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Block chain Integration with Cloud/Edge/Fog IOT System for Security Issues 8

Block chain Integration with Cloud/Edge/Fog IOT System for S...

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8th international conference on computing in Engineering and Technology, ICCET 2023

作者： Ghadiyaram, Anil Kumar Chakravarthy, Srinivasa L. Department of CSE Vignana Bharathi Institute of Technology Telangana Hyderabad India AP Visakhapatnam India

ISBN: (纸本)9781839539237

Over the last several years, the IoT has made significant strides. In conventional IoTecosystems, sensors feed data onto fog devices, which then upload the data to theCloud. IoT is susceptible to threats to privacy and security because it lacks inherentsecurity safeguards. With its "security by design,"Blockchain (BC) may assist inmeeting the important security needs in IoT. Blockchain solutions may assist addressmost IoT architectural flaws by avoiding trusted third parties, protecting against asingle point of failure, and avoiding trusted third parties altogether. To protect againstpossible attacks and lower transaction costs, distributed IoT systems may be builtusing the blockchain's capabilities, such as decentralization, consensus mechanisms,data encryption, and smart contracts. the performance of IoT security might beimproved by using blockchain, a decentralized and open database *** have been motivated by this to look at blockchain adoption in the IoTecosystem. this study presents a survey on the integration of blockchain technologyfor security concerns with cloud, edge, and fog IoT systems. the goal of this study is to examine current research trends on the use of BC-related methodologies and tools inan IoT environment. © the Institution of Engineering & Technology 2023.

关键词： Cloud computing architecture

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APIM: Adaptive Path Isolation for Mixed Flows in Data Center Networks 8

APIM: Adaptive Path Isolation for Mixed Flows in Data Center...

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8th IEEE international conference on Computer and Communications, ICCC 2022

作者： Li, Xiao Yang, Fan State Key Laboratory of Networking and Switching Technology Beijing100876 China Beijing University of Posts and Telecommunications Beijing100876 China Purple Mountain Laboratories Nanjing211111 China

ISBN: (纸本)9781665450515

With the emergence of 5G and cloud computing technologies, modern data centers host a wide variety of heterogeneous mixed flows. However, only few load balancing schemes adopt path partition to route mixed flows. Due to resource competition between mouse and elephant flows, two key performance indicators, flow completion time and throughput, are negatively impacted to some extent. We propose a new load balancing scheme APIM. Based on adaptive path isolation, the elephant and mouse flows are forwarded on their respective paths. Meanwhile, APIM uses Equal Cost Multi Path for mouse flows to acquire low latency and Random Packet Spraying for elephant flows to guarantee throughput. the experimental results show that APIM decreases the completion time of mouse flows and ensures the throughput of elephant flows. © 2022 IEEE.

关键词： Benchmarking

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Privacy Estimation on Twitter: Modelling the Effect of Latent Topics on Privacy by Integrating XGBoost, Topic and Generalized Additive Models 19

Privacy Estimation on Twitter: Modelling the Effect of Laten...

引用

2022 IEEE SmartWorld, 19th IEEE international conference on Ubiquitous Intelligence and computing, 2022 IEEE international conference on Autonomous and Trusted Vehicles conference, 22nd IEEE international conference on Scalable computing and Communications, 2022 IEEE international conference on Digital Twin, 8th IEEE international conference on Privacy computing and 2022 IEEE international conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Tillmann, Arne Kqiku, Lindrit Reinhardt, Delphine Weisser, Christoph Säfken, Benjamin Kneib, thomas Georg-August-Universität Göttingen Göttingen Germany Insitute of Computer Science Georg-August-Universität Göttingen Göttingen Germany Clausthal University of Technology Clausthal Germany

ISBN: (纸本)9798350346558

Securing their users' privacy is a central duty of Online Social Networks (OSN), but the complex non-linear effects of social media content on privacy is not well understood. We propose a novel framework that integrates XGBoost, Latent Dirichlet Allocation (LDA) topic models and Generalized Additive Models (GAM) to perform statistical inference about the complex non-linear relationship between the topics and privacy of tweets. First, XGBoost is used to predict the privacy of tweets. then, the predictions are improved by analyzing the classified tweets with LDA topic models. Finally, we model the nonlinear relationship between topics and privacy with GAMs by using (penalized) splines. Instead of being limited to predictive modeling, our approach enables us to model the non-linear relationship between latent topics and the privacy of tweets. © 2022 IEEE.

关键词： Social networking (online)

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Research on Anomaly Detection of distributed Intelligent Teaching System Based on Cloud computing 8th

Research on Anomaly Detection of Distributed Intelligent Tea...

