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Edge Computing Devices Authentication using Quantum Computing 15

Edge Computing Devices Authentication using Quantum Computin...

引用

15th International Conference on Computing communication and Networking Technologies, ICCCNT 2024

作者： Telsang, Vinayak A. Kakkasageri, Mahabaleshwar S. Devangavi, Anil D. Dept. of Computer Science and Engineering Biluru Gurubasava Mahaswamiji Institute of Technology Mudhol India Dept. Electronics and Communication Engineering Basaveshwar Engineering College Bagalkote India Dept. of Artificial Intelligence and Machine Learning Basaveshwar Engineering College Bagalkote India

ISBN: (纸本)9798350370249

Edge computing allows different technologies such as Internet of Things (IoT), vehicle-to-vehicle communications(VV), Industrial IOT (IIOT) to connect to the cloud computing to facilitate end users. The edge networks uses low bandwidth, and enhances the processing speed. With more number of IoT devices connected in the network the privacy of data stored at the edge server also under threat. Authentication is a major challenge which is be addressed to provide security and privacy to IoT devices connected in the network. The existing works uses cryptographic algorithms to solve the authentication problems, but with increase in growth of quantum computers and quantum computing, breaking the complex cryptographic algorithm is not an issue. Hence one should adopt the quantum approach to provide authentication in edge network. The proposed work uses quantum key and context information of IoT devices to store in the edge server using blockchain, which proves to be more secure. The performance analysis shows that it is better with respect to registration, encryption, decryption and authentication of IoT devices. ©2024 IEEE.

关键词： Authentication Blockchain Cryptography Edge computing Quantum key

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Integration of Q-Learning with Maximal Ratio Combining to Enhance IoT communications in Dynamic Fading Environments 12

Integration of Q-Learning with Maximal Ratio Combining to En...

引用

12th International Conference on Internet of Everything, Microwave, Embedded, communication and Networks, IEMECON 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Sharma, Rashmi Upadhyay, Abhay Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era deemed to be University Dehradun India Dept. of Electronics and Communication Engineering Graphic Era deemed to be University Dehradun India Nagpur Campus Pune India

ISBN: (纸本)9798350387315

This paper serves to show how Q-learning can be used in complement with Maximal Ratio Combining to better IoT communication systems under dynamic fading, high-density networks, and severe interference sources. The ML-enhanced MRC demonstrated promising improvements in signal strength and quality, allowing for performance that was either above or at least equal to the regular MRC. The ML-enhanced presented the added benefit of dynamic adaptation, modifying its performance to meet real-life needs by adapting to issues such as increased density and interference. These results support that integrating Q-learning into MRC-based frameworks significantly increases the reliability and efficiency of IoT communication protocols. Future investigations will aim to improve ML algorithms more appropriate for devices with few resources and evaluate their potential with state-of-the-art technology to foster future applications across intelligent IoT networks. These approaches have the potential to support more efficient operations and increased connectivity in IoT systems. © 2024 IEEE.

关键词： Fading MRC Q-Learning Wireless

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Fingerprint definition for song recognition using Machine Learning Algorithm

Fingerprint definition for song recognition using Machine Le...

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2023 International Conference on Smart systems for Applications in Electrical Sciences, ICSSES 2023

作者： Arunakumari, B.N. Shashidhar, R. Sahana, B. Jagadamba, G. Manjunath, A.S. Roopa, M. Bms Institute of Technology and Management Dept. of Computer Science and Engineering Bengaluru India Jss Science and Technology University Dept. of Electronics & Communication Engineering Mysuru India Rv College of Engineering Dept. of Electronics & Communication Engineering Bengaluru India Siddaganga Institte of Technology Dept. of Information Science and Engineering Tumkuru India Jss Science and Technology University Dept. of Master of Computer Applications Mysuru India Dayananda Sagar College of Engineering Dept. of Electronics & Communication Bengaluru India

