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Multifactor Authentication Using Blockchain in 6G 8

Multifactor Authentication Using Blockchain in 6G

引用

8th ieee international conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Aishwarya, R. Khot, Anusha Sreenivas, Sumana Nagamani, K. R V College of Engineering Karnataka Bangalore India

ISBN: (纸本)9798331505462

With the rise of 6G technology, cyberattacks have become a significant concern, necessitating robust data security measures. Multi-factor authentication (MFA) systems, integrating advanced biometric methods, offer a promising solution to enhance security and protect sensitive information. this work explores the integration of iris and voice recognition with blockchain technology to enhance security measures for 6G networks. the increasing complexity of cyberattacks, privacy concerns from massive data collection, and the vulnerabilities associated with edge computing and quantum computing highlight the necessity for robust security solutions. Gaps in current 6G network security research, including limited studies on integrating multiple biometric modalities within Multi-Factor Authentication (MFA) systems and the lack of practical integration of AI/ML, distributed Ledger Technology, and quantum computing have been identified. Addressing these gaps can lead to scalable and effective security solutions for 6G networks. the combination of unique iris and voice patterns with the tamper-proof and decentralized nature of blockchain ensures a robust authentication process. this framework was implemented and its efficacy and feasibility were demonstrated through simulated authentication procedures. the results show a significant improvement in security metrics over conventional single-factor authentication methods, with high accuracy rates for both voice and iris recognition. these outcomes, along with the blockchain's tamper-proof features, provide a strong defense against unauthorized access. © 2024 ieee.

关键词： Authentication Protocol

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distributed Deep Deterministic Policy Gradient Agents for Real-Time Energy Management of DC Microgrid 6

Distributed Deep Deterministic Policy Gradient Agents for Re...

引用

ieee 6th international conference on Direct Current Microgrids (ICDCM)

作者： Buraimoh, Elutunji Ozkan, Gokhan Timilsina, Laxman Muriithi, Grace Arsalan, Ali Papari, Behnaz Moghassemi, Ali Edrington, Christopher Ozden, Mustafa Clemson Univ Dept Elect & Comp Engn Clemson SC 29634 USA Clemson Univ Dept Automot Engn Clemson SC USA

ISBN: (纸本)9798350363647;9798350363630

this paper presents a real-world military use of a microgrid with Vehicle-to-Grid (V2G) and Vehicle-to-Vehicle (V2V). this plug-and-play system delivers efficient, fast-deploying power for a contingency base within 20 minutes, generating up to 500 kW of three-phase power. It utilizes vehicle-based Internal Combustion (IC) engine generators and an Energy Storage System (ESS) to power vehicle equipment and off-board loads like shelters and communication centers. However, fluctuating off-board loads create operational challenges for this V2G-V2V microgrid. this work proposes a real-time implementation of energy management based on distributed Deep Deterministic Policy Gradient (DDPG), a deep reinforcement learning, to address this problem for continuous state and continuous action spaces. this work formulates the energy management problem as a Markov decision process, considering random load demands and fuel costs. this paper aims to minimize the microgrid's operating costs by optimizing the dispatch of onboard vehicle power generators and storage units. With simulation experiments, this work demonstrates the effectiveness of the proposed distributed deep reinforcement learning approach. the results show the distributed DDPG agents can utilize the state of the ESS and significantly decrease the microgrid's overall operation costs. this validates the practical value of distributed DDPG for economic operations in military microgrids.

关键词： Energy Management Deep Deterministic Policy Gradient Multi-Agent System Microgrid Reinforcement Learning Vehicle-to-Grid Vehicle-to-Vehicle

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Secure and Efficient Cluster Head Selection and Routing in WSN for IoT through Congestion Free Mechanism 6

Secure and Efficient Cluster Head Selection and Routing in W...

引用

6th international conference on computing Methodologies and Communication, ICCMC 2022

作者： Sindhuja, M. SRM Institute of Science and Technology School of Computing Department of Computing Technologies Kattankulathur Tamil Nadu Chennai India

ISBN: (纸本)9781665410281

Wireless sensor networks (WSNs) involve countless sensor hubs which can detect and process information in the earth in an intermittent way. In WSN, as the sensor hub relies upon its inward battery control, vitality proficiency and the lifetime of sensors have turned into a key issue on the execution of the wireless network. To make compelling use of vitality assets of a sensor hub, correspondence conventions can be planned decisively. To achieve this objective, sensor hubs clustering is one of the most thriving approaches. In accordance with, the selection of cluster heads (CHs) is in the transmission range of the hub. Cluster head has the obligation to perform secure and productive directing by keeping up and using a token for every hub. Such strategy gives a superior execution in security, vitality proficiency, load adjusting and so on. In this system, the cluster head is chosen proficiently. the reason cluster head is to enhance congestion free routing and secured information transmission. © 2022 ieee.

