Pub Date : 2025-10-01DOI: 10.1016/j.teler.2025.100254
Abubakar Wakili , Sara Bakkali , Isa Ali Ibrahim
Integrating Internet of Things (IoT) technologies in healthcare has significantly enhanced service delivery and also introduced critical cybersecurity vulnerabilities, including ransomware attacks, data tampering, and unauthorised access. To address these challenges, this study proposes a Digital Twin-Enhanced Cybersecurity Framework (DT-CF) tailored for healthcare IoT systems within Industry 4.0 environments. The DT-CF employs real-time digital twins to generate synchronised replicas of physical devices (e.g., smart infusion pumps, wearable sensors), enabling continuous monitoring and predictive anomaly detection through machine learning models. The framework integrates Hyperledger Fabric blockchain and smart contracts to enforce secure access control and ensure data integrity. A conceptual case study, designed to mirror the operational dynamics of a modern healthcare facility, is presented to illustrate the framework’s practical applicability, highlighting its potential to enhance system reliability and support automated threat mitigation. Key contributions include a scalable DT-CF architecture, AI-driven analytics, and a step-by-step implementation guide for deploying context-aware digital twins in clinical environments. By bridging real-time physical–virtual synchronisation with proactive cybersecurity measures, the DT-CF offers a resilient and transparent solution to safeguard sensitive patient data and critical healthcare infrastructure.
{"title":"A digital twin-enhanced cybersecurity framework for IoT in healthcare: Applications in industry 4.0","authors":"Abubakar Wakili , Sara Bakkali , Isa Ali Ibrahim","doi":"10.1016/j.teler.2025.100254","DOIUrl":"10.1016/j.teler.2025.100254","url":null,"abstract":"<div><div>Integrating Internet of Things (IoT) technologies in healthcare has significantly enhanced service delivery and also introduced critical cybersecurity vulnerabilities, including ransomware attacks, data tampering, and unauthorised access. To address these challenges, this study proposes a Digital Twin-Enhanced Cybersecurity Framework (DT-CF) tailored for healthcare IoT systems within Industry 4.0 environments. The DT-CF employs real-time digital twins to generate synchronised replicas of physical devices (e.g., smart infusion pumps, wearable sensors), enabling continuous monitoring and predictive anomaly detection through machine learning models. The framework integrates Hyperledger Fabric blockchain and smart contracts to enforce secure access control and ensure data integrity. A conceptual case study, designed to mirror the operational dynamics of a modern healthcare facility, is presented to illustrate the framework’s practical applicability, highlighting its potential to enhance system reliability and support automated threat mitigation. Key contributions include a scalable DT-CF architecture, AI-driven analytics, and a step-by-step implementation guide for deploying context-aware digital twins in clinical environments. By bridging real-time physical–virtual synchronisation with proactive cybersecurity measures, the DT-CF offers a resilient and transparent solution to safeguard sensitive patient data and critical healthcare infrastructure.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"20 ","pages":"Article 100254"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145222209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-28DOI: 10.1016/j.teler.2025.100256
Degen Hu, Chenyang Wang
In the Russo-Ukrainian conflict, the Bucha Incident has sparked extensive debates and diverse narratives, making it an important lens for examining public communication. This paper analyzes the narrative competition presented on the official websites of the Russian and Ukrainian Ministries of Foreign Affairs (MFAs). By applying Fairclough’s 3D Model of Discourse Analysis, the study finds that the two countries construct their narratives in distinctly different ways. Ukraine adopts an appealing framework, using emotionally driven stories to accuse Russia of committing a civilian massacre. By contrast, Russia employs an evidentiary framework to deny such accusations, emphasizing what it regards as gaps in the evidence of Ukraine’s narratives. This discursive rivalry can be viewed as a form of hybrid media warfare, where the control of public opinion is the key to gaining international support.
