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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Joykutty, Anu Maria Baranidharan, B. Rajagiri School of Engineering & Technology Department of Computer Science & Engineering Kochi India SRM Institute of Science & Technology Department of Computing Technologies Chennai India

ISBN: (纸本)9798331300579

With the use of cognitive radio (CR) technology, wireless devices can utilize licensed spectrum when it is unused by the licensed users. CR was developed as a response to the wireless spectrum shortage issue caused by the static spectrum allocation. Using CR technology, the unlicensed users can opportunistically access the spectrum during the absence of usage by the licensed users. Clustering is a widely used technique in Cognitive Radio Networks (CRNs) to efficiently manage network resources, optimize spectrum utilization, and enhance overall network performance. This study focuses on the applications of clustering techniques in the area of CRNs like spectrum management, QoS Support, topology management, energy efficiency, routing etc. © Grenze Scientific Society, 2024.

关键词： Cognitive radio

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A Three Layer authentication using FEO 4

A Three Layer authentication using FEO

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4th IEEE International Conference on Data engineering and Communication Systems, ICDECS 2024

作者： Hanji, Bhagyashri R Aishwarya, E. Poojitha, B.V. Anushree, H.R. Chinmayi, T.K. Dayananda Sagar Academy of Technology and Management Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350393354

In the contemporary digital landscape, ensuring robust security measures is imperative to safeguard sensitive information and transactions. This work introduces an innovative Three-Level Authentication System that incorporates facial recognition, eye blink password, and OTP (One-Time Password) generation to enhance security and improve the user experience. The initial level of authentication leverages advanced facial recognition technology. Employing sophisticated algorithms, the system analyzes and verifies unique facial features, establishing a secure foundational layer for user identification. The second level introduces the groundbreaking concept of Eye Blink Password, utilizing distinctive eye gestures and blinks for authentication. This biometric approach not only enhances security but also provides a memorable and user-friendly authentication method. The third level further bolsters security by generating dynamic OTPs, introducing a time-sensitive element that significantly reduces the risk of unauthorized access, especially during online transactions. This system proves beneficial in safeguarding against thermal attacks, which exploit heat signatures to capture sensitive information, as well as shoulder surfing, a threat that relies on visual observation. By combining these three authentication levels, the proposed system offers a comprehensive and robust approach to security, addressing various potential vulnerabilities and providing a more secure digital environment. © 2024 IEEE.

关键词： Authentication

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A Lightweight Security Algorithm for Authenticating Mobile Transactions using Wearable Devices and ECC Based Signcryption 10

A Lightweight Security Algorithm for Authenticating Mobile T...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Harrish, A. David, Shibin Karunya Institute of Technology and Sciences Division of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350384369

Internet of Things (IoT) devices are intelligent and act as the core component for capturing transactional data, initiating communication with wearable devices. Wearable devices such as smartwatches or smart wristbands serve as the user's payment interface. It aligns with near field communication (NFC) technology which gets connected with payment terminals at a closer range. As these terminals have secure payment gateways like Unified Payment Interface (UPI) and other intermediaries, transactions between the user's bank account and the merchant will be easier. To prove authorization in the transaction, an additional layer of security called vein pattern authentication is invoked. Alongside, elliptic curve cryptography (ECC) based signcryption ensures secure transactions by encrypting and digitally signing the payment data which guarantees confidentiality and non-repudiation. Therefore, a system that adds additional security to the mobile transactions by appending vein pattern and ECC-based signcryption technique. As a result, confidentiality, authorization, and robustness in the transaction is achieved at a higher rate by inculcating forward secrecy, verifiability and non-repudiation. © 2024 IEEE.

关键词： Gateways (computer networks)

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A Multi-Faceted Approach for Underwater Sonar Rock vs Mine Classification Using Machine Techniques 1

A Multi-Faceted Approach for Underwater Sonar Rock vs Mine C...

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1st International Conference on Cognitive, Green and Ubiquitous Computing, IC-CGU 2024

作者： Sahoo, Sasmita Mohanta, Raj Kumar Pani, Prangya Paramita Mohapatra, Sunil Kumar Chakravarty, Sujata Centurion University of Technology and Management Department of Computer Science & Engineering Bhubaneswar India

ISBN: (纸本)9798350361780

A significant challenge of underwater object classification distinguishing sonar rocks from buried mines is crucial in maritime and naval security, as the enemy country has planned explosive mines in the ocean. Furthermore, there is a possibility of encountering rocks. This research is motivated by the urgent need for reliable and efficient underwater detection methods, which have a variety of applications in environmental studies and maritime security. Many classification methods, from traditional algorithms to modern deep learning models, have been used to identify the unique patterns in sonar data. This study enhances the accuracy of the existing system capable of classifying between mines and rocks beneath the submarine to protect human resources and marine life. Our comprehensive approach integrates data preprocessing, feature extraction, and several machine learning classification techniques such as KNN, NB, SVM, Decision Tree, Random Forest, and neural network by utilizing the Sonar Mines vs. Rocks data to classify the object. The outcome of this research shows that a high accuracy of 98% was achieved in the LDA grid approach followed by 94 % in SVM (rbf), and 88-91% in neural network and boosting techniques. This research work also provides a smart web interface allowing users to input sonar data and receive real-time classification results. © 2024 IEEE.

