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CEER:Cooperative Energy-Efficient Routing Mechanism for Underwater Wireless Sensor Networks Using Clusters

Computer Systems Science & engineering 2023年第6期45卷 2587-2602页

作者： Sayyed Mudassar Shah Tariq Hussain Babar Shah Farman Ali Khalid Zaman Kyung-Sup Kwak Institute of Computer Science&Information Technology the University of Agriculture Peshawar25000Pakistan High Performance Computing and Networking Institute National Research Council(ICAR-CNR)Naples80131Italy College of Technological Innovation Zayed UniversityDubai19282UAE Department of Software Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Inha UniversityIncheon22212Korea

Underwater acoustic sensor networks(UWASNs)aim to find varied offshore ocean monitoring and exploration *** most of these applications,the network is composed of several sensor nodes deployed at different depths in the *** nodes located at depth on the seafloor cannot invariably communicate with nodes close to the surface level;these nodes need multihop communication facilitated by a suitable routing *** this research work,a Cluster-based Cooperative Energy Efficient Routing(CEER)mechanism for UWSNs is proposed to overcome the shortcomings of the Co-UWSN and LEACH *** optimal role of clustering and cooperation provides load balancing and improves the network *** simulation results using MATLAB show better performance of CEER routing protocol in terms of various parameters as compared to Co-UWSN routing protocol,i.e.,the average end-to-end delay of CEER was 17.39,Co-UWSN was 55.819 and LEACH was *** addition,the average total energy consumption of CEER was 9.273,Co-UWSN was 12.198,and LEACH was *** packet delivery ratio of CEER was 53.955,CO-UWSN was 42.047,and LEACH was *** stability period CEER was 130.9,CO-UWSN was 129.3,and LEACH was *** obtained results maximized the lifetime and improved the overall performance of the CEER routing protocol.

关键词： Cluster head co-UWSN UWSN relay LEACH CEER

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Web Application to predict Skin Disease: An Approach Using Deep Learning Algorithm

Web Application to predict Skin Disease: An Approach Using D...

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Human-Computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Eelanila Thayalan Ayingaran Arumugavel Sharujan Ganeshan Makenthiran Dalaxshan Harinda Fernando Kaushalya Rajapakse Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798350394634

ISBN: (纸本)9798350394641

The Disease Prediction System revolutionizes healthcare with advanced machine learning techniques for early detection of skin diseases, notably focusing on skin cancer. Through image processing and Transfer Learning, it excels in identifying potential malignancies, enabling timely interventions. Its capabilities extend to benign tumors and growth disorders, utilizing the ResNet50 Model for precise identification. Additionally, it predicts skin reactions associated with various dermatological conditions, such as Urticaria Hives and Warts, leveraging the efficientnetB0 Model. Integration of the VGG16 Model enhances diagnostic accuracy for inflammatory skin conditions. This holistic approach prioritizes patient-centric care, leveraging diverse datasets and intricate pattern recognition in medical images. The system’s proactive nature embodies personalized solutions for early detection, timely intervention, and improved patient outcomes. Its versatility and accuracy underscore itstransformative potential in healthcare delivery. By harnessing diverse datasets and recognizing intricate patterns within medical images, it heralds a new era of personalized healthcare solutions. In essence, the Disease Prediction System exemplifies the transformative potential of machine learning in healthcare, ensuring the highest standards of diagnostic accuracy and efficacy, while prioritizing patient well-being and quality oflife.

关键词： Transfer learning Medical services Skin Pattern recognition Medical diagnostic imaging Standards Robots

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An efficient group key agreement protocol with administrator 3

An efficient group key agreement protocol with administrator

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3rd International Conference on Internet of Things and Smart City, IoTSC 2023

作者： Fang, Qihao Zhang, Lei Zhang, Mingrui Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai200062 China Science and Technology on Communication Security Laboratory Chengdu610041 China Engineering Research Center of Software/Hardware Co-design Technology and Application Ministry of Education Shanghai200062 China

ISBN: (纸本)9781510666375

Group key agreement technology is one of the most popular solution to establish a reliable secure channel between communicating entities of a group. Group key agreement protocol with administrator (GKAA) can handle a large number of group operations in sequence to resolve disorder problem and it is widely used in practical applications. However, in most of existing protocol, the administrator has to compute materials for each participant in the group which brings huge calculate overhead. In this paper, we propose an efficient group key agreement protocol with Administrator. Our GKAA protocol is able to perform group operation in a high efficacy way with the help of a key tree. It is also flexible and scalable since it suits for any network communication environment like IoT, video meeting, social applications, etc. Our protocol satisfies the properties including forward secrecy, PCS and key control resistance. © 2023 SPIE.