{"title":"Hybrid media warfare: Discourse analysis of Russian and Ukrainian MFA websites on the Bucha Incident","authors":"Degen Hu, Chenyang Wang","doi":"10.1016/j.teler.2025.100256","DOIUrl":"10.1016/j.teler.2025.100256","url":null,"abstract":"<div><div>In the Russo-Ukrainian conflict, the Bucha Incident has sparked extensive debates and diverse narratives, making it an important lens for examining public communication. This paper analyzes the narrative competition presented on the official websites of the Russian and Ukrainian Ministries of Foreign Affairs (MFAs). By applying Fairclough’s 3D Model of Discourse Analysis, the study finds that the two countries construct their narratives in distinctly different ways. Ukraine adopts an appealing framework, using emotionally driven stories to accuse Russia of committing a civilian massacre. By contrast, Russia employs an evidentiary framework to deny such accusations, emphasizing what it regards as gaps in the evidence of Ukraine’s narratives. This discursive rivalry can be viewed as a form of hybrid media warfare, where the control of public opinion is the key to gaining international support.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"20 ","pages":"Article 100256"},"PeriodicalIF":4.7,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-18DOI: 10.1016/j.teler.2025.100250
Tabu S. Kondo, Daniel Ngondya, Hamim Rusheke
Timely screening of cervical cancer enhances treatment efficacy. However, conventional screening approaches are intrusive and inaccessible to women, especially in resource-constrained settings. While applying machine learning in cervical cancer diagnosis has the potential to enhance screening rates, privacy and inclusion, results from existing works indicate a wide disparity in approaches. In this work, a systematic review of literature was conducted to highlight gaps in literature in relation to the application of machine learning for cervical cancer diagnosis from risk factors. Existing reviews on cervical cancer diagnosis have focused on image datasets and have only considered suitable Machine Learning algorithms, their performance, and features in the datasets used. Little emphasis has been paid to data preprocessing, model implementation and usability testing. In this work, four scholarly databases, namely Scopus, ScienceDirect, PubMed, and BioMedCentral (BMC), were queried using a combination of relevant keywords. Twenty-seven (27) original journal articles written in English and published between January 2014 and January 2024 were retrieved and included in the study. Results indicate that 88.9% of the studied works have used a single dataset-pointing to data sharing challenges. Only one work (3.7%) has done comprehensive data preprocessing; the rest have done partial or no data preprocessing. While Sub-Saharan Africa bears the largest cervical cancer burden, it has shown minimal involvement in cervical cancer diagnosis using machine learning, with no collaboration among experts and countries. Works have substantially focused on the performance of machine learning models, with the top 5 commonly used algorithms being Decision Tree, Support Vector Machine, Random Forest, and Logistic Regression. The implementation of the models and the assessment of the usability and acceptance of the resulting applications, however, have been neglected in the works. Policies on Machine Learning based disease diagnosis tools should emphasize diversity, equity, and inclusivity on dataset creation, comprehensive and standardized data preprocessing pipelines and prioritize human-centered design, usability testing, and clinical validation to ensure solutions are reliable and acceptable by medical professionals and relevant stakeholders.
