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Cyber-Syndrome:Concept,Theoretical Characterization,and Control Mechanism

Tsinghua science and Technology 2024年第3期29卷 721-735页

作者： Feifei Shi Huansheng Ning Liming Chen Sahraoui Dhelim School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Faculty of Computing Ulster UniversityNewtownabbeyBT370QBUK School of Computer Science University College DublinDublinD04 V1W8Ireland

The prevalence of social media and mobile computing has led to intensive user engagement in the emergent Cyber-Physical-Social-Thinking(CPST)***,the easy access,the lack of governance,and excessive use has generated a raft of new behaviors within CPST,which affects users’physical,social,and mental *** this paper,we conceive the Cyber-Syndrome concept to denote the collection of cyber disorders due to excessive or problematic Cyberspace interactions based on CPST *** we characterize the Cyber-Syndrome concept in terms of Maslow’s theory of Needs,from which we establish an in-depth theoretical understanding of Cyber-Syndrome from its etiology,formation,symptoms,and ***,we propose an entropy-based Cyber-Syndrome control mechanism for its computation and *** goal of this study is to give new insights into this rising phenomenon and offer guidance for further research and development.

关键词： Cyber-Syndrome cyber-physical systems Cyber-Physical-Social-Thinking(CPST)space Maslow’sHierarchy of Needs entropy

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Physical-layer security for primary users in 5G underlay cognitive radio system via artificial-noise-aided by secondary users

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International Journal of computers and Applications 2024年第9期46卷 702-714页

作者： Al-Rjoob, Ayat M. Ababnah, Ahmad A. Al-Mistarihi, Mamoun F. Darabkh, Khalid A. Electrical and Communication Engineering Department German-Jordanian University and Technology Amman Jordan Electrical Engineering Department Faculty of Engineering Jordan University of Science and Technology Irbid Jordan Computer Engineering Department School of Engineering The University of Jordan Amman Jordan

The advent of the Internet of Things (IoT) has revolutionized connectivity by interconnecting a vast array of devices, underscoring the critical need for robust data security, particularly at the Physical Layer Security (PLS). Ensuring data confidentiality and integrity during wireless communications poses a primary challenge in IoT environments. Additionally, within the constrained frequency bands available, Cognitive Radio Networks (CRNs) has emerged as an urgent necessity to optimize spectrum utilization. This technology enables intelligent management of radio frequencies, enhancing network efficiency and adaptability to dynamic environmental changes. In this research, we focus on examining the PLS for the primary channel within the underlying CRNs. Our proposed model involves a primary source-destination pair and a secondary transmitter-receiver pair sharing the same frequency band simultaneously. In the presence of a common eavesdropper, the primary concern lies in securing the primary link communication. The secondary user (SU) acts as cooperative jamming, strategically allocating a portion of its transmission power to transmit artificial interference, thus confusing the eavesdropper and protecting the primary user's (PU) communication. The transmit power of the SU is regulated by the maximum interference power tolerated by the primary network's receiver. To evaluate the effectiveness of our proposed protocol, we develop closed-form mathematical expressions for intercept probability ((Formula presented.)) and outage probability (OP) along the primary communication link. Additionally, we derive mathematical expressions for OP along the secondary communications network. Furthermore, we investigate the impact of transmit power allocation on intercept and outage probabilities across various links. Through both simulation and theoretical analysis, our protocol aims to enhance protection and outage efficiency for the primary link while ensuring appropriate secondary

关键词： Cognitive radio

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iLIAC: An approach of identifying dissimilar groups on unstructured numerical image dataset using improved agglomerative clustering technique

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Multimedia Tools and Applications 2024年第39期83卷 86359-86381页

作者： S, Sreedhar Kumar Ahmed, Syed Thouheed Fathima, Afifa Salsabil Mathivanan, Sandeep Kumar Jayagopal, Prabhu Saif, Abdu Gupta, Sachin Kumar Sinha, Garima Department of Computer Science and Engineering School of Engineering and Technology CMR University Karnataka Bengaluru India Department of Electrical Engineering Indian Institute of Technology Hyderabad Telangana Kandi India School of Computer Science and Engineering REVA University Bangalore India School of Computer Science and Engineering Galgotias University Uttar Pradesh Greater Noida203201 India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Communication and Computer Engineering Faculty of Engineering and IT Taiz University Taiz Yemen Katra India Department of Computer Science Engineering Jain University Bangalore India

