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8th International Conference on Business and Industrial Research, ICBIR 2023

作者： Kurniawan, Yohannes Jayamuni, James Henderson Kwandou, Natasya Anwar, Norizan Bina Nusantara University Information Systems Department School of Information Systems Jakarta11480 Indonesia School of Information Science College of Computing Informatics and Media Universiti Teknologi Mara Shah Alam40450 Malaysia

ISBN: (纸本)9798350399646

Metaverse refers to the next generation of the internet. Through the technology development, it allows users to interact with others by using 3D avatars. Education has been one of the highly compatible metaverse applications. Nowadays, the way of learning has also gradually changed and shifted to online with the collaboration of various tools. By using metaverse in the future, the learning process can be much more elevated with an immersive experience. Therefore, this study aimed to analyze user satisfaction using Mozilla Hub, an online tool that enables users to explore virtual worlds. We gathered the data by conducting a web-based simulation for 20 students to try the experiences and features. From the simulation, we asked some questions related to the experience of using it and analyzed the results by using a descriptive statistical method. The result showed that most participants gave a positive response toward the implementation of the metaverse. However, some improvement is still needed in developing the metaverse to be more optimally used. © 2023 IEEE.

关键词： E-learning

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Availability Analysis of Network-Attack-Resilient Byzantine Fault Tolerant systems

Availability Analysis of Network-Attack-Resilient Byzantine ...

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Reliable Distributed systems

作者： Aren Alyahya David Tipper Amy Babay Department of Informatics and Networked Systems School of Computing and Information University of Pittsburgh Pittsburgh PA

ISBN: (数字)9798331530037

ISBN: (纸本)9798331530044

Byzantine Fault Tolerant (BFT) systems are used in applications that need to maintain high availability even in the presence of failures or compromises. BFT systems are typically designed to tolerate a preconfigured threshold number of faulty replicas (f), where the $f$ faulty replicas may behave arbitrarily (potentially maliciously). However, as BFT system designs become more complex, it is important to evaluate the impact of such designs on the overall system availability with respect to standard crash faults. In this paper, we analyze three BFT systems that are designed to withstand both system compromises and network attacks: Spire, Confidential Spire, and Decoupled Spire. These network-attack-resilient BFT systems utilize a combination of on-premises and data center replicas to reduce cost and simplify deployment for system operators. We develop an availability model that accounts for differences between the availability of on- premises and data center replicas and analyze Spire, Confidential Spire, and Decoupled Spire under this model. Key system design insights from the analysis are that network-attack-resilient BFT configurations can meet the availability requirements of critical systems, as they provide higher availability than Classical BFT with less available servers. We show also that network-attack- resilient BFT configurations with fewer geographic sites provide higher availability, and that Confidential Spire has the highest availability, followed by Spire and then Decoupled Spire.

关键词： Data centers Analytical models Fault tolerance Costs Fault tolerant systems Data models Computer crashes Servers Standards

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Bibliometric Analysis of Trend in Metaverse Research 8

Bibliometric Analysis of Trend in Metaverse Research

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Cassandra, Cadelina Masrek, Mohamad Noorman Aman, Fadhilah School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia School of Information Science College of Computing Informatics and Media University Teknologi Mara Shah Alam Selangor Malaysia

ISBN: (纸本)9798350326093

Metaverse is currently going to be a popular topic. This study aims to investigate the research trends in metaverse topics to provide a new point of view for future research direction. This study performed a bibliometric analysis systematic literature review by reviewing the specific term in the Scopus database. The data were obtained from publish or perish app and analyzed using the VOSviewer Software. This research article was limited from 2018 - 2022, and 119 were analyzed using the VOSViewer Software. The result shows that the metaverse topic is increasing very fast in 2022. The most popular term in the title and abstract combination are Experience, Study, Application, and Education, which indicates the opportunity for future research, trend, and topic that the public and researchers are interested in. Meanwhile, the keyword of a metaverse in education is still limited, which opens new opportunities to be discussed in the future. © 2023 IEEE.

关键词： Application programs

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DeepDect: A Facial Deepfake Video Detection Application using Ensemble Learning 12

DeepDect: A Facial Deepfake Video Detection Application usin...

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12th IEEE Conference on systems, Process and Control, ICSPC 2024

作者： Tay, Wan Xin Chua, Hui Na Jasser, Muhammed Basheer Issa, Bayan Wong, Richard T.K. Sunway University No. 5 Jalan Universiti School of Engineering and Technology Department of Computing and Information Systems Selangor Darul Ehsan Bandar Sunway47500 Malaysia University of Aleppo Faculty of Informatics Engineering Syria

ISBN: (纸本)9798350391398

The emerging technology of deepfake video poses significant threats to information integrity and public trust. Deepfake videos come in various forms, including face swaps, lip-syncing, and full-body simulations. Detection algorithms may struggle to generalize across these different types of deepfakes, leading to lower effectiveness in real-world applications. An advanced deepfake detection system is developed using an ensemble approach, combining the strengths of three pre-trained Convolutional Neural Networks (CNNs)ResNeXt50, Xception, and EfficientNet-v2-with Long ShortTerm Memory (LSTM) layers to capture both spatial and temporal features from videos to improve detection accuracy. The ensemble model is further enhanced by incorporating additional features such as lip movements, eye blinks, head poses, and color contrasts to identify subtle inconsistencies in deepfake videos that are often ignored by traditional detection methods. The ensemble model achieves an accuracy of 84.06%, with a good balance between precision and recall, indicating its effectiveness in real-world applications. We developed DeepDect, a web application embedded with the ensemble model, to provide a user-friendly interface for deepfake detection by uploading videos or submitting URL links. The application includes educational content about deepfake techniques to raise user awareness about the potential dangers of deepfakes. © 2024 IEEE.