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8th EAI international conference on e-Learning, e-Education, and Online Training, eLEOT 2022

作者： Zheng, Fayue Ma, Lei Yang, Hongxue Liu, Leiguang Beijing Polytechnic Beijing100016 China

ISBN: (纸本)9783031211607

the traditional anomaly detection method of intelligent teaching system has some problems, such as poor accuracy and response efficiency. therefore, this paper proposes a distributed anomaly detection method of intelligent teaching system based on cloud computing. Collect the abnormal data of distributed intelligent teaching system through cloud computing method, calculate the local reachable density according to Gaussian distribution function, build a data management model, and use distributed technology to locate and manage the abnormal area of teaching data, so as to achieve the goal of data detection and identification. the experimental results show that this method can effectively improve the recall rate of anomaly detection data in intelligent teaching system, and the response efficiency has been effectively improved. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Anomaly detection

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Violence Detection In Videos via Motion-Guided Global and Local Views 8

Violence Detection In Videos via Motion-Guided Global and Lo...

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8th international conference on Data Science in Cyberspace, DSC 2023

作者： Su, Ning Sun, Lijuan Gao, Yutong Wu, Jingchen Wu, Xu Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education China School of Cyberspace Security Bupt China School of Economics and Management Beijing University of Posts and Telecommunications Beijing China Beijing Jiaotong University Beijing Key Lab of Traffic Data Analysis and Mining Beijing China Bupt China

ISBN: (纸本)9798350331035

Video violence detection aims to locate the time window in which violent behavior occurs. Most methods focus on utilizing RGB features directly or only fusing RGB and audio features, ignoring the effective exploitation of motion information carried in optical flow. this lack of emphasis on motion information may impact the overall accuracy of violence detection. Moreover, we observe that videos contain strong local correlations, so it is insufficient to analyze only from a holistic perspective without capturing finer details. therefore, in this paper, we design a novel Global-and-Local Cross-Modal Network (GL-CMN) for violence detection, which effectively integrates motion information and multi-granularity features from target videos. Specifically, we first propose a Motion-Guided Attention Module (MGAM) to obtain enhanced visual features by calibrating RGB features through optical flow features. Secondly, the enhanced features are simultaneously fed into two parallel branches of the network. the global branch fuses the visual and audio features into holistic representations. the local branch extracts multi-scale temporal dependencies through dilated convolutions. Experiments demonstrate that our method exhibits significant improvement compared to previous state-of-the-art methods on the XD-Violence dataset. © 2023 IEEE.

关键词： Attention Mechanism Multimodality Multiple Instance Learning Violence Detection

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Dynamic VNF Placement in 5G Edge Nodes 8

Dynamic VNF Placement in 5G Edge Nodes

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8th IEEE international conference on Network Softwarization (NetSoft) - Network Softwarization Coming of Age - New Challenges and Opportunities

作者： Harris, Dor Raz, Danny Techion Dept Comp Sci Haifa Israel

ISBN: (纸本)9781665406949

the ongoing transition into 5G networks is enabled in part by the combination of NFV (Network Function Virtualization) and MEC (Multi-access Edge computing), two promising paradigms that allow executing ultra-low-latency network services on edge nodes, physically closer to the clients. However, orchestrating this complex distributed environment and especially provisioning services in a timely manner, in order to address the dynamic workload, remained a big challenge. In this paper we address this challenge and study ways to dynamically place network functions at edge nodes, across the network, in a way that maximizes client satisfaction, we measure this satisfaction by the number of clients that received their desired services in a manner that holds these required services low-latency demands. In order to balance between the dynamic workload and the non-negligible cost of replacing the functions at the edge, we partition the time into epochs and reassign VNFs (Virtual Network Functions) only at the beginning of each epoch. Our theoretical analysis, based on studying a simple variant of the online problem, shows that the data from the last epoch can provide guarantees on the expected performance. We then evaluate the actual performance of our algorithm based on extensive simulations over real data. the results indicate that our new algorithm can be deployed in a realistic 5G setting, generating an overall dynamic solution that outperforms currently used methods.

关键词： Multi-access edge computing Costs 5G mobile communication Heuristic algorithms Computational modeling conferences Data models

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Fuzzy rule-based grey wolf(GW-FIS) in Wireless Body Area Networks 8

Fuzzy rule-based grey wolf(GW-FIS) in Wireless Body Area Net...

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8th IEEE international conference for Convergence in Technology, I2CT 2023

作者： Sharma, Poonam Saini, Kamaljit Singh Sidhu, Prabhjot Kaur Chandigarh University University Institute of Computing Punjab Mohali India MSIT IT Department GGSIP University New Delhi India

ISBN: (纸本)9798350334012

Wireless body area networks are crucial in many fields, including healthcare, education, and others. Congestion Control Problem is the main issue facing the design of Wireless Body Area Networks. Inconsistent traffic loads, power restrictions, bandwidth restrictions, and many-to-one information architecture all contribute to significant congestion problems in WBAN, which can be managed with effective path ***, this paper proposed Grey Wolf-Fuzzy Inference System (GW-FIS) appproach that utilizes the hunting mechanism of grey wolves and a rules-based approach of fuzzy to attain congestion-aware transmission among wireless body area networks. the hunting mechanism of grey wolves says that in each iteration, omega wolves update the position, and here omega wolves represent the highly congested area and then update the rate of transmission for that node. Moreover, the fuzzy rule defines the congestion level with the randomly distributed grey *** proposed approach select the best path with lowest congestion level to data transmission in WBANs. the proposed approach is simulated using a Network simulator, and performance is computed based on two different scenarios in terms of total energy consumption (TEC), packet delivery ratio (PDR), and end-to-end delay (E2D). the simulated results of first scenario that is based on number of connection are compared with the existing algorithms. It is found that the performance of proposed protocol is improved by 38.6%,6% and 49.5% from GWO respectively in terms of TEC,PDR and E2D. Secondly proposed mechanism are compared with existing mechanism based on second scenario that is speed of nodes and results shows that proposed protocol improved the performance by 47%,6% and 63% from GWO respectively in trem of TEC,PDR and E2D. though PDR is not much improved still results clearly show that the proposed approach's calculate the best path for data transmission with low congestion level. © 2023 IEEE.

