There are many phishing websites detection techniques in literature, namely white-listing, black-listing, visual-similarity, heuristic-based, and others. However, detecting zero-hour or newly ...designed phishing website attacks is an inherent property of machine learning and deep learning techniques. By considering a promising solution of machine learning and deep learning techniques, researchers have made a great deal of effort to tackle the this problem, which persists due to attackers constantly devising novel strategies to exploit vulnerability or gaps in existing anti-phishing measures. In this study, an extensive effort has been made to rigorously review recent studies focusing on Machine Learning and Deep Learning Based Phishing Websites Detection to excavate the root cause of the aforementioned problems and offer suitable solutions. The study followed the significant criterion to search, download, and screen relevant studies, then to evaluate criterion-based selected studies. The findings show that significant research gaps are available in the rigorously reviewed studies. These gaps are mainly related to imbalanced dataset usage, improper selection of dataset source(s), the unjustified reason for using specific train-test dataset split ratio, scientific disputes on website features inclusion and exclusion, lack of universal consensus on phishing website lifespans and on what is defining a small dataset size, and run-time analysis issues. The study clearly presented a summary of the comparative analysis performed on each reviewed research work so that future researchers could use it as a structured guideline to develop a novel solution for anti-phishing website attacks.
This study examined determinants of library and information science undergraduate students’ first impression with the university library websites. A total enumeration method was used to involve ...54 year 4 undergraduate students of Library and Information Science from two selected universities. Undergraduate Students’ Determinants of First Impression with University Library Websites Questionnaire was used to gather data. The results obtained demonstrate that there is significant correlation between LIS students’ Perception of Website quality, Website interactivity, Website aesthetic perception, Website prototypicality, and Website satisfaction with first impression toward the university library website. The five independent variables (Website quality, Website interactivity, Website aesthetic perception, Website prototypicality, and Website satisfaction) jointly (as indicated by the R-square value) explained or predicted 66% of the variation in LIS students’ first impression towards university library website. Aesthetic perception of library website contributed most to the prediction of LIS students’ first impression towards library website, followed in declining order of strength by library website interactivity, library website satisfaction, and library website quality. However, prototypicality though correlated with first impression, its contribution is not significant. Notable limitation of this study is that, data was collected from undergraduate students in only two universities focusing only Library and Information Science students. The results call for formidable efforts to improve the users experience on the web, because the first impression counts. This study has implications for the users patronizing the university library websites. The results show that Aesthetic perception of library website contributed mostly to the prediction of LIS students’ first impression towards university library website, followed by library website interactivity. These findings may not be applicable to other university library websites but this depend on the experience of the users.
Being a controversial industry, oil companies turn to corporate social responsibility (CSR) as a means to obtain legitimacy. Adopting a case study methodology, this research examines the ...characteristics of CSR strategies and CSR communication tactics of six oil companies by analyzing their 2011-2012 web site content. We found that all six companies engaged in CSR activities addressing the needs of various stakeholders and had cross-sector partnerships. CSR information on these companies' web sites was easily accessible, often involving the use of multimedia technologies and sometimes social media platforms. Furthermore, to boost the credibility of their CSR messages, these companies utilized a variety of tactics, such as factual arguments and two-sided messages. In sum, this research unveils the interconnectedness among business strategy, CSR practices, and CSR communication in oil companies' attempt to gain legitimacy in an environment of controversy. The article ends with a discussion of the theoretical and practical implications of the research findings.
Understanding factors that influence online shopping and managing consumer relationships is not a trivial task for firms, considering the many pertinent factors that influence behavior, including the ...product being shopped (i.e., the "what") and the context of the website itself (i.e., the "where"). This study investigates the impact of these characteristics on an online transaction's basket value, after incorporating the role of other aspects of the browsing process including page views and visit duration. The authors estimate a multivariate mixed-effects Type II Tobit model with a system of equations to explain variation in shopping basket value, using data involving 773,262 browsing sessions resulting in 9,664 transactions across 43 product categories from 385 unique websites. The results support the assertions that contextual factors are associated with online browsing. For example, a website's scope in terms of product variety is associated positively with visit durations and basket values but negatively with page views. Furthermore, a website's communication functionality is positively associated with basket value for hedonic products. Insights suggest managerial implications involving product and website strategies for online retailers.
