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26th International Conference on Information and Communications Security, ICICS 2024

作者： Spathoulas, Georgios Katsika, Angeliki Kavallieratos, Georgios Department of Information Security and Communication Technology Norwegian University of Science and Technology Gjøvik Norway Department of Computer Science and Biomedical Informatics University of Thessaly Lamia Greece

ISBN: (纸本)9789819787975

Cyber-physical systems (CPSs) have been used in different domains to enable automation, increase efficiency and effectiveness, and reduce the operational costs of traditional systems. CPSs come with several limitations and requirements that must be considered when designing their application to different domains. Artificial intelligence (AI) can facilitate the optimization of cyber-physical systems’ operation. However, integration of AI functionality into CPS is not easy due to limitations in hardware, software, and flexibility. The main contribution of the present paper is a novel approach for the use of remote AI services in CPSs. By employing zero-knowledge proofs, we protect the privacy of models and data and we can verify the integrity of the operations on the side of the AI service. Our experiments have shown that such an approach is feasible and brings significant offerings, such as verifiable remote AI inference for CPS. Our experiments have shown that currently available zero-knowledge implementations require large proof generation times, which hinder the effective application of remote AI services to real-world CPS. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Differential privacy

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Analyzing and Predicting the Helpfulness of Reviews in MOOCs Context Using Deep Learning 28th

Analyzing and Predicting the Helpfulness of Reviews in MOOCs...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

作者： Kastrati, Zenun Fatima, Sana Kurti, Arianit Daudpota, Sher Muhammad Imran, Ali Shariq Department of Informatics Linnaeus University Växjö351 95 Sweden Department of Computer Science Sukkur IBA University Sukkur65200 Pakistan Department of Computer Science Norwegian University of Science & Technology Gjøvik2815 Norway

Students' feedback is an essential part of the teaching-learning process and serves as an effective instrument for continuous improvement in educational environments. The insights gathered from students' experiences and perceptions expressed in reviews provide instructors with a valuable resource to enhance their teaching methods, instructional design, and overall classroom dynamics. However, students' reviews are often unclear, contradictory, and conflicting with each other, making their interpretation and use challenging. Therefore, this study proposes a novel deep learning-based approach that helps course designers and instructors effectively identify constructive and useful reviews. The approach leverages the integration of several attributes, including textual review, student satisfaction, meta-data of the course, and review-derived information such as sentiment, readability, and review depth. The approach is tested on a real-life dataset comprising 38,717 reviews gathered from the Coursera learning platform for the purpose of this study. The experimental results, with an F1-score of 0.91, suggest that the approach can be an effective tool for educators and instructional designers to identify helpful student reviews. © 2024 The Authors.

关键词： Contrastive Learning

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Exploring Multimedia Vector Spaces with vitrivr-VR 30th

Exploring Multimedia Vector Spaces with vitrivr-VR

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30th International Conference on MultiMedia Modeling, MMM 2024

作者： Spiess, Florian Rossetto, Luca Schuldt, Heiko Department of Mathematics and Computer Science University of Basel Basel Switzerland Department of Informatics University of Zurich Zurich Switzerland

ISBN: (纸本)9783031533013

Virtual reality (VR) interfaces are becoming more commonplace as the number of capable and affordable devices increases. However, VR user interfaces for common computing tasks often fail to take full advantage of the affordances provided by this immersive interface modality. New interfaces designed for VR must be developed in order to fully explore the possibilities for user interaction. In this paper, we present vitrivr-VR and the improvements made for its participation in the Video Browser Showdown (VBS) 2024. We describe the current state of vitrivr-VR, with a focus on a novel point cloud browsing interface and improvements made to its text input methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Content based retrieval

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Enhancing intrusion detection in IIoT: optimized CNN model with multi-class SMOTE balancing

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Neural Computing and Applications 2024年第24期36卷 14643-14659页

作者： Eid, Abdulrahman Mahmoud Soudan, Bassel Nassif, Ali Bou Injadat, MohammadNoor Department of Computer Engineering College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Department of Data Science and AI Faculty of Information Technology Zarqa University Zarqa Jordan

This work introduces an intrusion detection system (IDS) tailored for industrial internet of things (IIoT) environments based on an optimized convolutional neural network (CNN) model. The model is trained on a dataset that was balanced using a novel multi-class implementation of synthetic minority over-sampling technique (SMOTE) that ensures equal representation of all classes. Additionally, systematic optimization will be used to fine tune the hyperparameters of the CNN model and mitigate the effects of the increased size of the training dataset. Evaluation results will demonstrate substantial improvement in performance when the optimized CNN model is trained on the balanced dataset. The proposed IDS will be evaluated using the IIoT-specific WUSTL-IIOT-2021 dataset, and then its generalization capability will be verified using the non-domain specific UNSW_NB15 dataset. The model’s performance will be evaluated using accuracy, precision, recall, and F1-score metrics. The results will demonstrate that the proposed IDS is highly effective with performance exceeding 99.9% on all performance metrics. The IDS is also highly effective in detecting intrusion for generic IT networks achieving improvements in excess of 30% compared to the default baseline model. The results emphasize the versatility and effectiveness of the proposed IDS model, making it a reliable and adaptable solution for enhancing network security across diverse network environments. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Neural network models

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Analysis and Design of User Interface and User Experience Using Design science Research Methodology: A Case Study of the Quranic Reading and Writing Application 12

Analysis and Design of User Interface and User Experience Us...