Unstructured Numerical Image Dataset Separation (UNIDS) method employing an enhanced unsupervised clustering technique. The objective is to delineate an optimal number of distinct groups within the input grayscale (G-S) image content, utilizing the improved limited iteration agglomerative clustering (iLIAC) clustering technique for the separation and enhancement of picture elements. The UNIDS method is structured into two primary stages: partitioning and validation. In the partitioning stage, the UNIDS method identifies an appropriate number of discrete clusters within the grayscale image using the iLIAC technique, eliminating the need for predetermined procedures. Subsequently, the method evaluates the similarity and deviation among data elements within the same group in the resultant image dataset. Additionally, it assesses the proximity and inters severance among clusters in the outcome of the image dataset through the partitioning process. Empirical results indicate that the UNIDS system excels in the spontaneous identification of an optimal number of discrete clusters within the input G-S image. The system demonstrates superior thickness, reduced deviation among data elements within the same cluster, increased inter-separation, and diminished inter-closeness between cluster elements. Furthermore, empirical analysis establishes the superior performance of the UNIDS approach compared to existing clustering techniques. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Iterative methods

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Beyond Precision and Recall: Measuring Search Engine Consistency Using Rank Stability

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IEEE Access 2025年 13卷 92242-92259页

作者： Lakshmi, S. Thinakaran, Rajermani Batri, Krishnan Sowrirajan, R. Murugan, Sivaram Jain University Department of Electronics and Communication Engineering Karnataka Bengaluru India INTI International University Faculty of Data Science and Information Technology Negeri Sembilan Malaysia Jain University School of Computer Science and Engineering Karnataka Bengaluru India Dr. N.G.P. Arts and Science College Department of Mathematics Tamil Nadu Coimbatore India Sivas University of Science and Technology Faculty of Engineering and Natural Sciences Department of Computer Engineering Sivas58000 Turkey

Traditional information retrieval metrics such as precision, recall, and F-measure assess document relevance but fail to capture the stability of search rankings. Search engines frequently update their algorithms, leading to variations in retrieved documents and their rankings across identical queries. This study introduces a novel rank correlation measure that quantifies search result consistency by analyzing rank fluctuations in repeated queries, serving as a proxy for temporally separated searches. The proposed approach distinguishes between overlapping and non-overlapping documents, providing a detailed measure of ranking stability. Empirical evaluations comparing Google and Bing reveal that Google exhibits greater rank fluctuations for non-overlapping documents, whereas both search engines maintain relatively stable rankings for overlapping documents. These findings highlight the importance of rank-based evaluation frameworks in search engine analysis, extending beyond conventional retrieval metrics. By incorporating stability assessments, this research enhances the methodology for evaluating search consistency in dynamic web environments, contributing to process innovation in information retrieval (SDG 9: Industry, Innovation, and Infrastructure) and promoting fair, reliable access to information (SDG 16: Peace, Justice, and Strong Institutions). © 2013 IEEE.

关键词： Online searching

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DialTest-EA: An Enhanced Fuzzing Approach With Energy Adjustment for Dialogue Systems via Metamorphic Testing

DialTest-EA: An Enhanced Fuzzing Approach With Energy Adjust...

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作者： Chen, Haibo Chen, Jinfu Wu, Yucheng Cai, Saihua Ahmad, Bilal Huang, Rubing Wang, Shengran Zhang, Chi School of Computer Science and Communication Engineering Jiangsu Key Laboratory of Security Technology Industrial Cyberspace Jiangsu University Zhenjiang China School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology China

Deep neural networks (DNNs) possess potent feature learning capability, enabling them to comprehend natural language, which strongly support developing dialogue systems. However, dialogue systems usually perform incorrect behaviours in some corner cases, which may cause misunderstanding or economic loss. To test and debug dialogue systems, a popular fuzzing framework by metamorphic testing with Gini impurity guidance is proposed, namely, DialTest. However, DialTest treats all seeds (the initial test inputs to generate the mutated test inputs) equally during the fuzzing process and does not differentiate seeds, resulting in a certain limitation to its incorrect behaviour detection capability. In this paper, we propose to enhance the DialTest by applying a lightweight energy adjustment strategy called DialTest with Energy Adjustment (DialTest-EA). DialTest-EA employs the ant colony optimization algorithm (ACO) to adjust the mutation energy of each seed adaptively, ensuring that potential seeds have more opportunities to generate subsequent test inputs. To evaluate the effectiveness of the proposed DialTest-EA, we conduct a series of comparisons with the original DialTest and random mutation strategy. The experimental results show that the proposed DialTest-EA outperforms the compared methods both in the intent detection and slot filling tasks. Compared with the original DialTest, the intent detection accuracy of generated test cases by the proposed method is reduced by more than 14%, and the slot filling accuracy is reduced by more than 8%. © 2024 John Wiley & Sons Ltd.