ISBN: (纸本)9798350347296

A condensed content-based signature that summarises an audio recording is known as an audio fingerprint. Audio The capability to recognize music regardless of design and without the use of meta-data or watermark embedding has made fingerprinting technologies popular. In. tegrity checking, watermark support, and content-based aural retrieval are additional applications for fingerprinting. The various methods of fingerprinting have been discussed using various justifications and terminologies, such as pattern matching, multimedia information retrieval, or cryptography. It is a distinct and condensed digest created using perceptually important elements of a video. Audio material can be monitored using fingerprinting technologies without requiring embedding of metadata or watermarks. However, audio fingerprinting has extra applications The algorithm is trained using thousands of mini audio speech commands. In order to improve the training efficiency, audio features are extracted during a pre-processing. The accuracy of the developed model is 83.7%. © 2023 IEEE.

关键词： Cryptography

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Enhancing VANET Efficiency with ACRR Technique for Improved Traffic Management and Network Scalability

Enhancing VANET Efficiency with ACRR Technique for Improved ...

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2024 International Conference on Science, Technology, engineering and Management, ICSTEM 2024

作者： Karthick, K. Talari, Praveen Nishadevi, V. Krishna Prakash, R. Asokan, R. Velusamy, A. Dept. of Computer Science and Engineering Kongunadu College of Engineering and Technology Tamilnadu Trichy India Dept. of Computer Science and Engineering Vignan Bharathi institute of technology Telangana Hyderabad India Dept. of Computer Science and Engineering Mahendra College of Engineering Tamilnadu Salem India Dept. of Information Technology Sona College of Technology Salem India Dept. of Electronics and Communication Engineering Kongunadu College of Engineering and Technology Tamilnadu Trichy India Dept. of Information Technology Sona College of Technology Tamil Nadu Salem India

ISBN: (纸本)9798350376913

The role of Vehicular Ad Hoc Networks (VANETs) is crucial in enabling Intelligent Transportation system (ITS) technologies such as safe financial transactions, media applications, and effective traffic control. As traffic increases, the topology of vehicular networks is in constant flux, and the sparse distribution of vehicles, particularly on highways, presents challenges for network scalability. This situation makes it difficult for cars to keep consistent routes inside the network, which affects the stability of the network. To address these challenges, the developed Adaptive-ant Colony based Randomized Recommendation (ACRR) technique emerges as a unique solution for enhancing VANETs by reducing travel time. In instances of high traffic density on busy roads, the ACRR algorithm is effectively utilized to group vehicles. Leveraging data collected from these densely populated road segments, the system identifies congestion-prone areas and formulates optimal vehicle routes based on customized vehicle groupings. The framework's performance evaluation encompasses various parameters, including packet loss, message transmission rate, energy consumption, and average cluster growth. The proposed VANET framework, empowered by the ACRR algorithm, achieves an impressive message transmission rate of approximately 80%. In comparison, alternative methods like Re-RouTE exhibit a limited transmission rate of 70%, while others such as Net Run Rate (NRR), DIVERT 30, and DIVERT-60 demonstrate rates below 20%. Furthermore, the framework's parcel loss is significantly reduced to only 33% of that observed in the standard VANET framework. As a result, the ACRR algorithm integrated into the VANET framework demonstrates notable efficiency when compared to other approaches. It is crucial to recognize that, even with a refined technique, managing traffic congestion remains challenging if drivers disregard the recommended routing suggestions. Overall, this research offers insights into the p

关键词： Traffic congestion

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Adaptive Strategies for Maximizing Spectral Efficiency in dual branch MRC systems Facing non-Uniform Fading Patterns 12

Adaptive Strategies for Maximizing Spectral Efficiency in du...

