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Multi-Attribute Decision-Making for Intrusion Detection Systems: A Systematic Review

International Journal of information technology and Decision Making 2023年第1期22卷 589-636页

作者： Alamleh, Amneh Albahri, O.S. Zaidan, A.A. Alamoodi, A.H. Albahri, A.S. Zaidan, B.B. Qahtan, Sarah Binti Ismail, Amelia Ritahani Malik, R.Q. Baqer, M.J. Jasim, Ali Najm Al-Samarraay, Mohammed S. Department of Computing Faculty of Arts Computing and Creative Industry Universiti Pendidikan Sultan Idris Tanjung Malim35900 Malaysia Computer Techniques Engineering Department Mazaya University College Nasiriyah Iraq Faculty of Engineering and IT The British University in Dubai United Arab Emirates Baghdad Iraq Future Technology Research Center National Yunlin University of Science and Technology Douliou Taiwan Department of Computer Center Middle Technical University's Baghdad Iraq International Islamic University Malaysia Kuala Lumpur Malaysia Department of Artificial Intelligence Faculty of Information Technology Zarqa University Zarqa Jordan Department of Medical Instrumentation Techniques Engineering Al-Mustaqbal University College Hillah Iraq Foundation of Alshuhda Baghdad Iraq

Intrusion detection systems (IDSs) employ sophisticated security techniques to detect malicious activities on hosts and/or networks. IDSs have been utilized to ensure the security of computer and network systems. However, numerous evaluation and selection issues related to several cybersecurity aspects of IDSs were solved using a decision support approach. The approach most often utilized for decision support in this regard is multi-Attribute decision-making (MADM). MADM can aid in selecting the most optimal solution from a huge pool of available alternatives when the appropriate evaluation attributes are provided. The openness of the MADM methods in solving numerous cybersecurity issues makes it largely efficient for IDS applications. We must first understand the available solutions and gaps in this area of research to provide an insightful analysis of the combination of MADM techniques with IDS and support researchers. Therefore, this study conducts a systematic review to organize the research landscape into a consistent taxonomy. A total of 28 articles were considered for this taxonomy and were classified into three main categories: data analysis and detection (n=4), response selection (n=7) and IDS evaluation (n=17). Each category was thoroughly analyzed in terms of a variety of aspects, including the issues and challenges confronted, as well as the contributions of each study. Furthermore, the datasets, evaluation attributes, MADM methods, evaluation and validation and bibliography analysis used by the selected articles are discussed. In this study, we highlighted the existing perspective and opportunities for MADM in the IDS literature through a systematic review, providing researchers with a valuable reference. © 2023 World Scientific Publishing Company.

关键词： Taxonomies

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Rooted Tree Optimization for Wind Turbine Optimum Control Based on Energy Storage System

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computers, Materials & Continua 2023年第2期74卷 3977-3996页

作者： Billel Meghni Afaf Benamor Oussama Hachana Ahmad Taher Azar Amira Boulmaiz Salah Saad El-Sayed M.El-kenawy Nashwa Ahmad Kamal Suliman Mohamed Fati Naglaa K.Bahgaat Department of Electrical Engineering Badji Mokhtar UniversityLSEM LaboratoryAnnaba23000Algeria Department of Electrical Engineering Biskra UniversityLGEB LaboratoryBiskra07000Algeria Department of Drilling and Rig Mechanics Ksadi Merbah UniversityOuargla30000Algeria College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityBenha13518Egypt Department of Electronics University of Badji MokhtarLERICA LaboratoryAnnaba23000Algeria Delta Higher Institute for Engineering&Technology(DHIET) Mansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Faculty of Engineering Cairo UniversityGiza12613Egypt Department of Communications and Electronics Engineering Faculty of EngineeringCanadian International College(CIC)ElShiekh ZayedEgypt

The integration of wind turbines(WTs)in variable speed drive systems belongs to the main factors causing lowstability in electrical ***,in order to avoid this issue,WTs hybridization with a storage system is a *** paper investigates WT system operating at variable *** system contains of a permanent magnet synchronous generator(PMSG)supported by a battery storage system(BSS).To enhance the quality of active and reactive power injected into the network,direct power control(DPC)scheme utilizing space-vector modulation(SVM)technique based on proportional-integral(PI)control is ***,to improve the rendition of this method(DPC-SVM-PI),the rooted tree optimization technique(RTO)algorithm-based controller parameter identification is used to achieve PI optimal *** compare the performance ofRTO-based controllers,they were implemented and tested along with some other popular controllers under different working *** obtained results have shown the supremacy of the suggested PIRTO algorithm compared to competing controllers regarding total harmonic distortion(THD),overshoot percentage,settling time,rise time,average active power value,overall efficiency,and active power steadystate error.