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12th International Conference on Cyber and IT Service Management, CITSM 2024

作者： Subagja, Barra Arya Putra Masrurohagustin, Siti UmmiFenty Eka Muzayyana Rosyada, Dede Rahayu, Cindy Amriza, Rona Nisa Sofia Agustin, Fenty Eka Muzayyana Universitas Islam Negeri Syarif Hidayatullah Department of Informatics Jakarta Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia National Taiwan University of Science and Technology Department of Information Management Taiwan Department of Informatics Universitas Islam Negeri Syarif Hidayatullah Jakarta Indonesia

ISBN: (纸本)9798331528799

Reading and writing the Quran is a fundamental practice for Muslims worldwide. However, with the limitations of time, resources, and busy academic schedules, many Muslim students struggle to develop these essential skills. This research aims to design an intuitive and efficient Quran reading and writing application using User Interface (UI) and User Experience (UX) principles. The study employs the Design science Research Methodology (DSRM) to guide the development of the application. The research identifies the user needs through literature reviews, questionnaires, and interviews and presents a high-fidelity prototype that improves usability and engagement. Results indicate the application effectively meets the needs of users and provides a more attractive, efficient, and user-friendly experience. © 2024 IEEE.

关键词： User interfaces

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Reversible data hiding based on pixel segmentation and prediction for improving hiding capacity

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Signal, Image and Video Processing 2024年第6-7期18卷 5043-5059页

作者： Huang, Cheng-Ta Weng, Chi-Yao Zheng, Guo-Ting Weng, Hao-Yu International Bachelor Program in Informatics Yuan Ze University Taoyuan320315 Taiwan Department of Information Management Yuan Ze University Taoyuan320315 Taiwan Department of Computer Science and Information Engineering National Chiayi University Chiayi City600355 Taiwan Department of Computer Science and Artificial Intelligence National Pingtung University Pingtung900391 Taiwan Department of Computer Science and Information Engineering National Central University Taoyuan City320317 Taiwan

The idea of the traditional histogram shifting technique is to hide a message within the cover-image pixel distribution. However, the embedding capacity is limited by the peak point occurrences. To solve this problem, many reversible data hiding (RDH) techniques are developed to combine pixel prediction and histogram shifting to increase the embedding payload. In this paper, a RDH scheme based on chessboard prediction and pixel partitioning is proposed for enhancing the hiding payload. Pixel partitioning is used to separate a pixel into two parts: most significant bit and least significant bit. Then, the chessboard predictor is adopted to generate prediction errors and separate the pixels. Thereafter, histogram shifting is applied to embed the secret messages into prediction errors. Due to the high similarity of adjacent pixels in an image, the generated prediction errors are highly close to zero, resulting in a large embedding space. The experimental results indicate that the proposed method has superior performance in embedding capacity with acceptable image visual quality compared to existing schemes since it adopts the adaptive adjustment strategy to achieve this improved balance. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Pixels

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Vehicle Occurrence-Based Parking Space Detection

Vehicle Occurrence-Based Parking Space Detection

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： De Almeida, Paulo R. Lisboa Alves, Jeovane Honório Oliveira, Luiz S. Hochuli, Andre Gustavo Fröhlich, João V. Krauel, Rodrigo A. Department of Informatics Curitiba Brazil Graduate Program in Informatics Curitiba Brazil Department of Computer Science Joinville Brazil

ISBN: (纸本)9798350337020

Smart-parking solutions use sensors, cameras, and data analysis to improve parking efficiency and reduce traffic congestion. computer vision-based methods have been used extensively in recent years to tackle the problem of parking lot management, but most of the works assume that the parking spots are manually labeled, impacting the cost and feasibility of deployment. To fill this gap, this work presents an automatic parking space detection method, which receives a sequence of images of a parking lot and returns a list of coordinates identifying the detected parking spaces. The proposed method employs instance segmentation to identify cars and, using vehicle occurrence, generate a heat map of parking spaces. The results using twelve different subsets from the PKLot and CNRPark-EXT parking lot datasets show that the method achieved an AP25 score up to 95.60% and AP50 score up to 79.90%. © 2023 IEEE.

