Deep Learning for Phishing Detection: Taxonomy, Current Challenges and Future Directions

This work was supported in part by the Ministry of Higher Education under the Fundamental Research Grant Scheme under Grant FRGS/1/2018/ICT04/UTM/01/1; and in part by the Faculty of Informatics and Management, University of Hradec Kralove, through SPEV project under Grant 2102/2022.Phishing has become an increasing concern and captured the attention of end-users as well as security experts. Existing phishing detection techniques still suffer from the de ciency in performance accuracy and inability to detect unknown attacks despite decades of development and improvement. Motivated to solve these problems, many researchers in the cybersecurity domain have shifted their attention to phishing detection that capitalizes on machine learning techniques. Deep learning has emerged as a branch of machine learning that becomes a promising solution for phishing detection in recent years. As a result, this study proposes a taxonomy of deep learning algorithm for phishing detection by examining 81 selected papers using a systematic literature review approach. The paper rst introduces the concept of phishing and deep learning in the context of cybersecurity. Then, taxonomies of phishing detection and deep learning algorithm are provided to classify the existing literature into various categories. Next, taking the proposed taxonomy as a baseline, this study comprehensively reviews the state-of-the-art deep learning techniques and analyzes their advantages as well as disadvantages. Subsequently, the paper discusses various issues that deep learning faces in phishing detection and proposes future research directions to overcome these challenges. Finally, an empirical analysis is conducted to evaluate the performance of various deep learning techniques in a practical context, and to highlight the related issues that motivate researchers in their future works. The results obtained from the empirical experiment showed that the common issues among most of the state-of-the-art deep learning algorithms are manual parameter-tuning, long training time, and de cient detection accuracy.Ministry of Higher Education under the Fundamental Research Grant Scheme FRGS/1/2018/ICT04/UTM/01/1Faculty of Informatics and Management, University of Hradec Kralove, through SPEV project 2102/202

Phishing Webpage Classification via Deep Learning-Based Algorithms: An Empirical Study

This work was supported/funded by the Ministry of Higher Education under the Fundamental Research Grant Scheme (FRGS/1/2018/ICT04/UTM/01/1). The authors sincerely thank Universiti Teknologi Malaysia (UTM) under Research University Grant Vot-20H04, Malaysia Research University Network (MRUN) Vot 4L876, for the completion of the research. Faculty of Informatics and Management, University of Hradec Kralove, SPEV project Grant Number: 2102/2021.Phishing detection with high-performance accuracy and low computational complexity has always been a topic of great interest. New technologies have been developed to improve the phishing detection rate and reduce computational constraints in recent years. However, one solution is insufficient to address all problems caused by attackers in cyberspace. Therefore, the primary objective of this paper is to analyze the performance of various deep learning algorithms in detecting phishing activities. This analysis will help organizations or individuals select and adopt the proper solution according to their technological needs and specific applications’ requirements to fight against phishing attacks. In this regard, an empirical study was conducted using four different deep learning algorithms, including deep neural network (DNN), convolutional neural network (CNN), Long Short-Term Memory (LSTM), and gated recurrent unit (GRU). To analyze the behaviors of these deep learning architectures, extensive experiments were carried out to examine the impact of parameter tuning on the performance accuracy of the deep learning models. In addition, various performance metrics were measured to evaluate the effectiveness and feasibility of DL models in detecting phishing activities. The results obtained from the experiments showed that no single DL algorithm achieved the best measures across all performance metrics. The empirical findings from this paper also manifest several issues and suggest future research directions related to deep learning in the phishing detection domain.Ministry of Higher Education under the Fundamental Research Grant Scheme FRGS/1/2018/ICT04/UTM/01/1Universiti Teknologi Malaysia (UTM) Vot-20H04Malaysia Research University Network (MRUN) 4L876Faculty of Informatics and Management, University of Hradec Kralove, SPEV project 2102/2021