关键词： Rooted tree optimization(RTO)method direct power control(DPC) wind turbine(WT) proportional integral(PI) PMSG

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Text-to-Ontology Mapping via Natural Language Processing Models 22

Text-to-Ontology Mapping via Natural Language Processing Mod...

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22nd Conference information Technologies - Applications and Theory, ITAT 2022

作者： Yorsh, Uladzislau Behr, Alexander S. Kockmann, Norbert Holeňa, Martin Faculty of Information Technology CTU Prague Czech Republic Faculty of Biochemical and Chemical Engineering TU Dortmund University Germany Institute of Computer Science Czech Academy of Sciences Prague Czech Republic Leibniz Institute for Catalysis Rostock Germany

The paper presents work in progress attempting to solve a text-to-ontology mapping problem. While ontologies are being created as formal specifications of shared conceptualizations of application domains, different users often create different ontologies to represent the same domain. For better reasoning about concepts in scientific papers, it is desired to pick the ontology which best matches concepts present in the input text. We have started to automatize this process and attack the problem by utilizing state-of-the-art NLP tools and neural networks. Given a specific set of ontologies, we experiment with different training pipelines for NLP machine learning models with the aim to construct representative embeddings for the text-to-ontology matching task. We assess the final result through visualizing the latent space and exploring the mappings between an input text and ontology classes. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Ontology

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Multi-disciplinary Trends in Artificial Intelligence 1

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丛书名： Lecture Notes in computer Science

1000年

作者： M. Narasimha Murty Xiangjian He Raghavendra Rao Chillarige Paul Weng

ISBN: (数字)9783319133652

ISBN: (纸本)9783319133645

This book constitutes the refereed conference proceedings of the 8th International Conference on Multi-disciplinary Trends in Artificial Intelligence, MIWAI 2014, held in Bangalore, India, in December 2014. The 22 revised full papers were carefully reviewed and selected from 44 submissions. The papers feature a wide range of topics covering both theory, methods and tools as well as their diverse applications in numerous domains.

关键词： Artificial Intelligence Data Mining and Knowledge Discovery Image Processing and computer Vision Algorithm Analysis and Problem Complexity information Systems Applications (incl. Internet)

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Driver behavior detection based on multi GNSS technology 35th

Driver behavior detection based on multi GNSS technology

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35th FISITA World Automotive Congress, 2014

作者： Chatranuwathana, Sunhapos Thitipatanapong, Raksit Noomwongs, Nuksit Phondeenana, Peerapat Klongnaivai, Sanya Smart Mobility Research Center Department of Mechanical Engineering Faculty of Engineering Chulalongkron University Bangkok Thailand Space Technologies Group Information Communication & Computing Research Unit National Electronic & Computer Technology Center Pathumtani Thailand

The driver behavior is the key to safe mobility. In general, vehicle maneuvers can be determined from acceleration of the vehicle. Physically, the acceleration and brake can be detected with longitudinal acceleration while turning and lane change can be detected with lateral acceleration. Normally, IMU (inertia measurement unit) has been designated to get those data. However, the I MU is not convenience to install in the vehicles especially as aftermarket additional parts. Nowadays, navigation system technologies have been much improved both on availability and accuracy with combination of multiple navigation satellite systems. Normally, it’s called Multi-GNSS (multiple global navigation satellite system). With decimeter precision and the update rate scale up to 10-Hz, the GNSS would be an alternative solution for driver behavior detection. This paper applied the behavior detection algorithm from previous study [3], and enhanced with advance Multi-GNSS;precise point position (PPP) technique. The advantage of PPP over conventional navigation is decimeter accuracy without direct connection to reference base station. The experimental Multi-GNSS receiver was JAVAD Delta G3T that installed on a utility vehicle. The navigation data was post-processed with the open source RTKLIB 2.4.2 software. On the other hand, the reference vehicle dynamic measurement system was VBOX 3LSi with integrated IMU. As results, the PPP improved the chance of detection of the algorithm from nothing in lane-changing to half of total incidents and significant improved on fault detected. Furthermore, the turning of vehicle which can be detected with conventional GPS was slightly improved with PPP by 15%. The limitations of current study are satellite availability that new block of navigation satellite still in commissioning phase and limited. Moreover, all experiments were carried out in Pathumthani, Thailand. Different city, location and satellite systems may obtain different results. In this pap