关键词： Wireless sensor networks

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Improved-Hybrid GA-Based Technique to Optimize the Resource Utilization in Cloud 6

Improved-Hybrid GA-Based Technique to Optimize the Resource ...

引用

6th international conference on Contemporary computing and Informatics, IC3I 2023

作者： Kumar, Amodh Ahlawat, Deepak Harnal, Shilpi Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350304480

Data clustering is a technique related to technology that can be used and utilized in vast areas of computer science and other applications. In this work, the technique access and used for clustering is improved-hybrid clustering in cloud computing with the application of GA in the algorithm. the process is started by uploading the text documents on the cloud and the GA algorithm of improved-hybrid similarity is applied and results are considered for analysis. the research is a step towards innovation and two parameters for resource optimization are taken into consideration viz., memory consume and CPU utilization. the results obtained for memory utilization and CPU utilization are scalable and optimal in the carried-out study. © 2023 ieee.

关键词： Cloud computing Genetic algorithm Hadoop distributed File System (HDFS) Improved-Hybrid Similarity Service-Level Agreement (SLA) Teaching-Learning Based Optimization (TLBO)

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Drowsiness Sensing System for Driver Safety 6

Drowsiness Sensing System for Driver Safety

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6th international conference on Advanced computing and Communication Technologies for High Performance Applications (ACCthPA)

作者： Colin, Pinto A. Colaco, S. G. Deepansh, A. Melron, Rodrigues, I Deekshith, V St Joseph Engn Coll Mangalurur India

ISBN: (纸本)9798350398441

Drowsy driving-related vehicle accidents are a growing source of concern. Drowsiness can happen when driving as a result of fatigue and lack of sleep. the best method to prevent crashes brought on by sleepy drivers is to recognize their state and warn them beforehand. this paper presents a technique for detecting driver drowsiness using eye blink detection. In the proposed system the motorist is forewarned about the drowsy state through an alarm and if unavoidable brings the vehicle to a halt to avert an accident. the proposed design provides scope for improvement in the area of driver safety system.

关键词： eye blink sensor Microcontroller drowsy driving

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Potential Possibilities of Voice Pattern Recognition by a distributed Fiber Optic sensor 23rd

Potential Possibilities of Voice Pattern Recognition by a Di...

引用

23rd international conference on Next Generation Wired/Wireless Networks and systems (NEW2AN) / 16th conference on Internet of things and Smart Spaces (RuSMART)

作者： Gubareva, Olga Yu Dashkov, Michael V. Makarov, Igor S. Gureev, Vladimir O. Evtushenko, Alexander S. PovolzhskiyState Univ Telecommun & Informat Lva Tolstogo 23 Samara 443010 Russia

ISBN: (纸本)9783031609930;9783031609947

Currently, ensuring information security (IS) is one of the priorities of a state's national policy. One of the most important tasks of IS is the precise identification of users within information systems. Biometric methods of identification and authentication are considered the most reliable. To address the challenge of identifying a user's identity based on acoustic signals, the utilization of existing fiber-optic communication lines with installed vibro-acoustic monitoring systems at the controlled facility has been proposed.

关键词： fiber-optic communication lines vibro-acoustic monitoring systems security mel frequency cepstral coefficients

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PipePrune: Pipeline Parallel Based on Convolutional Layer Pruning for distributed Deep Learning 23

PipePrune: Pipeline Parallel Based on Convolutional Layer Pr...

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23rd ieee international conference on High Performance computing and Communications, 7th ieee international conference on Data Science and systems, 19th ieee international conference on Smart City and 7th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Tan, Daojun Jiang, Wenbin Qin, Shang Jin, Hai School of Computer Science and Technology Huazhong University of Science and Technology Natl. Eng. Res. Ctr. for Big Data Technol. and Syst. Serv. Comp. Technol. and Syst. Lab Cluster and Grid Comp. Lab Wuhan430074 China

ISBN: (纸本)9781665494571

Benefitting from the combination of the idea of pipeline with model parallelism and data parallelism, pipeline parallelism improves the efficiency of distributed deep learning systems significantly. However, suffering from the bubbles and gaps caused by the imbalance of different stages in pipeline, it can not output ideal performance yet. To explore the potential of pipeline parallelism further, we propose a novel approach called PipePrune, which adds a convolutional layer pruning strategy to pipeline creatively to reduce the bubbles and gaps. For the convolutional layers with heavy overheads, some unimportant kernels are pruned by the measurement of the L1-norm. this approach makes the processing overheads of different pipeline stages more balanced. the experimental results show that, compared with state-of-the-art pipeline methods, PipePrune can improve the training speeds obviously (e.g. for ResNet50 on ImageNet, about 30% speed improvement is realized with only 1.1% loss of training accuracies). © 2021 ieee.