On-chip ZnO nanofibers prepared by electrospinning method for NO2 gas detection

In the present study, on-chip ZnO nanofibers were fabricated by means of the electrospinning technique followed by a calcination process at 600 oC towards the gas sensor application. The morphology, composition, and crystalline structure of the as-spun and annealed ZnO nanofibers were investigated by field emission scanning electron microscopy (FESEM), energy dispersive X-ray (EDX), and X-ray diffraction (XRD), respectively. The findings show that spider-net like ZnO nanofibers with a diameter of 60 – 100 nm were successfully synthesized without any incorporation of impurities into the nanofibers. The FESEM images also reveal that each nanofiber is composed of many nanograins. The combination of experimental and calculated X-ray diffraction data indicate that ZnO nanofibers were crystallized in hexagonal wurtzite structure. For the gas sensing device application, the ZnO nanofibers-based sensors were tested with the nitrogen dioxide gas in the temperature range of 200 oC to 350 oC and concentrations from 2.5 ppm to 10 ppm. The sensing property results indicate that at the optimal working temperature of 300 oC, the ZnO nanofibers-based sensors exhibited a maximum response of 30 and 166 times on exposure of 2.5 and 10 ppm NO2 gas, respectively. The presence of nanograins within nanofibers, which results in further intensification of the resistance modulation, is responsible for such high gas response

Factors Influence on Promotion Mix in E-marketing: Case of Technology Services Enterprise in Vietnam

Purpose: The objective of this study is to clarify factors affecting the promotion mix in E-Marketing, with specific target audience being enterprises operating in the technology service industry in Vietnam.   Theoretical framework: Based on the promotion theory and social exchange theory, this study focuses on the factors that influence on the promotion decision in firms.   Design/Methodology/Approach: This study applies both qualitative and quantitative methods with data collected from a questionnaire survey.   Findings: There are 4 factors respectively Sales Promotion, Advertising, Public Relations and Personal Selling that affect the mixed promotion activities in E-Marketing of technology service enterprises in Vietnam.   Research, practical & social implications: This study propose solutions to improve the promotion activities in the e – marketing of firms in Vietnam.   Originality/Value: This study is one of the early studies that have focused in this field in Vietnam.Propósito: El objetivo de este estudio es aclarar los factores que afectan la combinación de promoción en E-Marketing, con un público objetivo específico que son las empresas que operan en la industria de servicios de tecnología en Vietnam. Marco teórico: Basado en la teoría de la promoción y la teoría del intercambio social, este estudio se centra en los factores que influyen en la decisión de promoción en las empresas. Diseño/metodología/enfoque: este estudio aplica métodos cualitativos y cuantitativos con datos recopilados de una encuesta de cuestionario. Hallazgos: Existen 4 factores, respectivamente, Promoción de Ventas, Publicidad, Relaciones Públicas y Ventas Personales que afectan las actividades mixtas de promoción en E-Marketing de las empresas de servicios de tecnología en Vietnam. Implicaciones de investigación, prácticas y sociales: este estudio propone soluciones para mejorar las actividades de promoción en el marketing electrónico de las empresas en Vietnam. Originalidad/valor: Este estudio es uno de los primeros que se han centrado en este campo en Vietnam.Objetivo: O objetivo deste estudo é esclarecer os fatores que afetam o mix de promoção no E-Marketing, tendo como público-alvo específico as empresas que operam no setor de serviços de tecnologia no Vietnã.. Referencial teórico: Com base na teoria da promoção e na teoria das trocas sociais, este estudo se concentra nos fatores que influenciam a decisão de promoção nas empresas.. Desenho/metodologia/abordagem: Este estudo aplica métodos qualitativos e quantitativos com dados coletados de uma pesquisa por questionário. Resultados: Existem 4 fatores, respectivamente, Promoção de Vendas, Publicidade, Relações Públicas e Vendas Pessoais que afetam as atividades de promoção mista em E-Marketing de empresas de serviços de tecnologia no Vietnã. Pesquisa, implicações práticas e sociais: Este estudo propõe soluções para melhorar as atividades de promoção no e – marketing de empresas no Vietnã. Originalidade/valor: Este estudo é um dos primeiros estudos que se concentraram neste campo no Vietnã. Palavras-chave:  Mix de promoção; E-Marketing; Serviços de tecnologia; Vietn