关键词： Convolutional neural networks

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PhD Forum: Challenges of Availability and Cost Assessments for Network-Attack-Resilient Byzantine systems

PhD Forum: Challenges of Availability and Cost Assessments f...

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Reliable Distributed systems

作者： Aren Alyahya Department of Informatics and Networked Systems School of Computing and Information University of Pittsburgh Pittsburgh PA

ISBN: (数字)9798331530037

ISBN: (纸本)9798331530044

Byzantine Fault Tolerant (BFT) system designs are developing to counter more sophisticated compromise and attack scenarios. Network-attack-resilient-BFT systems have developed frameworks for distributing replicas among multiple sites. Network-attack-resilient BFT systems are also resilient against sites' failures. These kinds of BFT systems are characterized by having a large number of servers, thus, some designs use a combination of data center and on-premises replicas to lower the overall costs. Availability analyses are inexpensive analytical methods that can be applied in the first stages of choosing the system design to measure the overall availability. The objective is to evaluate the availability of these new emerging BFT systems. The findings from this analysis could used as a guide in developing new system designs, or to establish a framework for selecting an existing BFT system. Two availability modelling techniques can be used to measure and understand the accessibility of the BFT systems: non-state space availability models and state space availability models. This paper highlights some of the challenges in developing such availability models. Conducting a cost analysis, combined with availability analysis, provides a clear understanding of the cost-benefit trade-off involved in investing in such systems.

关键词： Fault tolerance Data centers Protocols Fault tolerant systems Extraterrestrial measurements Computer crashes Complexity theory Servers Cost benefit analysis Resilience

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The Integration Between Social Media and Customer Relationship Management: The Reliability Analysis 8th

The Integration Between Social Media and Customer Relationsh...

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8th International Congress on Information and Communication Technology, ICICT 2023

作者： Anwar, Norizan Masrek, Mohamad Noorman Shuhidan, Shamila Mohamed Kurniawan, Yohannes School of Information Science College of Computing Informatics and Media Universiti Teknologi MARA Selangor Shah Alam40150 Malaysia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9789819932429

Most organization fully utilize social media (SocMed) for their operations in response to Pandemic COVID-19. SocMed, i.e., e-commerce has attracted more users to use and studies found that SocMed manages Customer Relationship and indirectly influences business performance. Customer Relationship Management (CRM) has been used for quite sometimes ago by most organizations. However, studies claimed that organization did not fully utilize the features of CRM. They just keep customer information without doing anything for future strategic planning, competitive advantage, decision-making, and much more. Therefore, this chapter aims to investigate the concept of integration between SocMed and CRM. SPSS version 26 has been used in analyzing the descriptive analysis, i.e., demographic profile and reliability analysis. The results show that all the variables surpass the cutoff value for the pilot test. This pilot study is giving an insight to the researchers in pursuing the data collection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Reliability analysis

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Cardiac Arrhythmia Disease Classifier Model Based on a Fuzzy Fusion Approach

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Computers, Materials & Continua 2023年第5期75卷 4485-4499页

作者： Fatma Taher Hamoud Alshammari Lobna Osman Mohamed Elhoseny Abdulaziz Shehab Eman Elayat College of Technological Innovation Zayed UniversityDubaiUAE Department of Information Systems College of Computer and Information SciencesJouf UniversitySakakaSaudi Arabia Department of Electronics and Communications Engineering Delta Higher Institute for Engineering&TechnologyMansouraEgypt College of Computing and Informatics University of SharjahSharjahUnited Arab Emirates Department of Information Systems Mansoura UniversityMansoura35516Egypt Department of Teacher Preparation Faculty of Specific EducationMansoura UniversityMansouraEgypt

Cardiac diseases are one of the greatest global health *** to the high annual mortality rates,cardiac diseases have attracted the attention of numerous researchers in recent *** article proposes a hybrid fuzzy fusion classification model for cardiac arrhythmia *** fusion model is utilized to optimally select the highest-ranked features generated by a variety of well-known feature-selection *** ensemble of classifiers is then applied to the fusion’s *** proposed model classifies the arrhythmia dataset from the University of California,Irvine into normal/abnormal classes as well as 16 classes of ***,at the preprocessing steps,for the miss-valued attributes,we used the average value in the linear attributes group by the same class and the most frequent value for nominal ***,in order to ensure the model optimality,we eliminated all attributes which have zero or constant values that might bias the results of utilized *** preprocessing step led to 161 out of 279 attributes(features).Thereafter,a fuzzy-based feature-selection fusion method is applied to fuse high-ranked features obtained from different heuristic feature-selection *** short,our study comprises three main blocks:(1)sensing data and preprocessing;(2)feature queuing,selection,and extraction;and(3)the predictive *** proposed method improves classification performance in terms of accuracy,F1measure,recall,and precision when compared to state-of-the-art *** achieves 98.5%accuracy for binary class mode and 98.9%accuracy for categorized class mode.