{"title":"Application of artificial intelligence in cervical cancer diagnosis using risk factors: A systematic review","authors":"Tabu S. Kondo, Daniel Ngondya, Hamim Rusheke","doi":"10.1016/j.teler.2025.100250","DOIUrl":"10.1016/j.teler.2025.100250","url":null,"abstract":"<div><div>Timely screening of cervical cancer enhances treatment efficacy. However, conventional screening approaches are intrusive and inaccessible to women, especially in resource-constrained settings. While applying machine learning in cervical cancer diagnosis has the potential to enhance screening rates, privacy and inclusion, results from existing works indicate a wide disparity in approaches. In this work, a systematic review of literature was conducted to highlight gaps in literature in relation to the application of machine learning for cervical cancer diagnosis from risk factors. Existing reviews on cervical cancer diagnosis have focused on image datasets and have only considered suitable Machine Learning algorithms, their performance, and features in the datasets used. Little emphasis has been paid to data preprocessing, model implementation and usability testing. In this work, four scholarly databases, namely Scopus, ScienceDirect, PubMed, and BioMedCentral (BMC), were queried using a combination of relevant keywords. Twenty-seven (27) original journal articles written in English and published between January 2014 and January 2024 were retrieved and included in the study. Results indicate that 88.9% of the studied works have used a single dataset-pointing to data sharing challenges. Only one work (3.7%) has done comprehensive data preprocessing; the rest have done partial or no data preprocessing. While Sub-Saharan Africa bears the largest cervical cancer burden, it has shown minimal involvement in cervical cancer diagnosis using machine learning, with no collaboration among experts and countries. Works have substantially focused on the performance of machine learning models, with the top 5 commonly used algorithms being Decision Tree, Support Vector Machine, Random Forest, and Logistic Regression. The implementation of the models and the assessment of the usability and acceptance of the resulting applications, however, have been neglected in the works. Policies on Machine Learning based disease diagnosis tools should emphasize diversity, equity, and inclusivity on dataset creation, comprehensive and standardized data preprocessing pipelines and prioritize human-centered design, usability testing, and clinical validation to ensure solutions are reliable and acceptable by medical professionals and relevant stakeholders.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"20 ","pages":"Article 100250"},"PeriodicalIF":4.7,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-12DOI: 10.1016/j.teler.2025.100251
Diona Varastika, Maureen Esther Wijaya, Monica Shannon Clio Aurelie, Putu Wuri Handayani, Hana Fitriani
M-Paspor, a mobile passport application, was launched in Indonesia to facilitate digital passport management services. However, the suboptimal quality of the app has led to user dissatisfaction and limited its utilization. This study aimed to analyze the factors influencing the use of M-Paspor. Data were obtained from a survey of 433 respondents and interviews with 30 participants. Quantitative data were processed using covariance-based structural equation modeling, while the qualitative analysis used a content analytical approach. The results of this study showed that system quality, information quality, service quality, and user satisfaction play an important role in increasing the intention to use M-Paspor. In addition, user satisfaction was proven to strengthen the intention to use this application. On the other hand, perceived cyber risk was shown to affect the level of trust in government, and this trust, along with the users’ self-efficacy and satisfaction, also affected the intention to use M-Paspor. However, the analysis also found that neither information quality nor the perception of cyber risk had a direct influence on the intention to use the application. These findings suggest that while cyber risk is a concern, other factors, such as trust in government and first-hand experience of using the app, are more dominant in driving M-Paspor use.
{"title":"Mobile passport success in indonesia based on the DeLone–McLean information systems success model","authors":"Diona Varastika, Maureen Esther Wijaya, Monica Shannon Clio Aurelie, Putu Wuri Handayani, Hana Fitriani","doi":"10.1016/j.teler.2025.100251","DOIUrl":"10.1016/j.teler.2025.100251","url":null,"abstract":"<div><div>M-Paspor, a mobile passport application, was launched in Indonesia to facilitate digital passport management services. However, the suboptimal quality of the app has led to user dissatisfaction and limited its utilization. This study aimed to analyze the factors influencing the use of M-Paspor. Data were obtained from a survey of 433 respondents and interviews with 30 participants. Quantitative data were processed using covariance-based structural equation modeling, while the qualitative analysis used a content analytical approach. The results of this study showed that system quality, information quality, service quality, and user satisfaction play an important role in increasing the intention to use M-Paspor. In addition, user satisfaction was proven to strengthen the intention to use this application. On the other hand, perceived cyber risk was shown to affect the level of trust in government, and this trust, along with the users’ self-efficacy and satisfaction, also affected the intention to use M-Paspor. However, the analysis also found that neither information quality nor the perception of cyber risk had a direct influence on the intention to use the application. These findings suggest that while cyber risk is a concern, other factors, such as trust in government and first-hand experience of using the app, are more dominant in driving M-Paspor use.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"20 ","pages":"Article 100251"},"PeriodicalIF":4.7,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-12DOI: 10.1016/j.teler.2025.100252
Erkut Altındağ, Yavuz Selim Balcioglu
This study explores the multifaceted role of StarCraft and StarCraft II as both gaming phenomena and platforms for cognitive, social, and technological inquiry. Drawing on a mixed-method approach, we analyzed over 48,000 Reddit comments to investigate how the StarCraft community engages with topics such as artificial intelligence (AI), esports culture, and cognitive skill development. The research integrates topic modeling, sentiment analysis, social network analysis, and qualitative thematic interpretation to map out patterns in community discourse. Results show that while academic literature emphasizes AI applications in StarCraft, community discussions extend these narratives to include emotional resilience, real-life skill transfer, and evolving perspectives on professional play. Theoretical framing through Activity Theory highlights how technology mediates action and how community spaces serve as environments for social learning and identity formation. The findings underscore StarCraft's relevance not only as a strategic game but as a rich ecosystem for interdisciplinary research in AI, education, psychology, and digital media studies.