Depth-dose distribution in potatoes with low-energy X-rays

Irradiation is known as a handful measure to inhibit potato sprouting, kill harmful bacteria, and increase preservation. The absorbed dose is one of the essential characteristics of the irradiation process. In this study, the depth-dose distributions in potatoes and polymethyl methacrylate were investigated under low-energy X-ray irradiation by using the Fricke dosimeter and Gafchromic film dosimeter. The dose rates required for the rays to penetrate in polymethyl methacrylate were compared with those in potatoes. Polymethyl methacrylate could be used as a phantom in measuring the depth dose delivered in potatoes. The difference in depth-dose distribution in potatoes between one-sided and double-sided irradiation was also investigated. The calculated dose uniformity ratio values are 5.8 and 1.9 for potatoes irradiating one-sided and double-sided

Validation and utilization of an internally controlled multiplex Real-time RT-PCR assay for simultaneous detection of enteroviruses and enterovirus A71 associated with hand foot and mouth disease

Background: Hand foot and mouth disease (HFMD) is a disease of public health importance across the Asia-Pacific region. The disease is caused by enteroviruses (EVs), in particular enterovirus A71 (EV-A71). In EV-A71-associated HFMD, the infection is sometimes associated with severe manifestations including neurological involvement and fatal outcome. The availability of a robust diagnostic assay to distinguish EV-A71 from other EVs is important for patient management and outbreak response. Methods: We developed and validated an internally controlled one-step single-tube real-time RT-PCR in terms of sensitivity, linearity, precision, and specificity for simultaneous detection of EVs and EV-A71. Subsequently, the assay was then applied on throat and rectal swabs sampled from 434 HFMD patients. Results: The assay was evaluated using both plasmid DNA and viral RNA and has shown to be reproducible with a maximum assay variation of 4.41 % and sensitive with a limit of detection less than 10 copies of target template per reaction, while cross-reactivity with other EV serotypes was not observed. When compared against a published VP1 nested RT-PCR using 112 diagnostic throat and rectal swabs from 112 children with a clinical diagnosis of HFMD during 2014, the multiplex assay had a higher sensitivity and 100 % concordance with sequencing results which showed EVs in 77/112 (68.8 %) and EV-A71 in 7/112 (6.3 %). When applied to clinical diagnostics for 322 children, the assay detected EVs in throat swabs of 257/322 (79.8 %) of which EV-A71 was detected in 36/322 (11.2 %) children. The detection rate increased to 93.5 % (301/322) and 13.4 % (43/322) for EVs and EV-A71, respectively, when rectal swabs from 65 throat-negative children were further analyzed. Conclusion: We have successfully developed and validated a sensitive internally controlled multiplex assay for rapid detection of EVs and EV-A71, which is useful for clinical management and outbreak control of HFMD. Keywords: Hand foot and mouth disease, Enteroviruses, Enterovirus A71, Real-time RT-PCR, Diagnosi

A generic assay for whole-genome amplification and deep sequencing of enterovirus A71

Enterovirus A71 (EV-A71) has emerged as the most important cause of large outbreaks of severe and sometimes fatal hand, foot and mouth disease (HFMD) across the Asia-Pacific region. EV-A71 outbreaks have been associated with (sub)genogroup switches, sometimes accompanied by recombination events. Understanding EV-A71 population dynamics is therefore essential for understanding this emerging infection, and may provide pivotal information for vaccine development. Despite the public health burden of EV-A71, relatively few EV-A71 complete-genome sequences are available for analysis and from limited geographical localities. The availability of an efficient procedure for whole-genome sequencing would stimulate effort to generate more viral sequence data. Herein, we report for the first time the development of a next-generation sequencing based protocol for whole-genome sequencing of EV-A71 directly from clinical specimens. We were able to sequence viruses of subgenogroup C4 and B5, while RNA from culture materials of diverse EV-A71 subgenogroups belonging to both genogroup B and C was successfully amplified. The nature of intra-host genetic diversity was explored in 22 clinical samples, revealing 107 positions carrying minor variants (ranging from 0 to 15 variants per sample). Our analysis of EV-A71 strains sampled in 2013 showed that they all belonged to subgenogroup B5, representing the first report of this subgenogroup in Vietnam. In conclusion, we have successfully developed a high-throughput next-generation sequencing-based assay for whole-genome sequencing of EV-A71 from clinical samples