引用

12th International Conference on Internet of Everything, Microwave, Embedded, communication and Networks, IEMECON 2024

ISBN: (纸本)9798350387315

The presented research paper investigates the development and performance of adaptive strategies for nonuniform fading patterns in dual-branch Maximal Ratio Combining systems. The study employs key enabling strategies, including power control, adaptive modulation, and antenna selection, with the purpose of improving the spectral efficiency and reliability of wireless communication systems. Conducting simulations in MATLAB and Python, this paper presents a comprehensive analysis using heatmaps, 3D surface plots, and dynamic simulation outputs to show the effect of the strategies under different Signal-to-Noise Ratios and fading conditions. The outcomes, illustrated in a clear-cut manner in the visuals, reveal that the adaptive strategies lead to a drastic reduction in the Bit Error Rates and a more optimal distribution of power across the branches, ensuring highly effective performance even in the case of the most challenging non-uniform fading patterns. Ultimately, the research findings show sight into the necessity of adaptive strategies to ensure proper coverage and quality of communication in non-uniform fading conditions, which novel research could benefit from. © 2024 IEEE.

关键词： MATLAB

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A New Transition Structure between Microstrip and Substrate Integrated Waveguide 10

A New Transition Structure between Microstrip and Substrate ...

引用

10th IEEE Asia-Pacific Conference on Applied Electromagnetics, APACE 2024

作者： Kang, Huijune Park, Kyungmin Yoo, Minjong Jang, Youna Ahn, Dal Soonchunhyang University Dept. of ICT Convergence Asan-Si Korea Republic of Soonchunhyang University Dept. of Electrical Communication System Engineering Asan-Si Korea Republic of Soonchunhyang University Dept. of Electrical Engineering Asan-Si Korea Republic of

ISBN: (纸本)9798350364163

In this paper, transition structures from microstrip to SIW (Substrate Integrated Waveguide) are proposed for an efficient transition. Transition structures reduce return loss and insertion loss by eliminating electric field discontinuity and impedance matching between microstrip and SIW. This paper proposes two transition structures using tapered lines. In the first transition structure, both the tapered lines and the SIW are designed on a single substrate. In the second transition structure, the SIW, which is designed on a separate substrate, is laminated over the substrate with the tapered lines. The single-substrate transition structure has the advantages of a simple manufacturing process and lower cost, while the laminated transition structure offers advantages in terms of design flexibility, performance optimisation and miniaturization. Both designs have reflection loss of less than 20dB and insertion loss of less than 3dB in the frequency range of 8~12GHz. © 2024 IEEE.

关键词： Substrate integrated waveguides

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Experimental Validation of Blockchain Based Triple Branch MRC for Secured communication in Adverse Fading Conditions

Experimental Validation of Blockchain Based Triple Branch MR...

引用

2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Upadhyay, Deepak Upadhyay, Abhay Gupta, Mridul Sharma, Kunj Bihari Maindola, Meenakshi Garg, Shobhit Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to be University Dept. of Management Studies Dehradun India

ISBN: (纸本)9798350364866

The investigation in this study entails integrating blockchain technology with maximal ratio combining in a triple branch configuration for secure communications under multipath fading conditions. The proposed combines blockchain's decentralized and immutable characteristics with MRC's communication outcomes and flaws, which are worsened by the multipath fading channels. To evaluate this, the team carried out various empirical tests with the key findings being the Signal-to-Noise Ratio performance. Since the blockchain integrated system is anticipated to exhibit a higher SNR, our results showed a substantial increase in SNR. This confirms the robust and secure communication capabilities of the integrated solution under study. Therefore, the researchers demonstrate how blockchain can greatly enhance security as well as the quality of the communication, presenting a better solution in challenging data transmission conditions. This study establishes the foundation for further research on blockchain technology applications in the communication field. © 2024 IEEE.

关键词： Blockchain

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Design of Broadband Microstrip Interdigital Bandpass Filter Using Coupling Matrix 10

Design of Broadband Microstrip Interdigital Bandpass Filter ...