{"title":"Beyond the fog of war: Mining social dynamics and genre shaping in the StarCraft universe","authors":"Erkut Altındağ, Yavuz Selim Balcioglu","doi":"10.1016/j.teler.2025.100252","DOIUrl":"10.1016/j.teler.2025.100252","url":null,"abstract":"<div><div>This study explores the multifaceted role of <em>StarCraft</em> and <em>StarCraft II</em> as both gaming phenomena and platforms for cognitive, social, and technological inquiry. Drawing on a mixed-method approach, we analyzed over 48,000 Reddit comments to investigate how the <em>StarCraft</em> community engages with topics such as artificial intelligence (AI), esports culture, and cognitive skill development. The research integrates topic modeling, sentiment analysis, social network analysis, and qualitative thematic interpretation to map out patterns in community discourse. Results show that while academic literature emphasizes AI applications in <em>StarCraft</em>, community discussions extend these narratives to include emotional resilience, real-life skill transfer, and evolving perspectives on professional play. Theoretical framing through Activity Theory highlights how technology mediates action and how community spaces serve as environments for social learning and identity formation. The findings underscore <em>StarCraft</em>'s relevance not only as a strategic game but as a rich ecosystem for interdisciplinary research in AI, education, psychology, and digital media studies.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"20 ","pages":"Article 100252"},"PeriodicalIF":4.7,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.1016/j.teler.2025.100238
Rashika Bahl , Shanton Chang , George Buchanan , Dana McKay , Marc Cheong
Many researchers have qualitatively examined the everyday information behaviors of different populations and developed models to understand such behaviors. However, there is a lack of quantitative research that seeks to understand the prevalence of these everyday information activities. Given the lack of instruments for measuring everyday behaviors, we turn to information literacy instruments as they encompass the skills used to support these behaviors. Often such instruments are tested with tertiary (university and post-secondary) student populations and focus on academic information behaviors. Academic information behaviors take place in conjunction with everyday information behaviors but are different to one another. Further, the instruments do not account for transnational information behaviors even though international students travel across countries and cultures to pursue higher education. Our study addresses these gaps by developing a survey instrument based on existing information behavior models and information literacy competencies. We collect data from 202 tertiary students studying at universities in Victoria, Australia. Following data collection, we run a factor analysis to validate the instrument and understand what factors shape the phenomenon of everyday information behaviors. Our factor analysis reveals eight factors. The factors indicate that interactions with disagreeable information are separate from those with useful information. They also show that transnational information behaviors are part of the everyday. Our prototype instrument is an important contribution to the literature and the factors will be valuable to future researchers studying everyday information behaviors.