Spatiotemporal evolution of SARS-CoV-2 Alpha and Delta variants during large nationwide outbreak of COVID-19, Vietnam, 2021

We analyzed 1,303 SARS-CoV-2 whole-genome sequences from Vietnam, and found the Alpha and Delta variants were responsible for a large nationwide outbreak of COVID-19 in 2021. The Delta variant was confined to the AY.57 lineage and caused >1.7 million infections and >32,000 deaths. Viral transmission was strongly affected by nonpharmaceutical interventions

EFETIVIDADE DA INTERVENÇÃO EDUCACIONAL DIGICARE NA MELHORIA DAS HABILIDADES DE COACHING CLÍNICO DE ESTUDANTES DE ENFERMAGEM E MEDICINA NO VIETNAME E BANGLADESH: UM PRÉ- E PÓS-ESTUDO EXPLORATÓRIO

Coaching has become an important approach to support self-management of patients with non-communicable diseases (NCDs) in healthcare education. Studies conducted in European countries have emphasized the significance of formal coaching training in enhancing the competencies of healthcare students. However, in Southeast Asia, where NCDs pose a serious public health concern, there is a lack of such training opportunities. To address this issue, an exploratory pre and post study was conducted to evaluate the effectiveness of the DigiCare educational intervention in improving clinical coaching skills. Nursing and medical students from six universities in Vietnam and Bangladesh were invited to participate. The intervention included both theoretical and practical classes with interactive methods and home assignments, with a total duration of over 10 contact hours. Pre- and post-intervention assessments were conducted using the Self-Efficacy and Performance in Self-management Support instrument, which was translated and culturally adapted to both countries. Statistical analysis showed a significant improvement in students’ overall competence scores from before (M = 2.6, SD = .67) to after the intervention (M = 3.05, SD = .55), with a medium effect size (p < .001; d = .73). The DigiCare educational intervention appears to be a low-cost and meaningful addition to the curriculum of both nursing and medical universities across countries, with potential benefits in the development of students’ clinical coaching competencies.O coaching tornou-se uma abordagem importante para apoiar a autogestão de pacientes com doenças não transmissíveis (DNTs) na educação em saúde. Estudos realizados em países europeus têm enfatizado a importância do treinamento formal em coaching para aprimorar as competências dos estudantes de saúde. No entanto, no Sudeste Asiático, onde as DNTs representam uma séria preocupação de saúde pública, há uma falta de oportunidades de treinamento nesse sentido. Para abordar essa questão, foi conduzido um pré- e pós-estudo exploratório para avaliar a eficácia da intervenção educacional DigiCare na melhoria das habilidades de coaching clínico. Estudantes de enfermagem e medicina de seis universidades no Vietname e em Bangladesh foram convidados a participar. A intervenção incluiu aulas teóricas e práticas com métodos interativos e tarefas domiciliares, totalizando mais de 10 horas de contato. Avaliações pré e pós-intervenção foram conduzidas utilizando o instrumento de Autoeficácia e Desempenho no Suporte à Autogestão, que foi traduzido e adaptado culturalmente para ambos os países. Análises estatísticas mostraram uma melhoria significativa nas pontuações gerais de competência dos estudantes, de antes (M = 2,6, DP = 0,67) para depois da intervenção (M = 3,05, DP = 0,55), com um efeito médio (p < 0,001; d = 0,73). A intervenção educacional DigiCare parece ser uma adição de baixo custo e significativa para o currículo de universidades de enfermagem e medicina em diferentes países, com benefícios potenciais no desenvolvimento das competências clínicas de coaching dos estudantes