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10th IEEE Asia-Pacific Conference on Applied Electromagnetics, APACE 2024

作者： Park, Kyungmin Yoo, Minjong Kang, Huijune Jang, Youna Ahn, Dal Soonchunhyang University Dept. of ICT Convergence Asan-Si Korea Republic of Soonchunhyang University Dept. of Electric Communication System Engineering Asan-Si Korea Republic of Soonchunhyang University Dept. of Electrical Engineering Asan-Si Korea Republic of

ISBN: (纸本)9798350364163

This paper proposes a structure for a 15th order interdigital bandpass filter in the S-band range, designed by extracting the group delay and coupling coefficients through EM simulation using a coupling matrix. The proposed filter is designed as a broadband filter with a center frequency of 3.75 GHz and a bandwidth of 2 GHz. The designed filter has an insertion loss of 3.78 dB and a return loss of 12.17 dB in the specified frequency band. Additionally, to achieve miniaturization, a substrate with a dielectric constant of 10.2 was used, and the substrate's dimensions are 28.5 × 9.5 × 4.4 mm3 © 2024 IEEE.

关键词： Group delay

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Machine Learning Approaches for Predictive Channel State Information in MIMO systems Using LSTM 2

Machine Learning Approaches for Predictive Channel State Inf...

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2nd International Conference on Advanced Computing and communication Technologies, ICACCTech 2024

作者： Upadhyay, Deepak Sharma, Amulya Gupta, Mridul Devgan, Divyansh Garg, Shobhit Upadhyay, Abhay Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to be University Dept. of Management Studies Dehradun India

ISBN: (纸本)9798331519056

In this paper, we analyse machine learning models, including Long Short-Term Memory networks, to predict the CSI and evaluate their impact on adaptive transmission in MIMO systems. To achieve this objective, we use simulation to generate CSI data in a MIMO environment and compare the performance of ML models to traditional methods. Our simulation reveals using our dataset that LSTM models improve the SNR values significantly, which means that their predictions are more accurate. At the same time, these models require greater computational and other resources. In contrast, despite its relative inefficiency in comparison with LSTM, Decision Trees improve the SNR moderately while consuming fewer resources but needing a substantial amount of time. Analysis of the source tries to examine the balance between performance and resource usage may validate the use of ML-based methods, and especially LSTM, to predict the CSI advancedly, but the actual application must take constraints into account. © 2024 IEEE.

关键词： Contrastive Learning

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Improved Heart Sound Classification Using LSTM Based Deep Learning Technique 5

Improved Heart Sound Classification Using LSTM Based Deep Le...

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5th International Conference on Intelligent communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Naveen Sundar, G. Subramanian, Suresh Narmadha, D. Malin Bruntha, P. Iwin Thanakumar Joseph, S. Saravanan, S. Karunya Institute of Technology and Sciences Dept. of Computer Science and Engineering Coimbatore India Saveetha School of Engineering Dept. of Electronics and Communication Chennai India Karunya Institute of Technology and Sciences Dept. of Electronics and Communication Engineering Coimbatore India Koneru Lakshmaiah Education Foundation Dept. of Cse Vaddeswaram India Vellore Institute of Technology Dept. of Multimedia Vellore India

ISBN: (纸本)9798350385649

The goal of this research is to categorize heart sounds using phonocardiogram (PCG) data using machine learning and deep learning techniques, which are crucial for the early diagnosis of cardiovascular illness. The five different classes that make up the dataset are extrastole, extrahls, murmur, artefact, and normal. In order to extract features using Mel-frequency cepstral coefficients (MFCC), preprocessing entails normalization. This is essential for capturing distinctive sound characteristics. For classification, four models are used: Random Forest, Recurrent Neural Network (RNN), Multilayer Perceptron (MLP), and Long Short-Term Memory (LSTM). The results demonstrate how well LSTM performs, with an astounding accuracy of almost 94.5% in heart sound classification. This result emphasizes how useful deep learning architectures-in particular, LSTM-are for heart sound classification tasks that depend on MFCC-based features. According to the study, LSTM-based approaches have the potential to greatly improve identification precision and accuracy. © 2024 IEEE.

关键词： Long short-term memory

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