关键词： Global positioning system

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Clustering Approach for Modeling Course Difficulty Level in Adaptive Learning

Clustering Approach for Modeling Course Difficulty Level in ...

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2024 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2024

作者： Imamah Yuhana, Umi Laili Djunaidy, Arif Pardede, Eric Purnomo, Mauridhi Hery Departement of Electrical Engineering Faculty of Intelligent Electrical Informatics Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Departement of Informatics Faculty of Intelligent Electrical Informatics Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Departement of Information Systems Faculty of Intelligent Electrical Informatics Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Departement of Computer Science Information Technology La Trobe University BundooraVIC3086 Australia

ISBN: (纸本)9798350322996

The variations in students' abilities present challenges in achieving desired learning outcomes. Students exhibit different levels of comprehension regarding the complexity of learning materials. In this study, we aim to model the difficulty levels of learning materials using a clustering approach to offer personalized learning material recommendations within an adaptive learning framework. Data were collected from student scores of Data Structure course obtained between 2020 and 2022 at the University of Trunojoyo Madura. The dataset modeling process adheres to the CRISP-DM Methodology, employing the K-Means clustering method and Euclidean Distance. We employed the Within-Cluster Sum of Squares (WCSS) metric and silhouette score to identify the optimal K-value, which resulted in a value of 5, accompanied by a silhouette score of 0.629. Our analysis pinpointed Stack and Deque as the easiest, while Linked List emerged as the most challenging course material. Accordingly, we will assign a label of 1 to the easiest materials, 2 to those of medium difficulty, and 3 to the most challenging ones. These labels will serve as criteria for recommending suitable learning materials to students based on their knowledge level. We will assess the ratio between the overall knowledge level score and the difficulty level of the material. The ratio value will serve as a reference for determining material recommendations for students. Materials categorized with the highest difficulty levels are exclusively suggested to students demonstrating faster learning abilities with a high value of ratio, and vice versa. This approach is feasible for implementation in adaptive learning. © 2024 IEEE.

关键词： Contrastive Learning

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Cryptology and Network Security 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Swee-Huay Heng Rebecca N. Wright Bok-Min Goi

ISBN: (数字)9783642176197

ISBN: (纸本)9783642176180

The 9th International Conference on Cryptology and Network Security (CANS 2010) was held in Kuala Lumpur, Malaysia during December 12–14, 2010. The conference was co-organized by the Multimedia University (MMU), Malaysia, and Universiti Tunku Abdul Rahman (UTAR), Malaysia. The conference received 64 submissions from 22 countries, out of which 21 were accepted after a careful and thorough review process. These proceedings also contain abstracts for two invited talks. All submissions were reviewed by at least three members of the Program Committee; those authored or co-authored by Program Committee members were reviewed by at least ?ve reviewers. P- gram Committee members were allowed to use external reviewers to assist with their reviews, but remained responsible for the contents of the review and r- resenting papers during the discussion and decision making. The review phase was followed by a 10-day discussion phase in which each paper with at least one supporting review was discussed, additional experts were consulted where needed, and ?nal decisions were made. We thank the Program Committee for their hard work in selecting the p- gram. We also thank the external reviewers who assisted with reviewing and the CANS Steering Committee for their help. We thank Shai Halevi for use of his Web-Submission-and-Review software that was used for the electronic s- mission and review of the submitted papers, and we thank the International Association for Cryptologic Research (IACR) for Web hosting of the software.