{"title":"Everyone, everyday, everywhere: Designing a quantitative measure of information behaviors","authors":"Rashika Bahl , Shanton Chang , George Buchanan , Dana McKay , Marc Cheong","doi":"10.1016/j.teler.2025.100238","DOIUrl":"10.1016/j.teler.2025.100238","url":null,"abstract":"<div><div>Many researchers have qualitatively examined the everyday information behaviors of different populations and developed models to understand such behaviors. However, there is a lack of quantitative research that seeks to understand the prevalence of these everyday information activities. Given the lack of instruments for measuring everyday behaviors, we turn to information literacy instruments as they encompass the skills used to support these behaviors. Often such instruments are tested with tertiary (university and post-secondary) student populations and focus on academic information behaviors. Academic information behaviors take place in conjunction with everyday information behaviors but are different to one another. Further, the instruments do not account for transnational information behaviors even though international students travel across countries and cultures to pursue higher education. Our study addresses these gaps by developing a survey instrument based on existing information behavior models and information literacy competencies. We collect data from 202 tertiary students studying at universities in Victoria, Australia. Following data collection, we run a factor analysis to validate the instrument and understand what factors shape the phenomenon of everyday information behaviors. Our factor analysis reveals eight factors. The factors indicate that interactions with disagreeable information are separate from those with useful information. They also show that transnational information behaviors are part of the everyday. Our prototype instrument is an important contribution to the literature and the factors will be valuable to future researchers studying everyday information behaviors.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100238"},"PeriodicalIF":4.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144925157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.1016/j.teler.2025.100245
Rudolf Siegel , Cornelius J. König , Julia Jörg
Electronic monitoring has become a widespread method to record and analyze the behavior of employees. The current study investigated how developmental and controlling purposes of electronic monitoring, as well as participation, moderate the effects of electronic monitoring on employees’ well-being. Based on social information processing theory, developmental and controlling purposes were assumed to buffer or strengthen the relationship of monitoring with work satisfaction, engagement, and stress. In addition, participative decision making by team-leaders and works councils were expected to weaken this relationship. To examine our hypotheses, we surveyed 365 blue-collar workers from 29 organizations in Germany. To provide the best fit to the data, a Bayesian multivariate and multilevel approach was applied. We found detrimental effects of electronic monitoring on worker stress. However, we could not find the proposed moderator effects. We discuss several theoretical and methodological aspects that may have led to these findings. Future research on electronic monitoring should consider additional explaining factors rather than solely focusing on electronic monitoring.
{"title":"An expanded view on electronic monitoring: Testing moderating effects of participation and perceived purposes of electronic monitoring","authors":"Rudolf Siegel , Cornelius J. König , Julia Jörg","doi":"10.1016/j.teler.2025.100245","DOIUrl":"10.1016/j.teler.2025.100245","url":null,"abstract":"<div><div>Electronic monitoring has become a widespread method to record and analyze the behavior of employees. The current study investigated how developmental and controlling purposes of electronic monitoring, as well as participation, moderate the effects of electronic monitoring on employees’ well-being. Based on social information processing theory, developmental and controlling purposes were assumed to buffer or strengthen the relationship of monitoring with work satisfaction, engagement, and stress. In addition, participative decision making by team-leaders and works councils were expected to weaken this relationship. To examine our hypotheses, we surveyed 365 blue-collar workers from 29 organizations in Germany. To provide the best fit to the data, a Bayesian multivariate and multilevel approach was applied. We found detrimental effects of electronic monitoring on worker stress. However, we could not find the proposed moderator effects. We discuss several theoretical and methodological aspects that may have led to these findings. Future research on electronic monitoring should consider additional explaining factors rather than solely focusing on electronic monitoring.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100245"},"PeriodicalIF":4.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144932236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cloud computing environments face persistent threats from sophisticated Distributed Denial of Service (DDoS) attacks. Effective defense requires not only high accuracy but also real-time performance and transparent decision-making, a combination that challenges conventional security solutions. To address these challenges, a novel framework is introduced for real-time DDoS detection. It integrates a hybrid ensemble feature selection pipeline, combining statistical analysis with metaheuristic algorithms (GA, ACO, PSO, Aquila, GWO) to isolate the most critical traffic features. The Synthetic Minority Oversampling Technique (SMOTE) is employed to rectify class imbalance inherent in real-world network data. At the core of the framework, a comparative analysis evaluates the efficacy of deep learning models, with a focus on Kolmogorov–Arnold Networks (KAN) against established architectures like CNN, LSTM, and GRU. For model transparency and to foster operator trust, Explainable AI (XAI) techniques, specifically SHAP and LIME, are integrated to interpret detection results. The system’s performance is rigorously validated on public benchmark datasets (CICIDS2017, CICIDS2018, CICDDoS2019) and a custom dataset generated within a realistic OpenStack simulation environment. Results demonstrate that the KAN-based model significantly outperforms its counterparts, achieving superior detection accuracy while maintaining the lowest inference latency, confirming its suitability for real-time defense. Furthermore, the XAI component successfully provides clear, actionable insights into the model’s decision-making process, enhancing the framework’s overall reliability for modern cloud security operations.