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Offshore Software Maintenance Outsourcing Process Model Validation:A Case Study Approach

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computers, Materials & Continua 2023年第3期74卷 5035-5048页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Adel Sulaiman Muhammad Akram Ahmad Salman Khan Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan

The successful execution and management of Offshore Software Maintenance Outsourcing(OSMO)can be very beneficial for OSMO vendors and the OSMO *** a lot of research on software outsourcing is going on,most of the existing literature on offshore outsourcing deals with the outsourcing of software development *** frameworks have been developed focusing on guiding software systemmanagers concerning offshore software ***,none of these studies delivered comprehensive guidelines for managing the whole process of *** is a considerable lack of research working on managing OSMO from a vendor’s ***,to find the best practices for managing an OSMO process,it is necessary to further investigate such complex and multifaceted phenomena from the vendor’s *** study validated the preliminary OSMO process model via a case study research *** results showed that the OSMO process model is applicable in an industrial setting with few *** industrial data collected during the case study enabled this paper to extend the preliminary OSMO process *** refined version of the OSMO processmodel has four major phases including(i)Project Assessment,(ii)SLA(iii)Execution,and(iv)Risk.

关键词： Offshore outsourcing process model model validation vendor challenges case study

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Modeling Hybrid Feature-Based Phishing Websites Detection Using Machine Learning Techniques

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Annals of Data science 2024年第1期11卷 217-242页

作者： Das Guptta, Sumitra Shahriar, Khandaker Tayef Alqahtani, Hamed Alsalman, Dheyaaldin Sarker, Iqbal H. Department of Computer Science and Engineering Chittagong University of Engineering & ampTechnology Chittagong4349 Bangladesh Unit of Cybersecurity Department of Computer Science Center of Artificial Intelligence King Khalid University Abha Saudi Arabia School of Engineering Computing and Informatics Dar Al-Hekma University Jeddah Saudi Arabia

In this paper, we mainly present a machine learning based approach to detect real-time phishing websites by taking into account URL and hyperlink based hybrid features to achieve high accuracy without relying on any third-party systems. In phishing, the attackers typically try to deceive internet users by masking a webpage as an official genuine webpage to steal sensitive information such as usernames, passwords, social security numbers, credit card information, etc. Anti-phishing solutions like blacklist or whitelist, heuristic, and visual similarity based methods cannot detect zero-hour phishing attacks or brand-new websites. Moreover, earlier approaches are complex and unsuitable for real-time environments due to the dependency on third-party sources, such as a search engine. Hence, detecting recently developed phishing websites in a real-time environment is a great challenge in the domain of cybersecurity. To overcome these problems, this paper proposes a hybrid feature based anti-phishing strategy that extracts features from URL and hyperlink information of client-side only. We also develop a new dataset for the purpose of conducting experiments using popular machine learning classification techniques. Our experimental result shows that the proposed phishing detection approach is more effective having higher detection accuracy of 99.17% with the XG Boost technique than traditional approaches. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.

关键词： Search engines

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On the Performance Evaluation of Mobility Model-Based GPSR Routing Protocol in Flying Ad hoc Networks 6

On the Performance Evaluation of Mobility Model-Based GPSR R...

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6th International Conference on Pattern Analysis and Intelligent Systems, PAIS 2024

作者： Bezziane, Mohamed Ben Sahraoui, Yesin Brik, Bouziane Mekkas, Lina Bougeurra, Sara Khaldi, Anouar University Kasdi Merbah Computer Science And Information Technologies Department Ouargla Algeria National Higher School of Artificial Intelligence Computer Science Algiers Algeria University of Sharjah College of Computing And Informatics Computer Science Department Sharjah United Arab Emirates

ISBN: (纸本)9798350350265

In recent times, we have witnessed the rapid and remarkable evolution of communication technologies, particularly in the domain of Flying Ad Hoc Networks (FANETs). This evolution has necessitated a thorough evaluation and significant enhancement of routing protocols to improve the overall performance of the system. To address the challenge of efficiently routing data in FANETs, where conventional methods may fall short during dynamic scenarios, the need for an effective framework becomes paramount in addressing these challenges. This paper aims to optimize routing efficiency in the context of FANETs, evaluating the performance of Greedy Perimeter Stateless Routing (GPSR) routing protocol under various mobility models, including Random Waypoint Mobility (RWPM), Mass Mobility, and Gauss Markov mobility models, to uncover their strengths and limitations. The simulation results reveal notable variations in performance indicators, including End-to-End delay, Packet Delivery Ratio, and Loss rate across various mobility models. However, Mass Mobility and Gauss-Markov Mobility exhibited consistent increases in Energy Consumption as the UAV count rose. On the other hand, Random Way Point Mobility demonstrated higher energy consumption compared to the former models. These findings offer valuable insights for selecting the most suitable mobility model for specific applications, and improving routing protocols, thereby advancing the reliability and effectiveness of Flying Ad Hoc environments. © 2024 IEEE.

关键词： Routing protocols

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