关键词： Network security

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Practical privacy-preserving mixing protocol for Bitcoin 26

Practical privacy-preserving mixing protocol for Bitcoin

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26th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2023

作者： Chang, Qianqian Xu, Lin Zhang, Lei Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai200062 China Science and Technology on Communication Security Laboratory Chengdu610041 China Engineering Research Center of Software/Hardware Co-design Technology and Application Ministry of Education Shanghai200062 China

ISBN: (纸本)9798350331684

The privacy of Cryptocurrencies are of great concern in various fields. Researches has shown that pseudonyms, which are used in Bitcoin, only provide weak privacy. The privacy of users may be put at risk under deanonymization attacks. The exisiting schemes typically require a trusted-third party to achieve anonymity, however this usually faces a single-point fault. In addition, existing schemes suffer from high communication complexity and impracticality. This paper proposes a practical privacy-preserving mixing protocol for Bitcoin to achieve unlink-ability of input and output address of transactions. Compared to existing schemes, our protocol improves practicality. The communication complexity of our protocol is linearly related to the number of peers. Moreover, our protocol is scalable as it works not only for Bitcoin, but also for other cryptocurrencies. © 2023 IEEE.

关键词： Computational complexity

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Smart Photo Editor for Differently-abled People using Assistive Technology 6

Smart Photo Editor for Differently-abled People using Assist...

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6th International Conference on Information Technology Research, ICITR 2021

作者： Buddhika, A.S. Wijesekera, P.K. Kavindu, D. G. Hasintha Dinusha, Dilshan S Arachchillage, Udara Srimath S. Samaratunge Kuruppu, Thilmi Anuththara Faculty of Computing Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9781665420006

Differently-abled people are significant minority groups, have many limitations to live everyday life, are starved of services, and are mostly ignored by society due to many types of disabilities. This problem may lead to massive frustrations and disappointments among themselves. Assistive technology may easily fill this gap with the enhanced different aiding applications. It helped in various ways, such as helping them to interact, communicate with people and allow people to do basic daily tasks by themselves. Nevertheless, there were fewer applications developed to entertain their leisure time. Therefore, the proposed solution provides a Smart Photo Editor, a hand-free mobile application with attractive photo editing features. This application focused on people having hand motor disabilities. Users can interact with the application using simple head gestures, eye gaze, and eye blinks. Head gestures and eye blinks are used as commands for application operations, while eye gaze is used for cursor enabling, which is helpful for navigation on application screens. Machine Learning (ML) and image processing techniques are used for real-time gesture recognition and eye gaze detection, using the input video frames captured by the inbuilt front-facing camera of the mobile phone. Moreover, in addition to the image processing techniques, Mask Recurrent-Convolutional Neural Network (R-CNN) is used to develop enhanced image adjusting features and customization of backgrounds based on object detection. © 2021 IEEE.

关键词： Image enhancement

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Unifying and Improving Graph Convolutional Neural Networks with Wavelet Denoising Filters 23

Unifying and Improving Graph Convolutional Neural Networks w...

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2023 World Wide Web Conference, WWW 2023

作者： Wan, Liangtian Li, Xiaona Han, Huijin Yan, Xiaoran Sun, Lu Ning, Zhaolong Xia, Feng Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province School of Software Dalian University of Technology Dalian China Research Center of Big Data Intelligence Research Institute of Artificial Intelligence Zhejiang Lab Hangzhou China Department of Communication Engineering Institute of Information Science Technology Dalian Maritime University Dalian China School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China School of Computing Technologies Rmit University Melbourne Australia

ISBN: (纸本)9781450394161

Graph convolutional neural network (GCN) is a powerful deep learning framework for network data. However, variants of graph neural architectures can lead to drastically different performance on different tasks. Model comparison calls for a unifying framework with interpretability and principled experimental procedures. Based on the theories from graph signal processing (GSP), we show that GCN's capability is fundamentally limited by the uncertainty principle, and wavelets provide a controllable trade-off between local and global information. We adapt wavelet denoising filters to the graph domain, unifying popular variants of GCN under a common interpretable mathematical framework. Furthermore, we propose WaveThresh and WaveShrink which are novel GCN models based on proven denoising filters from the signal processing literature. Empirically, we evaluate our models and other popular GCNs under a more principled procedure and analyze how trade-offs between local and global graph signals can lead to better performance in different datasets. © 2023 ACM.

关键词： Convolution

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Prism: Revealing Hidden Functional Clusters from Massive Instances in Cloud Systems 23

Prism: Revealing Hidden Functional Clusters from Massive Ins...