关键词： Ant colony optimization

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A transformer based real-time photo captioning framework for visually impaired people with visual attention

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Multimedia Tools and Applications 2024年第41期83卷 88859-88878页

作者： Muhammed Kunju, Abubeker Kiliyanal Baskar, S. Zafar, Sherin A R, Bushara S, Rinesh A, Shafeena Karim Kerala Kanjirapally India Faculty of Engineering Department of Electronics and Communication Engineering Karpagam Academy of Higher Education Coimbatore India Department of Computer and Electronics Engineering SEST- Jamia Hamdard New Delhi India Department of Electronics and Communication Engineering KMEA College of Engineering Kerala Cochin India Department of Computer Science and Engineering V.S.B College of Engineering Technical Campus Coimbatore India

In recent years, transformer-based photo captioning frameworks plays a crucial role in improving individuals’ overall well-being, self-reliance, and inclusivity by giving them access to visual content via written and voiced explanations. This research investigates a two-layer transformer architecture to capture extensive relationships in visual data effectively. Using a two-layer transformer design, visual attention mechanism enables the model to autonomously identify relevant regions within a picture while generating a particular word within the anticipated caption. To get the features from the images, a pre-trained Inception V3 model is used, and the feature maps are extracted from the final convolutional block. The dataset used in this research was Flick8k, Flick30k, among bespoke datasets. The model was trained on a TPU platform and implemented on a Raspberry Pi 4B graphics processing unit. To assess the efficacy of the two-layer transformer model for photo captioning, a series of experiments were undertaken using benchmark datasets and with state-of-the-art models. The quality of the generated captions was evaluated using quantitative criteria such as BLEU, BLEUR, ROUGE and F1 score. Furthermore, a series of qualitative assessments were conducted, employing human evaluators, to measure the overall coherence, and fluency of the captions. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： computer vision

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Design and Analysis of a UWB Slotted Vivaldi Antenna for Microwave Imaging Applications

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IEIE Transactions on Smart Processing and Computing 2023年第4期12卷 350-357页

作者： Paul, Liton Chandra Majumder, Akash Rani, Tithi Hossain, Md. Najmul Rahim, Md. Abdur Shin, Jungpil Yun, Keun Soo Department of Electrical Electronic and Communication Engineering Faculty of Engineering and Technology Pabna University of Science and Technology Pabna6600 Bangladesh Department of Electronics & Telecommunication Engineering Faculty of Electrical & Computer Engineering Rajshahi University of Engineering & Technology Rajshahi6204 Bangladesh Department of Computer Science and Engineering Faculty of Engineering and Technology Pabna University of Science and Technology Pabna6600 Bangladesh School of Computer Science and Engineering The University of Aizu / Fukushima Aizuwakamatsu965-8580 Japan School of Computer and Information Technology Ulsan College / Dong-gu Ulsan44610 Korea Republic of

An ultra-wideband (UWB) slotted compact Vivaldi antenna with a microstrip line feed was evaluated for microwave imaging (MI) applications. The recommended FR4 substrate-based Vivaldi antenna is 50×50×1.5 mm3 in size. The proposed compact Vivaldi antenna showed good radiation characteristics and spanned an ultra-wide bandwidth of 10 GHz, ranging from 3.6 to 13.6 GHz, using a microstrip line feed with a radial stub, tapered slots, and resonant cavities. After analyzing the simulation findings, the proposed compact slotted UWB Vivaldi antenna was compared with the basic Vivaldi antenna. The maximum gain and efficiency were 7.35 dB and 82%, respectively. The antenna was simulated in the time domain using the computer simulation technology (CST) microwave studio. The frequency domain solver was also used for cross-validation, and the results were equally good. In conclusion, the proposed compact Vivaldi antenna is a good option for microwave imaging applications. © 2023 The Institute of Electronics and Information Engineers.