关键词： Sonar

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GDformer: A lightweight decoder for efficient semantic segmentation of remote sensing Urban Scene Imagery 4

GDformer: A lightweight decoder for efficient semantic segme...

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4th International Conference on computer Vision and Data Mining, ICCVDM 2023

作者： Liu, Bing Zhong, Zhaohao School of Computer Science and Engineering Changchun University of Technology Changchun130012 China

ISBN: (纸本)9781510674448

Semantic segmentation of remote sensing urban scene imagery is a dense prediction task, which has been applied to the land-cover or land-use category. However, the dimension of remote sensing image is huge, which will result in the huge computation cost. In order to reduce the computation cost, a common method is to design a lightweight decoder to achieve a good trade-off between accuracy and computation cost. For this purpose, we design a lightweight transformer-based decoder GDformer. The GDformer consists of our proposed Global Value Transformer and Dynamic feature fusion module. The Global Value Transformer can extract the global semantic feature and the Dynamic feature fusion module can fuse the local feature and global semantic feature dynamic to capture the local-global context with a good trade-off, and the local-global context has been proved is necessary for the semantic segmentation of remote sensing. Extensive experiments prove that our proposed method can achieve a good trade-off between and state-of-the-art performance. © 2024 SPIE.

关键词： Remote sensing

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Systematic evaluation of hybrid steganography approach towards secure communication in IoT 1

Systematic evaluation of hybrid steganography approach towar...

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1st IEEE International Conference on Cognitive Robotics and Intelligent Systems, ICC - ROBINS 2024

作者： Gayathri, S. Appathurai, K. Sadish Sendil, M. Gowri, S. Surendran, R. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India Kg College of Arts and Science Department of Computer Technology Coimbatore India Guru Nanak Institute of Technology Department of Emerging Technologies Telegana 501506 India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798350372748

ISBN: (纸本)9798350372748

The proliferation of real-world internet connectivity has led to a convergence of a large number of people accessing common cloud facilities. While this has facilitated increased data sharing in the cloud, it has also raised concerns regarding data privacy and security. It is crucial for both cloud service providers and users to ensure the security of data in all aspects. However, the development of weighted algorithms aimed at enhancing security often leads to increased latency and degradation of cloud performance. The system presented in this study addresses the challenges of creating a secure environment and evaluates a proposed framework using hybrid steganography. In this system, the cover image, input data, and a uniquely generated secret key are considered for hybridization. The embedded image undergoes the Sum of Absolute Difference (SAD) algorithm for steganography, followed by the Discrete Wavelet Transform (DWT) process for image transformation before being communicated over the channel. At the receiving end, the reverse process is executed to extract the original information, contingent upon the correlation with the secret key. The proposed approach achieves an MSE (Mean Squared Error) of -0.52141 and a PSNR (Peak Signal-to-Noise Ratio) of 48 dB, demonstrating improved performance compared to existing approaches. © 2024 IEEE.

关键词： Steganography

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Blockchain-Based Federated Learning for IoT Sharing: Incentive Scheme with Reputation Mechanism 5th

Blockchain-Based Federated Learning for IoT Sharing: Incent...

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5th International Conference on Blockchain and Trustworthy Systems, BlockSys 2023

作者： Cai, Ting Li, Xiaoli Chen, Wuhui Wei, Zimei Ye, Zhiwei School of Computer Science and Engineering Hubei University of Technology Wuhan430068 China School of Computer Science and Engineering Hubei University of Arts and Science Xiangyang441053 China School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China

ISBN: (纸本)9789819981007

Huge amounts of data produced by millions of IoT devices are expected to be shared and leveraged as the cornerstone of real-world IoT applications, such as industrial IoT, smart grid, and intelligent transportation system. However, there still exist bottlenecks when implementing IoT sharing, such as the privacy leakage of user data, IoT data quality, and incentives for sharing these data. In this paper, we propose an online incentive framework for model sharing based on blockchain and federated learning to improve the privacy protection of IoT data. To ensure the quality of submitted data, a reputation mechanism is further designed to punish the users who do not complete the model-sharing task. Based on these settings, the model sharing problem based on federated learning is formulated as an online incentive mechanism, then we use deep reinforcement learning to obtain optimal sets of sharing users with the goal of maximizing long-term social welfare. Numerical results indicate the effectiveness of the proposed framework and incentive mechanism in IoT sharing. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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ProctorXam - Online Exam Proctoring Tool 1