关键词： Cardiac arrhythmia preprocessing missing values classification model fusion

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High-Secure Data Collection in IoT Sensor Networks using Homomorphic Encryption 16

High-Secure Data Collection in IoT Sensor Networks using Hom...

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Sensors and systems for Space Applications XVI 2023

作者： Nguyen, Tuy Tan Phan, Quoc Bao Bui, Ngoc Thang daCunha, Carlo School of Informatics Computing and Cyber Systems Northern Arizona University FlagstaffAZ86011 United States Department of Radiology Mayo Clinic RochesterMN55902 United States

ISBN: (纸本)9781510662087

In wireless sensor networks, sensor nodes are deployed in open environments to gather and send collected data to a remote server. During the data transmission process, the collected data is vulnerable to security risks, making it crucial to encrypt the data to prevent it from falling into the wrong hands. This paper proposes a new approach that integrates homomorphic encryption (HE) algorithms into the sensor devices, allowing the data collected by the sensors to be encrypted before transmission. By utilizing HE in the sensor networks, the server can execute calculations on the encrypted data without requiring decryption. To implement the HE function, we use the Simple Encrypted Arithmetic Library (SEAL), which the Microsoft Cryptography Research Group developed. We evaluated the HE-based data collection scheme in IoT sensor networks with various network topologies to assess network lifetime, communication distance, and data collection latency. © 2023 SPIE.

关键词： Cryptography

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Empirical Evaluations of Machine Learning Effectiveness in Detecting Web Application Attacks 7th

Empirical Evaluations of Machine Learning Effectiveness in...

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7th EAI International Conference on Future Access Enablers of Ubiquitous and Intelligent Infrastructures, EAI FABULOUS 2023

作者： Ismail, Muhusina Alrabaee, Saed Harous, Saad Choo, Kim-Kwang Raymond Department of Information Systems and Security CIT United Arab Emirates University Al Ain United Arab Emirates Department of Computer Science College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Department of Information Systems and Cyber Security University of Texas at San Antonio San Antonio United States

ISBN: (纸本)9783031500503

Web applications remain a significant attack vector for cybercriminals seeking to exploit application vulnerabilities and gain unauthorized access to privileged data. In this research, we evaluate the efficacy of eight supervised machine learning algorithms - Naive Bayes, Decision Tree, AdaBoost, Random Forest, Logistic Regression, K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Artificial Neural Network (ANN) - in detecting and countering web application attacks. Our results indicate that KNN and Random Forest classifiers achieve an accuracy rate of 89% and an area under the curve of 94% on the CSIC HTTP dataset, a commonly used benchmark in the field. Meanwhile, the Naive Bayes classifier proves the most efficient, taking the least computational time when differentiating between malicious and benign HTTP requests. These findings may help direct future efforts towards more efficient, machine learning-driven defenses against web application attacks. © ICST Institute for Computer Sciences, Social informatics and Telecommunications Engineering 2024.

关键词： Machine Learning Web Attacks Web Vulnerabilities

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Incompletion Rate Factors in MOOC: A Systematic Literature Review

Incompletion Rate Factors in MOOC: A Systematic Literature R...

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2023 International Conference on University Teaching and Learning, InCULT 2023

作者： Karsen, Marisa Uzir, Nora'ayu Ahmad Abdul Rahman, Safawi Bin Kurniawan, Yohannes School of Information Science College of Computing Informatics and Mathematics University Teknologi Mara Information Systems Department Puncak Perdana Campus Malaysia School of Information Systems Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9798350315745

Massive Online Open Courses (MOOCs) that are based on open e-learning courses might be one of the most versatile ways to offer access to quality education, regardless of the learners background. However, literature indicate that less than 10% of learners completed the MOOC courses they registered. Despite the efficient creation, and distribution of knowledge by taking advantage of advanced educational technology, yet the minimal completion rate in MOOCs remains unsolved. With the research question formulated as 'Why is the MOOCs completion rate among learners and professionals in higher education institution is low?' this paper presents the systematic literature review in which the researchers identified the factors that the learners acknowledged as the reason in the MOOC incompletion. Researchers also identified the factors that influence learners to complete MOOC courses and the research instruments were used by the prior studies to examine the motivation factors of learners in completing the MOOC courses. Based on the findings of the study and through the synthesis of the literature, this study presents a new perspective that can be used as a point of reference for future research and development to promote a higher MOOC completion rate. © 2023 IEEE.

关键词： Motivation

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