{"title":"Transparent DDoS defense by combining Kolmogorov–Arnold networks and XAI for real-time protection in cloud environments","authors":"Mohamed Ouhssini , Karim Afdel , Mohamed Akouhar , El hafed Agherrabi , Abdallah Abarda , Mohamed El Fatini , Hasna Mahmoud","doi":"10.1016/j.teler.2025.100242","DOIUrl":"10.1016/j.teler.2025.100242","url":null,"abstract":"<div><div>Cloud computing environments face persistent threats from sophisticated Distributed Denial of Service (DDoS) attacks. Effective defense requires not only high accuracy but also real-time performance and transparent decision-making, a combination that challenges conventional security solutions. To address these challenges, a novel framework is introduced for real-time DDoS detection. It integrates a hybrid ensemble feature selection pipeline, combining statistical analysis with metaheuristic algorithms (GA, ACO, PSO, Aquila, GWO) to isolate the most critical traffic features. The Synthetic Minority Oversampling Technique (SMOTE) is employed to rectify class imbalance inherent in real-world network data. At the core of the framework, a comparative analysis evaluates the efficacy of deep learning models, with a focus on Kolmogorov–Arnold Networks (KAN) against established architectures like CNN, LSTM, and GRU. For model transparency and to foster operator trust, Explainable AI (XAI) techniques, specifically SHAP and LIME, are integrated to interpret detection results. The system’s performance is rigorously validated on public benchmark datasets (CICIDS2017, CICIDS2018, CICDDoS2019) and a custom dataset generated within a realistic OpenStack simulation environment. Results demonstrate that the KAN-based model significantly outperforms its counterparts, achieving superior detection accuracy while maintaining the lowest inference latency, confirming its suitability for real-time defense. Furthermore, the XAI component successfully provides clear, actionable insights into the model’s decision-making process, enhancing the framework’s overall reliability for modern cloud security operations.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100242"},"PeriodicalIF":4.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144925164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.1016/j.teler.2025.100246
Maria Cavalcante , João Varajão , Luís Silva Rodrigues
Digital Transformation (DT) is a strategic and multidimensional initiative through which organisations reconfigure their business models, structures, and capabilities by integrating digital technologies. Despite growing attention in the literature, a gap remains in understanding the factors that precede DT efforts in a comprehensive and integrated manner. This study addresses this gap by empirically analysing the antecedents of DT, focusing on the motivations, objectives, and strategies formulated by organisations. A questionnaire-based survey was administered to 205 professionals involved in digital initiatives across diverse organisational contexts. The study follows a quantitative approach, supported by descriptive statistical analysis. The results show that, while there is an expected consistency between motivations and objectives, their correspondence with the strategies adopted is not always evident. This research contributes to the theoretical advancement of DT studies by proposing an integrated perspective on its antecedents and offers practical insights for managers and decision-makers in planning and monitoring digital initiatives, reinforcing the need for coherence between strategic intent and operational execution.