关键词： Training Deep learning Smart cities Pipelines Neural networks distributed databases Parallel processing

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Research of Seismic Streaming Storage Based on Druid 23

Research of Seismic Streaming Storage Based on Druid

引用

作者： Gao, Bing Chen, Jie Zou, Qijie Qin, Jing School of Information Engineering Dalian University Dalian Key Laboratory of Smart Medical and Health Dalian China School of Software Engineerin Dalian University Dalian Key Laboratory of Smart Medical and Health Dalian China

ISBN: (纸本)9781665494571

Along with the growth of seismic observation networks, the amount of seismic observation data is also increasing rapidly with the form of fast arrival stream, and it is an important and challenging task to store seismic data in time. However, two bottlenecks (slow read/write speed, poor user concurrency) still make the practical applications difficult. We proposes an Apache Druid-based storage solution for seismic observation data streams. the solution is more adaptable to the read/write requirement of large-scale seismic data streams. Specifically, we achieve real-time observation for two aspects: (I) using Kafka as a distributed message exchange system;and (II) implementing accesses and exchange with massive seismic stream data onto the Kafka indexing service provided by Druid. the experimental results show that the Druid-based temporal data storage solution has better stream input and real-time query performance compared with the existed Hbase storage method. © 2021 ieee.

关键词： Concurrent computing Smart cities Time series analysis Memory distributed databases Real-time systems Task analysis

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Proceedings - 2022 6th ieee international conference on Robotic computing, IRC 2022

Proceedings - 2022 6th IEEE International Conference on Robo...

引用

6th ieee international conference on Robotic computing, IRC 2022

ISBN: (纸本)9781665472609

the proceedings contain 78 papers. the topics discussed include: multimodal data collection system for UAV-based precision agriculture applications;towards gesture-based cooperation with cargo handling unmanned aerial vehicles: a conceptual approach;real-time learning of wing motion correction in an unconstrained flapping-wing air vehicle;a comparative analysis of collaborative robots for autonomous mobile depalletizing tasks;mechanical exploration of the design of tactile fingertips via finite element analysis;a flexible MATLAB/Simulink simulator for robotic floating-base systems in contact with the ground;distributed computation and dynamic load balancing in modular edge robotics;gaze-based object detection in the wild;experimental assessment of feature-based lidar odometry and mapping;and beacon-based indoor fire evacuation system using augmented reality and machine learning.

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Detecting and Securing Internet of things from Wormhole attacks in a Wireless sensor Networks 6

Detecting and Securing Internet of Things from Wormhole atta...

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6th international conference on Intelligent computing and Control systems, ICICCS 2022

作者： thangavel, Karthikeyan Gayathri Lakshmi, M. Priya, S. Sathiya Srinivasan, Sathiyandrakumar University of Technology and Applied Sciences Muscat Oman Saveetha Engineering College India Panimalar Institute of Technology India Kalasalingam Academy of Research and Education India

ISBN: (纸本)9781665410359

A IoT based on Wireless sensor Networks (WSN) includes some little sensors to gather the information and offer it with the focal storehouses. these sensors are battery-driven and asset limited gadgets that consume most of the energy in detecting or gathering the information and communicating it. During information sharing, security is a significant worry in such organizations as they are inclined to numerous dangers, of which the deadliest is the wormhole assault. these assaults are sent off without gaining the fundamental data of the organization and they profoundly compromise the correspondence, security, and execution of the network. In the IoT-based network climate, its relief turns out to be more testing due to the low asset accessibility in the detecting gadgets. this research study has played out a broad writing investigation of the current procedures against the wormhole assault and arranged them as per their approach. the investigation of writing has propelled our exploration. this calculation has been intended to be basic, furthermore less convoluted to stay away from the overheads and the waste of energy in its activity. the reproduction aftereffects of our procedure show cutthroat outcomes for the identification rate and parcel conveyance proportion. It additionally gives an expanded throughput, a diminished start to finish delay, and a much-decreased utilization of energy. © 2022 ieee.

关键词： Wireless sensor networks

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