ProctorXam - Online Exam Proctoring Tool

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1st IEEE International Conference on Electronics, Computing, Communication and Control technology, ICECCC 2024

作者： Ashwini, S. Bhuvan Kumar, M.S. Chandra Sai, D. Sathya, V. Atria Institute of Technology Dept. of Computer Science & Engineering Bangalore India

ISBN: (数字)9798350371802

ISBN: (纸本)9798350371802

Robust exam monitoring solutions are now essential in light of the most notable Covid-19 outbreak and the increasing inclination towards virtual learning. The automated method for supervising online exams that is suggested in this paper is intended to lessen the difficulties associated with exam cheating. With the assistance of our system's clever face detection algorithms, instructors may efficiently identify suspicious conduct by monitoring students' web activity and camera feed in real-time. Unlike earlier systems, ours provides improved accuracy and functionality, guaranteeing the authenticity of online tests. In light of the difficulties presented by the epidemic, this research attempts to offer a workable option for academic institutions and people wishing to administer fair and secure online exams. © 2024 IEEE.

关键词： Face recognition

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Financial Zen: Achieving Market Harmony through Reinforcement Learning and Algorithmic Trading 2

Financial Zen: Achieving Market Harmony through Reinforcemen...

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2nd International Conference on Data science and Information System, ICDSIS 2024

作者： Sowmya, M.R. Chhetri, Diwash Khatri Chai, Kumar Rohit Ashraf, Suhail Nitte Meenakshi Institute Of Technology Department Of Computer Science And Engineering Bengaluru India

ISBN: (纸本)9798350381665

Algorithmic trading, utilizing reinforcement learning, has attracted significant attention for its adaptability and potential in present financial markets. This research combines Deep Deterministic Policy Gradients (DDPG), Advantage Actor-Critic (AAC), and Proximal Policy Optimization (PPO) algorithms for a comprehensive trading system. To address memory constraints, a load-on-demand technique manages large datasets. Performance is evaluated across 30 Dow Jones stocks, compared to the Dow Jones Industrial Average (DJIA) and a minimum-variance portfolio. Results show the integrated approach outperforms traditional strategies in annualized return, Sharpe ratio, and maximum drawdown. This study contributes to algo-trading literature by leveraging multiple reinforcement learning algorithms, offering benefits for investors in dynamic markets. © 2024 IEEE.

关键词： Reinforcement learning

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A Comparative Study on the Properties of Carbon Fiber-Reinforced Polymer Composites Developed by Hand Layup and Vacuum Bagging Molding Techniques

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Journal of The Institution of Engineers (India): Series D 2024年第1期106卷 263-275页

作者： Amar, Thakur Abhinav Kumar, Amit Yadav, D.K. Department of Production and Industrial Engineering Birla Institute of Technology Jharkhand Mesra Ranchi835215 India Department of Mechanical Engineering National Institute of Technology Bihar Patna800005 India Department of Computer Science and Engineering National Institute of Technology Jharkhand Jamshedpur831014 India

The present study addressed the fabrication of carbon fiber-reinforced polymer (CFRP) composites using two different techniques: manual layup and vacuum bagging molding. The purpose was to compare their unique properties. CFRP composites employ woven roving mat carbon fiber as a reinforcing material, combined with an epoxy matrix consisting of Araldite and hardener. The resin to fiber ratio has been maintained at a 1:1 ratio, while the resin to hardener ratio has been maintained at a 10:1 ratio by weight. Various stacking sequences of carbon/epoxy composites (0/90) were made using both approaches. Optimization of several process parameters was carried out to enhance the mechanical properties of the polymer composites. Every laminate was composed of four to eight layers. Various carbon/epoxy composite orientations were subjected to testing until failure using a universal testing machine, in accordance with the relevant applicable standards (ASTM-D3039), in order to determine the ultimate tensile strength, % elongation (or ductility), and elastic constant. Furthermore, the adhesion intensity between the fiber and resin was assessed by conducting microstructural studies using a scanning electron microscope. The results demonstrated that the samples fabricated using the vacuum bagging mold technique exhibited superior tensile strength compared to the samples fabricated using the hand layup approach. © 2024, The Institution of Engineers (India).

关键词： Resins

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