关键词： Cryptology computer Communication Networks Programming Techniques Discrete Mathematics in computer Science Coding and information Theory Data Structures and information Theory

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Enhancing Image Security with Rossler Attractor-Based Encryption

Enhancing Image Security with Rossler Attractor-Based Encryp...

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Cyber Resilience (ICCR), International Conference on

作者： Hazem Al-Najjar Nadia Al-Rousan Department of Computer science Faculty of information technology University of Petra Amman Jordan Department of Computer Engineering Faculty of electrical Engineering and information systems German Jordanian University

ISBN: (数字)9798350394962

ISBN: (纸本)9798350394979

we introduced image encryption algorithms with high sensitivity, such that even a single alteration in a plain-text image would result in a complete transformation of the ciphered image. The first algorithm employed pixel values in a substitution approach, whereas the second algorithm utilized pixel values to generate chaotic function keys. Additionally, we employed a Rossler chaotic function with pixel data to generate chaotic values for the shuffling and substitution processes. After subjecting these algorithms to rigorous testing using standard metrics, our experiments revealed the efficiency of the algorithms in image encryption. Notably, even a minute change in the original image resulted in a vastly different ciphered image. These proposed algorithms underscored the effectiveness of integrating chaotic functions with pixel information, significantly enhancing image security.

关键词： Sensitivity Approximation algorithms Encryption Standards Testing Resilience

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Attention Mechanism for Fashion Image Captioning 5th

Attention Mechanism for Fashion Image Captioning

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5th International Conference on Green technology and Sustainable Development, GTSD 2020

作者： Nguyen, Bao T. Prakash, Om Vo, Anh H. Faculty of Information Technology Ho Chi Minh City University of Technology and Education Ho Chi Minh City Viet Nam Department of Computer Science and Engineering H.N.B Garhwal University Srinagar India Artificial Intelligence Laboratory Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam

ISBN: (纸本)9783030623234

Image captioning tries to make computer learn to understand the visual content of a given image and produce one or more description sentences. Recently, with the help from rapid development of deep learning, image captioning has become an active research. The encoder-decoder architecture is commonly considered as the baseline method to address image captioning. This model focuses on recognizing objects and the relationship among these objects. However, with fashion images, the generated sentence should not only describe items inside the input image, but also mention item attributes such as texture, fabric, shape, style, etc. This requirement of fashion image captioning is not able to be solved by the image-captioning method based on the traditional encoder-decoder architecture. Our study addresses this issue by proposing an image captioning model based on the attention mechanism for fashion image which is able to cover both items and the relationship among the detailed attributes of items. We introduce an efficient framework for fashion image captioning that incorporates spatial attention inside the traditional encoder-decoder architecture. Our model generates fashion image captions using the spatial attention mechanism, which dynamically modulates the sentence generation context in multi-layer feature maps. Experiments were conducted on Fashion-Gen, one of state-of-the-art fashion image dataset, and achieved CIDEr/ROUGE-L/BLEU-4 scores of 0.913, 0.502, and 0.221, respectively. Based on experiments, it is consistently presented that our proposed model has significantly improved the performance of fashion-image captioning task, and it even surpasses the baseline methods on the same fashion benchmark dataset. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Recurrent neural networks

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Lower and upper approximations in data tables containing possibilistic information

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作者： Nakata, Michinori Sakai, Hiroshi Faculty of Management and Information Science Josai International University 1 Gumyo Togane Chiba 283-8555 Japan Department of Mathematics and Computer Aided Sciences Faculty of Engineering Kyushu Institute of Technology Tobata Kitakyushu 804-8550 Japan

ISBN: (纸本)9783540716624

An extended method of rough sets, called a method of weighted equivalence classes, is applied to a data table containing imprecise values expressed in a possibility distribution. An indiscerniblity degree between objects is calculated. A family of weighted equivalence classes is obtained via indiscernible classes from a binary relation for indiscernibility between objects. Each equivalence class in the family is accompanied by a possibilistic degree to which it is an actual one. By using the family of weighted equivalence classes we derive a lower approximation and an upper approximation. These approximations coincide with those obtained from methods of possible worlds. Therefore, the method of weighted equivalence classes is justified. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Approximation theory

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