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Proceedings of the 38th IEEE/ACM International Conference on Automated software engineering

作者： Jinyang Liu Zhihan Jiang Jiazhen Gu Junjie Huang Zhuangbin Chen Cong Feng Zengyin Yang Yongqiang Yang Michael R. Lyu The Chinese University of Hong Kong Hong Kong SAR China School of Software Engineering Sun Yat-sen University Zhuhai China Computing and Networking Innovation Lab Huawei Cloud Computing Technology Co. Ltd China

ISBN: (纸本)9798350329964

Ensuring the reliability of cloud systems is critical for both cloud vendors and customers. Cloud systems often rely on virtualization techniques to create instances of hardware resources, such as virtual machines. However, virtualization hinders the observability of cloud systems, making it challenging to diagnose platform-level issues. To improve system observability, we propose to infer functional clusters of instances, i.e., groups of instances having similar functionalities. We first conduct a pilot study on a large-scale cloud system, i.e., Huawei Cloud, demonstrating that instances having similar functionalities share similar communication and resource usage patterns. Motivated by these findings, we formulate the identification of functional clusters as a clustering problem and propose a non-intrusive solution called Prism. Prism adopts a coarse-to-fine clustering strategy. It first partitions instances into coarse-grained chunks based on communication patterns. Within each chunk, Prism further groups instances with similar resource usage patterns to produce fine-grained functional clusters. Such a design reduces noises in the data and allows Prism to process massive instances efficiently. We evaluate Prism on two datasets collected from the real-world production environment of Huawei Cloud. Our experiments show that Prism achieves a v-measure of ~0.95, surpassing existing state-of-the-art solutions. Additionally, we illustrate the integration of Prism within monitoring systems for enhanced cloud reliability through two real-world use cases.

关键词： functional clusters

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ATT&CKViz: Enhancing Cybersecurity Insights by Visual Analytics of Attack Patterns

ATT&CKViz: Enhancing Cybersecurity Insights by Visual Analyt...

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engineering & computing Technologies (ICECT), International Conference on

作者： Inbasat Fiza Fizza Khurshid Manahil Fatima Umara Noor Zahid Rashid Department of Software Engineering Faculty of Computing and Information Technology International Islamic University Islamabad Pakistan Technology Management Economics and Policy Program College of Engineering Seoul National University Seoul South Korea

ISBN: (数字)9798350349719

ISBN: (纸本)9798350349726

The ATT&CK MITRE framework serves as an expansive repository of adversary tactics, techniques, and procedures. Given the sheer volume of these intricate attack patterns, the conventional manual navigation method proves to be time-intensive and less efficient for security analysts. As a remedy, there arises a compelling necessity to present the rich content encapsulated within the ATT&CK MITRE repository through interactive visualizations. In this paper ATT&CKViz an interactive web-based cyber-attack patterns visualization tool is presented that aims to empower security analysts with the ability to effortlessly explore the repository from diverse angles, which facilitates deep insights into cyber threats. The aim is to understand cyber threat efficiently with a timely response. The empirical evaluations depict that effectiveness and user-friendliness of ATT&CKViz.

关键词： Computers Navigation Visual analytics Manuals Cyberattack

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Joint QoS Prediction for Web Services based on Deep Fusion of Features

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IEEE Transactions on Network and Service Management 2023年 1-1页

作者： Ding, Linghang Liu, Jianxun Kang, Guosheng Xiao, Yong Cao, Buqing Hunan Provincial Key Lab. for Services Computing and Novel Software Technology and School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China

In order to solve the problem of insufficient accuracy of Web service QoS prediction, a joint QoS prediction method for Web services based on the deep fusion of features was proposed by considering the hidden environmental preference information in QoS and the common characteristics of multi-class QoS. QoS data was modeled as user-service bipartite graph at first, then, multi-component graph convolution neural network was used for feature extraction and mapping, and weighted fusion method was used for the same dimensional mapping of multi-class of QoS features. Subsequently, the attention factor decomposition machine was used to extract the first-order features, second-order interactive features and high-order interactive features of the mapped feature vector. Finally, the results of each part were combined to achieve the joint QoS prediction. The experimental results show that the proposed method is superior to the existing QoS prediction methods in terms of root mean square error (RMSE) and average absolute error (MAE). IEEE

关键词： Feature extraction

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Empowering Semantic Segmentation with Selective Frequency Enhancement and Attention Mechanism for Tampering Detection

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 3270-3283页

作者： Xu, Xu Lv, Wenrui Wang, Wei Zhang, Yushu Chen, Junxin Dalian University of Technology School of Software Dalian116621 China Northeastern University School of Computer Science and Engineering Shenyang110004 China Shenzhen MSU-BIT University Guangdong-Hong Kong-Macao Joint Laboratory for Emotion Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen518172 China Beijing Institute of Technology School of Medical Technology Beijing100081 China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing210016 China

Nowadays, massive amounts of multimedia contents are exchanged in our daily life, while tampered images are also flooding the social networks. Tampering detection is therefore becoming increasingly important for multimedia integrity, and it is generally realized by designing specific convolutional neural networks. From a new perspective, this article proposes two pluggable modules for empowering existing semantic segmentation models for tampering detection. First, a selective frequency enhancement (SFE) module is developed to suppress the semantic information and selectively enhance the tamper information. Second, a boundary enhanced attention (BEA) module is designed to highlight the edge information of tempered area. Our SFE and BEA modules are combined with five mainstream semantic segmentation networks for performance evaluation. The experiment results demonstrate that our modules are able to empower the semantic segmentation networks for tampering detection, and their combinations even perform better than state-of-the-art algorithms in certain datasets. © 2020 IEEE.

关键词： Semantics

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