10th International Congress on Information and Communication Technology in concurrent with ICT Excellence Awards (ICICT 2025) will be held at London, United Kingdom | February 18 - 21 2025.
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Authors - Rotimi Williams Bello, Pius A. Owolawi, Chunling Tu, Etienne A. van Wyk Abstract - One of the mainstream methods for user identification has been by face. However, the vulnerability of face-swapping applications to security issues when swapping the faces between two different facial images, has undermined the genuine aims of the technology, thereby threatening the security of certain applications and individual users when such action is performed without caution. To address this, we propose the development of scalable and safe cloud architecture for a face-swapping application that lets users upload two photos and get a face-swapped output. This is achieved by: (1) creating a secure virtual private cloud (VPC) to hold all application resources, (2) using a Web Application Firewall (WAF) to filter and safeguard requests, (3) putting application programming interface (API) Gateway into place to provide regulated access to the application's API, (4) processing and overseeing face-swapping operations with Lambda functions, (5) using VPC Endpoint to store input and output photos in Simple Storage Service (S3) buckets for private access, and (6) configuring a Simple Notification Service (SNS) to inform users of the progress and completion of their requests. A face swapping dataset derived from an open benchmark dataset was utilized for training and testing the proposed system. The experiment produced an effective solution with a 93% detection accuracy. The implications of this solution are: (1) the provision of security and private access to Amazon Web Services (AWS) by VPC Endpoints and WAF, (2) elimination of Network Address Translation (NAT) Gateway costs by utilizing VPC Endpoints for private S3 access, (3) offering of a scalable processing environment by Lambda functions without the need for server management, (4) delivering of real-time notifications by SNS to users regarding their request status, and (5) optimization of S3 storage ensures quick and efficient access to images.
Authors - Duong Bui, Cuong Nguyen Abstract - Purpose - We are currently experiencing the era of digital transformation. This leads to concepts like digital leadership, continuous learning, and digital culture. The objective of this study is to investigate the influence of various dimensions of digital leadership (DL) on enhancing responsible innovation (RI), with a mediating role of continuous learning (CL) and the management of digital culture (DC). Design/methodology/approach – This study was employed a mixed-methods research design. Data were collected using a self-administered questionnaire distributed to a sample of 250 employees from small and medium-sized enterprises in Vietnam, selected through convenience sampling. Findings - Structural equation modeling was utilized for path analysis in the study. The findings indicated a positive and significant impact of digital leadership (DL) on responsible innovation (RI), mediated through the roles of continuous learning (CL) and digital culture (DC). Practical implications – This study has highlighted the significance of the impact of DL to create CL and DC in Vietnam. The study also confirmed the relationship between DL and RI. It adds to the evidence on digital leadership in Vietnam. Originality/value – Empirical evidence was provided by this study to support the role of DC in fostering RI. Furthermore, how DL strengthens its influence on CL and DC within organizations was demonstrated. By doing so, a critical gap in understanding the impact of DL on RI, CL, and DC in the context of Vietnam is addressed by this research.
Authors - Suresh Rasappan, S. Ahamed Nishath, Francis Saviour Devaraj Abstract - This study proposes a hybrid CNN-ANN architecture for lung cancer image classification on the LC105K dataset. Enhanced feature extraction and representation techniques improve classification accuracy. The model leverages CNN and ANN strengths, demonstrating superior performance compared to existing methods. Results show significant accuracy, precision, and recall improvements, offering a promising solution for computer-aided diagnosis.
Authors - Abdellah Tahenni, Abdelkader Belkhir Abstract - This study provides the privacy concerns of AI predictive algorithms for E-health systems. A significant disadvantage is that these algorithms can infer delicate private health data of people, particularly high profile figures, from big datasets. This might be infringing privacy and result in discrimination or safety threats. The paper additionally analyzes the danger of AI prediction algorithms escalating wider privacy violation risks for patients and providers like accidental disclosure of personal details or unauthorized use of system vulnerabilities for information theft via AI models. The mixed-methods methodology encompasses evaluation of AI algorithm abilities, privacy breach case studies, expert interviews, healthcare provider surveys and eHealth method penetration tests. The results plot vulnerabilities, risk levels and technical, cultural and regulatory variables related to these privacy risks. To lessen those risks, a framework is suggested that has specialized safeguards including AI auditing and differing privacy, governance (data security policies and ethical AI guidelines), organizational (devoted privacy roles and staff training) along with ethical considerations balance innovation with privacy protection. Lastly, the study suggests multi-stakeholder, strategic and collaborative interaction among healthcare, policymakers, AI designers and patient advocates to mitigate AI driven privacy issues in eHealth systems through serious scrutiny and suggestions guided by this vision.
Authors - Kevin Tanuwijaya, Elfindah Princes Abstract - Indonesia's digital economy is rapidly expanding, fueled by technological advancements and government support for e-commerce. E-commerce has become a cornerstone of the nation's economy, significantly contributing to Gross Merchandise Value (GMV). However, Small and Medium-Sized Enterprises (SMSEs), crucial to Indonesia's economic landscape, face challenges in building lasting customer loyalty. This study investigates the impact of affiliate marketing and gamification on SMSE sustainability, focusing on economic, social, and environmental dimensions. Data were collected from a purposive sample of 100 respondents in Jakarta was analyzed using Structural Equation Modeling with Partial Least Squares (SEM-PLS). The results demonstrate that both affiliate marketing and gamification directly enhance customer loyalty. Furthermore, customer loyalty was found to have a significant positive impact on SMSE sustainability. Crucially, the study reveals a mediating effect of customer loyalty, bridging the gap between affiliate marketing and gamification strategies and their ultimate impact on business sustainability. This research contributes valuable insights into the sustainable business literature by empirically examining its effects on key sustainability variables. The study concludes with a discussion of theoretical implications, practical recommendations for SMSEs, and avenues for future research.
Authors - Nguyen Quoc Cuong, Huynh Gia Nghi, Mai Thi Bich Ngoc Abstract - Live streaming has transformed online purchasing, especially for tech-savvy Generation Z, who remain cautious in their purchasing decisions. This study explores the motivational factors driving live streaming-enabled purchasing decision in Vietnam. Applying CB-SEM in the Theory of Planned Behavior, this papers analyzes relationships among 07 variables: information quality, streamer attractiveness, interaction quality, trustworthiness, streamer expertise, online purchase intention, and online purchase decision. Samples consist of 233 Gen Z residents in Ho Chi Minh City (April–June 2024) was analyzed using SPSS and AMOS.. The findings indicate that all examined variables positively impact Gen Z's live stream purchase decisions, helping to advance scholarly understanding and offering insights for businesses to effectively integrate live streaming into their omnichannel strategies.