关键词： Cavity resonators

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Enhancing the blockchain interoperability through federated learning with directed acyclic graph

IET Blockchain

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IET Blockchain 2023年第4期3卷 238-248页

作者： Xia, Feng Kaiye, Li Songze, Wu yan, Xin Faculty of Data Science City University of Macau Avenida Padre Tomás Pereira China School of Computer Science and Communication Engineering Jiangsu Univestity Zhenjiang China

The use of federated learning to achieve blockchain interoperability has become a hot topic in research, because it enables data exchange without revealing any private information. However, the previous work, such as ScaleSFL (Asia-CCS, 2022), that has implemented federated learning for blockchain interoperability, the throughput of the framework still cannot support the practical applications. Therefore, a federated learning framework based on Directed Acyclic Graph (DAG) is proposed which utilizes sharding mechanism to enhance the blockchain interoperability. By constructing a weighted context graph based on data correlation, reasonable sharding of the dataset is achieved, thereby improving the efficiency of blockchain interoperability. The experimental results show that the federated framework reduces global computation in federated learning by 30% compared with other schemes, while increasing blockchain throughput by nearly 40%. © 2023 The Authors. IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Blockchain

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The Impact of CyRIS in Ascertaining Accurate Implementation of Projects 14

The Impact of CyRIS in Ascertaining Accurate Implementation ...

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14th International Conference on Computing communication and Networking Technologies, ICCCNT 2023

作者： Sharifi, Ahma Zia Walid, Md. Abul Ala Zia, Ghezal Ahmad Jan Salehin, Md. Nazmus Safi, Ihsan Ul Haq Al Islam, Iqbal Faculty of Computer Science Nangarhar Univeristy Department of Networking and Communication Afghanistan Department of Computer Science and Engineering Khulna9203 Bangladesh Berlin Germany Department of Computer Science and Engineering Natore Bangladesh Nangarhar University Department of Networking and Communication Faculty of Computer Science Afghanistan Department of Computer Science & Engineering Savar Dhaka Bangladesh

ISBN: (纸本)9798350335095

This systematic review seeks to evaluate the impact of CyRIS in ascertaining accurate implementation of projects with a primary focus on the merits of its functionalities. Core to the study is the view that CyRIS-driven project implementation reduces the risks of inaccuracy to an acceptable level. Although CyRIS is an extensively researched area in cyber security, a comprehensive review of subcategories, specifically, the accurate implementation of projects using the tool remains understudied. The proposed systematic review of literature provides insights and future directions from selected databases, including scienceDirect, Springer Journals, SAGE Journals, and Wiley Online Library. Moreover, the limitations and strengths of each article collected are assessed using the PRISMA model to identify risks of bias. The research, which consists of journal articles, conferences, and symposium papers, is analyzed using "Cyber-Range Instantiation Systems and accurate implementation of projects"as the key phrase and "Cyber-Risk Models", "Cyber Range Instantiation", and "Cyber Security Training", and "Accurate Implementation of Projects"as the keywords. The findings of the study will bridge the awareness gap in using CyRIS-led Cyber-Risk Models to execute accurate training scenarios, improve weaknesses of implementation, simulate real-time attack scenarios, and highlight existing gaps as well as prospects for future research. © 2023 IEEE.

关键词： Cybersecurity

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A machine learning approach for skin lesion classification on iOS: implementing and optimizing a convolutional transfer learning model with Create ML

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International Journal of computers and Applications 2024年第8期46卷 666-685页

作者： Benedek Szabo, Aron Katona, Jozsef Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Instrumentation and Automation Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary Department of Informatics GAMF Faculty of Engineering and Computer Science Kecskemét Hungary

The integration of machine learning (ML) into mobile applications presents unique challenges, particularly in resource-constrained environments such as iOS devices. Skin lesion classification is a critical task in dermatology, where accurate and efficient diagnostic tools can significantly aid in early detection of malignant lesions. This study aims to implement a machine learning-based iOS mobile application and develop a binary classification model for skin lesion images to determine whether a lesion is malignant. The research utilized Create ML to develop a convolutional neural network optimized for iOS, employing a transfer learning approach. A logistic regression model was cascaded with the convolutional neural network N to enhance classification accuracy. The model's performance was assessed through various validation metrics, ensuring its robustness and efficiency within the constraints of mobile hardware. A curated dataset from the International Skin Imaging Collaboration archive was used for training and testing. The model achieved an accuracy of 92%, a precision of 90%, a recall of 93%, and an F1-score of 91% in classifying skin lesions. These metrics validate the model's efficacy in identifying malignant lesions. Data curation involved collecting, labeling, and preparing a dataset from publicly available sources, ensuring the inclusion of diagnostically relevant features. The final model was integrated into an iOS application using Core ML and Vision frameworks. The developed application demonstrates reliable performance in classifying skin lesions with high accuracy on iOS devices. The inclusion of comprehensive performance metrics justifies the efficacy of the proposed approach. Future work will explore enhancements in model architecture and object detection capabilities to further improve diagnostic precision and application usability. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Image recognition

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