关键词： Energy utilization

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Challenges in Modelling Applications for Safe and Resilient Digital Twins 8

Challenges in Modelling Applications for Safe and Resilient ...

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8th IEEE international Smart Cities conference, ISC2 2022

作者： Khan, Muhammad Taimoor School of Computing and Mathematical Sciences University of Greenwich London United Kingdom

ISBN: (数字)9781665485616

ISBN: (纸本)9781665485616

Digital twin-based modern smart city infrastructures are evolving into intelligent and distributed systems of autonomous entities operating in a dynamic cyber-physical environment to offer real-time and critical services. these services are typically implemented as software applications in various application domains, e.g., healthcare, cooperative robotic systems, and autonomous vehicles. However, to assure continued safe operations of the critical services with strict real-time requirements even when the service is under attack is an extremely challenging task mainly because the underlying operating environment for such applications is highly volatile yet distributed. To this end, first, we classify (as we call it) timed resilience requirements into computational and communication resilience and then discuss key challenges that hinder the modeling of such requirements to help develop rigorous distributed applications for real-time resilient autonomous systems. Finally, we demonstrate our vision to handle these challenges by introducing by-design and by-response approaches that consider security as a prerequisite of the safety and resilience of autonomous systems. © 2022 IEEE.

关键词： Smart city

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Building a QoS Testing Framework for Simulating Real-World Network Topologies in a Software-defined networking Environment 8

Building a QoS Testing Framework for Simulating Real-World N...

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8th international conference on Engineering and Emerging Technologies, ICEET 2022

作者： Yoo, Hyeong Seon Yu, William Emmanuel S. Ateneo de Manila University Department of Information Systems and Computer Science Quezon City Philippines

ISBN: (纸本)9781665491068

Software-defined networking is an emerging technology for implementing Quality of Service (QoS) for its logically centralized control and decoupled control and forwarding planes. In this paper, we extend a previous framework that simulated a fat-Tree topology software defined network under QoS provisioning techniques to support different topologies, including data from the Internet Topology Zoo. We compare round-Trip times between each server and client, and transfer rates of HTTP traffic in the tree, mesh, and topology provided by Kreonet and Uni-C under a distributed class-based queuing system. We observe that while round-Trip times are not significantly different, transfer rate of HTTP traffic as generated by ApacheBenchmark in Kreonet decreased 57.1109% from the fat-Tree topology, and 49.5328% from the mesh topology. Uni-C topology took 114.9% more time for the switches in the network to have installed all their flows than the Kreonet topology, the next slowest topology. Uni-C topology also failed to finish the HTTP benchmarks due to its more complex topology in a resource-limited machine. these differences demonstrate that the complexity of real world network environments (i.e. route loops, layering, convergence times) affect the network behavior, which is key to a good simulator. therefore, the modified framework is able to support and properly simulate real-world network topologies. © 2022 IEEE.

关键词： Network topology

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A distributed Approach for 5G Computation Offloading based on Non-Preemptive Priority Scheduling and Deep Reinforcement Learning 8

A Distributed Approach for 5G Computation Offloading based o...

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8th IEEE international conference on Computer and Communications, ICCC 2022

作者： Liu, Nian Zhang, Tao Cui, Junlang Cao, Yanyi Zhang, Chuanfu School of Systems Science and Engineering Sun Yat-sen University Guangzhou China

ISBN: (纸本)9781665450515

Mobile devices generate numerous non-divisible and delay-sensitive tasks in 5G system, which bring a huge amount of network traffic. As Mobile edge computing can effectively alleviate computational pressure of terminal devices by offloading some tasks to edge servers, it is of great value to investigate an appropriate computation offloading scheme to reduce the sum processing delay and the task dropped rate in the 5G system. In order to deal with the problem, by adopting long short-term memory (LSTM), dueling double DQN (D3QN) and DQNReg, the problem is formulated into a long-term optimization problem in this paper. Based on non-preemptive priority scheduling and deep reinforcement learning (DQN), an innovatively distributed offloading algorithm named NPPS-D3QNReg is proposed, which can be used for adjusting the execution order of the tasks according to their deadlines. Finally, simulation results demonstrate that our proposed algorithm can effectively reduce the sum delay and task dropped rate. © 2022 IEEE.

关键词： Reinforcement learning

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