{"title":"Digital transformation initiatives: Motivations, objectives, and strategies","authors":"Maria Cavalcante , João Varajão , Luís Silva Rodrigues","doi":"10.1016/j.teler.2025.100246","DOIUrl":"10.1016/j.teler.2025.100246","url":null,"abstract":"<div><div>Digital Transformation (DT) is a strategic and multidimensional initiative through which organisations reconfigure their business models, structures, and capabilities by integrating digital technologies. Despite growing attention in the literature, a gap remains in understanding the factors that precede DT efforts in a comprehensive and integrated manner. This study addresses this gap by empirically analysing the antecedents of DT, focusing on the motivations, objectives, and strategies formulated by organisations. A questionnaire-based survey was administered to 205 professionals involved in digital initiatives across diverse organisational contexts. The study follows a quantitative approach, supported by descriptive statistical analysis. The results show that, while there is an expected consistency between motivations and objectives, their correspondence with the strategies adopted is not always evident. This research contributes to the theoretical advancement of DT studies by proposing an integrated perspective on its antecedents and offers practical insights for managers and decision-makers in planning and monitoring digital initiatives, reinforcing the need for coherence between strategic intent and operational execution.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100246"},"PeriodicalIF":4.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144988572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.1016/j.teler.2025.100241
Alexander Mertes, Achim Lang
Public involvement in public discourse is increasingly facilitated through digital means, known as electronic participation (e-participation). This study explores the development of e-participation tools by leveraging user profiles and personas to ensure user-centered design. E-participation involves engaging citizens in policy and decision-making processes through information and communication technologies (ICT). The study emphasizes the importance of user-centered design (UCD) in developing e-participation tools. Personas and user profiles are critical in this context. Personas are hypothetical archetypes created using qualitative methods such as interviews and focus groups, while user profiles are typically based on quantitative data, categorizing users into groups with similar characteristics and behaviors. Data for this study were collected through a survey conducted in Switzerland with 1,787 respondents. The study identified six distinct participation clusters, ranging from those who prefer digital to non-digital participation or were undecided. User profiles were created for each cluster using model-based clustering, highlighting socio-demographic characteristics and opinions on participation. The study then translated these user profiles into personas with the help of AI. Seven personas were developed, each with specific characteristics and challenges. These personas provide a detailed and reliable mapping of user groups, which can aid in developing e-participation tools. The findings suggest that combining qualitative and quantitative methods to create user profiles and personas can enhance the development process of e-participation tools, ensuring they meet the needs of diverse user groups.
{"title":"User profiles and personas of electronic participation in public discourse","authors":"Alexander Mertes, Achim Lang","doi":"10.1016/j.teler.2025.100241","DOIUrl":"10.1016/j.teler.2025.100241","url":null,"abstract":"<div><div>Public involvement in public discourse is increasingly facilitated through digital means, known as electronic participation (e-participation). This study explores the development of e-participation tools by leveraging user profiles and personas to ensure user-centered design. E-participation involves engaging citizens in policy and decision-making processes through information and communication technologies (ICT). The study emphasizes the importance of user-centered design (UCD) in developing e-participation tools. Personas and user profiles are critical in this context. Personas are hypothetical archetypes created using qualitative methods such as interviews and focus groups, while user profiles are typically based on quantitative data, categorizing users into groups with similar characteristics and behaviors. Data for this study were collected through a survey conducted in Switzerland with 1,787 respondents. The study identified six distinct participation clusters, ranging from those who prefer digital to non-digital participation or were undecided. User profiles were created for each cluster using model-based clustering, highlighting socio-demographic characteristics and opinions on participation. The study then translated these user profiles into personas with the help of AI. Seven personas were developed, each with specific characteristics and challenges. These personas provide a detailed and reliable mapping of user groups, which can aid in developing e-participation tools. The findings suggest that combining qualitative and quantitative methods to create user profiles and personas can enhance the development process of e-participation tools, ensuring they meet the needs of diverse user groups.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100241"},"PeriodicalIF":4.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144932234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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