Phishing is described as the art of echoing a website of a creditable firm intending to grab user's private information such as usernames, passwords and social security number. Phishing websites ...comprise a variety of cues within its content-parts as well as the browser-based security indicators provided along with the website. Several solutions have been proposed to tackle phishing. Nevertheless, there is no single magic bullet that can solve this threat radically. One of the promising techniques that can be employed in predicting phishing attacks is based on data mining, particularly the ‘induction of classification rules’ since anti-phishing solutions aim to predict the website class accurately and that exactly matches the data mining classification technique goals. In this study, the authors shed light on the important features that distinguish phishing websites from legitimate ones and assess how good rule-based data mining classification techniques are in predicting phishing websites and which classification technique is proven to be more reliable.
Website morphing infers latent customer segments from clickstreams and then changes websites' look and feel to maximize revenue. The established algorithm infers latent segments from a preset number ...of clicks and then selects the best "morph" using expected Gittins indices. Switching costs, potential website exit, and all clicks prior to morphing are ignored. We model switching costs, potential website exit, and the (potentially differential) impact of all clicks to determine when to morph for each customer. Morphing earlier means more customer clicks are based on the optimal morph; morphing later reveals more about the customer's latent segment. We couple this within-customer optimization to between-customer expected Gittins index optimization to determine which website "look and feel" to give to each customer at each click. We evaluate the improved algorithm with synthetic data and with a proof-of-feasibility application to Japanese bank card loans. The proposed algorithm generalizes the established algorithm, is feasible in real time, performs substantially better when tuning parameters are identified from calibration data, and is reasonably robust to misspecification.
Data, as supplemental material, are available at
http://dx.doi.org/10.1287/mnsc.2014.1961
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This paper was accepted by Eric Bradlow, special issue on business analytics
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Since machine learning became a prominent feature in the modern-day computing landscape, the urge to automate processes has increased. One such process of particular interest has been the automatic ...generation of websites based on user intention. Though the requirement of such automatic generation is a modern-day need, the quality of the automatic generation still provides a unique set of challenges. As such, to analyze these unique challenges and viable opportunities in automatic website generation, this survey systematically reviews research on the topics of automatic website generation. The analysis initially segments state-of-the-art into three categories based on the dominant strategy used for automatic generation. These strategies are examples-based, mock-up-driven, and artificial intelligence-driven automatic website generation. When considering the example-based strategy, the emphasis is on analyzing how manual design aspects of a professionally developed website are incorporated into generation models and the challenges that arise. Similarly, transformation methods from website visual design into functional GUI code are investigated for the mock-up-driven strategy with a particular reference to the six underlying conversion mechanisms. Finally, artificial intelligence website builders are analyzed based on their ability to build customizable websites to user preferences. Based on this systematic review of 47 research works on the three dominant strategies, this survey outlines unique challenges and future research endeavors that researchers would encounter when developing models that generate websites automatically and provides insights to researchers on selecting a website generation strategy based on user intention appropriately.
Website evaluation has gained considerable attention from academic researchers since the emergence of hotel websites in the late 1990 s. Previous studies have developed and adopted various ...methodologies and approaches for website evaluation. However, studies tracking changes in hotel website evaluation along with their rapid development have been scant. This study traces the chronological changes in website evaluation models and provides future research directions. The main findings indicate that information quality has been the main focus although different terms or expressions have been used to represent the concept. In addition, many diverse website evaluation models have been advocated in the past decade. Findings of this study can provide practical implications for hotel managers to ensure online hotel information quality and achieve high-level information communication.
In this article, the website infrastructures of both pro science climate change and climate denier websites are examined. The focus is on the backstage of the website, defined as the use of widgets, ...ad trackers, beacons, and analytics and not the website content, or what might be described as the front stage. This research addresses questions about the presence and use of trackers within the commodification of user attention, the audience economy. The study concludes that organizations on both sides of the climate issue use similar strategies in monetizing their websites and tracking user behavior. Moreover, the infrastructure that is created among the platforms reflects the major role that big tech plays in developing an interconnected web of tracker technologies. While website transparency may remain an ideal, the study advocates for a responsible approach to website development, one that acknowledges the complexity of the issue within a stronger regulatory environment.
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