctly. Students in these majors do show a lower rate of providing an incorrect answer, but it does not eliminate the deficiencies. The research shows that education for all students in cybersecurity, privacy protection, and related technologies is needed. Finally, while some solutions are presented, additional research is required to educate them further
Identity Sharing and Adaptive Personalization Influencing Online Repurchases
No full textAdaptive personalization systems are becoming common in online retail. These systems use dynamically generated data and advanced data analytic techniques to infer customer preferences and recommend products or services best suited to a customer’s tastes. However, the adaptive personalization system’s ability to continue delivering valuable personalized content relies heavily on return customers’ willingness to continue sharing their identity information. By applying identity theory and the action-cognitive processing-decision model, cognitive and behavioral processes are theorized whereby customers who willingly share identity information favorably assess the value of product or service recommendations provided by adaptive personalization systems relative to their self-identity needs. The effects of willingness to share identity information and perceived personalization value on repurchase intention are examined. The results empirically demonstrate that a willingness to share identity information increases repurchase intention; further, this relationship is partially mediated by the perceived value of adaptive personalization
Applications of Deep Learning Augmented Systems for Covid-19 Predictions- A Literature Review
Get PDFCovid-19 Diagnosis needs new Information Systems technologies as Deep learning methods, especially in medical image screening. We aim to review the applications of deep learning augmented systems in Covid-19 predictions with the help of a large literature collection from four major databases IEEE explore, ACM, Web of Science, and PubMed. We have identified three major research themes from the current literature, Image Classification, Image segmentation, and evaluation methods for DL models. Among the DL techniques, Transfer Learning is identified as the most popular method for different tasks on Chest X-rays and CT scans. Pre-trained models such as ResNet, VGG, DenseNet, and Unet are widely used in the covid-19 diagnosis. While these models are pre-trained on natural images, a Chest X-ray image pre-trained model CheXnet is gaining popularity in Covid-19 image tasks helping in improving accuracies of classifications
Fake News Detection on the Web: An LSTM-based Approach
Get PDFThe acceptance and popularity of social media platforms for the dispersion and proliferation of news articles have led to the spread of questionable and untrusted information (in part) due to the ease by which misleading content can be created and shared among the communities. While prior research has attempted to automatically classify news articles and tweets as credible and non-credible. In this work, we complement such research by proposing an approach that utilizes the amalgamation of natural language processing (NLP) and deep learning techniques such as Long Short-Term Memory (LSTM). We used publicly available datasets that contain labeled news articles and tweets to validate our model’s effectiveness. The results demonstrate that the proposed model works well for both long sequence news articles and short-sequence texts such as tweets
Deconstructing Compulsory Realpolitik in Cultural Studies: An Interview with Alexa Alice Joubin
Get PDFHow might we de-colonize hegemonic knowledge production about East Asia and its relationship with the West? This interview with Alexa Alice Joubin draws on new perspectives on cultural exchange in her book, Shakespeare and East Asia (Oxford University Press, 2021), which promotes treatment of Asian performing arts as original epistemologies rather than footnotes to the white, Western canon, and theory. We also present her latest thinking on multidisciplinarity. Her work, including Race (Routledge, 2019), has sought to deconstruct what she calls “compulsory realpolitik”—the conviction that the best way to understand non-Western cultures is by interpreting their engagement with pragmatic politics. In tandem with Anglo-Eurocentrism, she argues, compulsory realpolitik leads to the habitual privileging of the nation-state as a unit to organize knowledge
The Treatment of Privacy in Professional Codes of Ethics: An International Survey
Get PDFPrivacy is a major issue within libraries; however, the general concept of privacy varies across culture, context, and era. To understand what libraries mean when they discuss privacy, this article looks at the codes of ethics from 70 international library associations to find references to privacy. Using a content analysis, several themes emerge as issues that should be considered and asserted when approaching privacy concerns in the library
Security Analytics
Get PDFSecurity analytics, which separates malicious activity from normal usage patterns, leverages data analytics to assist with system security. The field encompasses analytic capabilities that enable the analysis of large quantities of structured and unstructured data across large infrastructures in a short amount of time, allowing monitoring and surveillance of activity such as network traffic, web transactions, network servers and nodes, and user credentialing to detect threats and to provide an overall picture of a system’s security posture