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Lightweight group authentication protocol for secure RFID system

Multimedia Tools and Applications 2024年第41期83卷 89249-89277页

作者： Kumar, Sanjeev Banka, Haider Kaushik, Baijnath Jharkhand Dhanbad India Jharkhand Dhanbad India Associate Professor Computer Science and Engineering SMVDU Jammu and Kashmir Katra India

Nowadays, wireless technology has been widely used in healthcare and communication systems. It makes our life easier in all respects. A radiofrequency identification device (RFID) has been deployed as a wireless and identity communication device. RFID is a low-resource device that requires cryptography with limited energy regarding the minimum key size. Security and authentication between the server and the tags are key challenges for an RFID system to maintain data privacy. This article presents the security vulnerabilities of recent existing RFID authentication schemes. Keeping the focus on stringent security, privacy, and low cost, we have designed a new lightweight group authentication protocol for the robust RFID system. A single server controls multiple tags by using the proposed lightweight protocol in the RFID system. Formal and informal security analysis is performed compared to other lightweight group authentication articles in which only informal security analysis is carried out. The formal security strength of our proposed protocol is analyzed using the AVISPA (Automated Verification of Internet Security Protocol Analysis) tool, confirming that it is safe from different security threats. The newly designed protocol’s performance analysis results are measured in terms of computational cost, storage space, and communication cost. Finally, the combined consequence of security and lightweight of the proposed group authentication protocol is superior and outperforms compared to the existing scheme. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Authentication

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When Computing Follows Vehicles: Decentralized Mobility-Aware Resource Allocation for Edge-to-Cloud Continuum

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IEEE Internet of Things Journal 2025年第13期12卷 23324-23340页

作者： Nezami, Zeinab Chaniotakis, Emmanouil Pournaras, Evangelos University of Leeds School of Electronic and Electrical Engineering Leeds United Kingdom University College London Associate Professor with the Ucl Energy Institute London United Kingdom University of Leeds Professor at the School of Computer Science Leeds United Kingdom

The transformation of smart mobility is unprecedented-Autonomous, shared and electric connected vehicles, along with the urgent need to meet ambitious net-zero targets by shifting to low-carbon transport modalities result in new traffic patterns and requirements for real-time computation at large-scale, for instance, self-driving cars and augmented reality applications. The cloud computing paradigm can neither respond to such low-latency requirements nor adapt resource allocation to such dynamic spatio-temporal service requests. This paper addresses this grand challenge by introducing a novel decentralized optimization framework for mobility-aware edge-to-cloud resource allocation, service offloading, provisioning and load-balancing. In contrast to related work, this framework comes with superior efficiency and cost-effectiveness under evaluation in real-world traffic settings and mobility datasets. This breakthrough capability of 'computing follows vehicles' proves to be superior to balance resource utilization in a highly cost-effective way, while preventing service deadline violations by 14%-34%. © 2014 IEEE.

关键词： Vehicle dynamics Quality of service Resource management Costs Optimization Energy consumption Dynamic scheduling Computational modeling Servers Real-time systems

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Design and Implementation of IoT based flood alert monitoring system using microcontroller 8051

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Materials Today: Proceedings 2023年 80卷 2840-2844页

作者： Chaduvula, Kavitha Kranthi kumar, K. Markapudi, Babu Rao Rathna Jyothi, Ch. Assistant Professor Department of Information Technology Gudlavalleru Engineering College Andhraparadesh Gudlavalleru India Professor and Head Department of Information Technology Gudlavalleru Engineering College Andhraparadesh Gudlavalleru India Professor and Head Department of Computer Science and Engineering Gudlavalleru Engineering College Andhraparadesh Gudlavalleru India Associate Professor Department of Computer Science and Engineering Andhra Loyola Institute of Engineering and Technology Andhraparadesh Vijayawada India

In the Internet of Things (IoT) the physical objects network is described as "things" linked to sensors, software and other technologies to connect and share information through the Internet with other devices and systems. The floods lead to large losses of life and property in several countries. However, the absence of sufficient technology results in further death and property losses as a result of flooding in developed countries. This is because of a lack of flood alert systems. The objective of this paper is to monitor the flood situation and provide a text message warning in the event of a threat. The main aim of this paper is to detect rising river water levels at a safe distance away from the railways and to allow the respective authorities to take appropriate measures by means of SMS. A sensor is a system that senses and reacts to certain physical data. The 8051 microcontrollers were produced by Intel in 1981. The microcontroller is 8-bit. It has 40 DIP pins, 4 kb of ROM stores and 128 bytes of RAM and two timers and 16 bits. It is equipped with 2 timers. There are four parallel 8-bit ports that are programmable and adjustable as necessary. The hardware device that uses GSM mobile technology for the provision of an information link with a remote network is a GSM modem or a GSM module. A float switch is a level sensor type, a fluid control system that is used inside a tank. A condenser is a tool that stores electrical energy in an electric field. It's a passive electronic feature with two terminals. A LED is a semiconductor light source that transmits light through the flowing current. Liquid Crystal Display stands for LCD. It is a thin, flat display device used in a variety of electronics. A digital electronic level shifter is a system used in the transformation of signs from one logic or voltage domain to another, also known as logic level shifter or voltage level Translation. A diode is an electronic component with a two-terminal that mainly conducts curre

关键词： Microcontrollers

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EDRLNet: privacy preservation in online social networks via deep reinforcement learning and graph convolutional networks

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International Journal of Information Technology (Singapore) 2025年 1-10页

作者： Gowda, Nithish Ranjan Venkatesh Venugopal, K.R. Department of Computer Science and Engineering University Visvesvaraya College of Engineering Bangalore University Bengaluru India Associate Professor Department Computer Science and Engineering University Visvesvaraya College of Engineering Bangalore University Bangalore India University Visvesvaraya College of Engineering Bangalore University Bangalore India

Online social networks (OSN) have become extremely popular in the past few decades. Prominent OSN companies, such as Facebook and Twitter, control a huge amount of information on its users as well as interactions that may cause people to have major privacy concerns. The OSN information is combined with other online sources to reveal sensitive information. As a result, there is a great need to anonymize the OSN data before providing it to a third party. Thus, in this study, we propose a Deep Reinforcement Learning (DRL)-based rewiring operation that entails changing the relationships (edges) between nodes (users) without changing their degree to protect users’ privacy. To accomplish this, we introduce a novel technique for Enhanced DRL Networks called “EDRLNet” which combines an Optimized Policy Network (OPN) and Graph Convolutional Network (GCN) that preserves the essential characteristics of OSN data while anonymizing it to prevent privacy breaches. This approach employs a GCN to extract embeddings (features) from the edges and nodes. Furthermore, OPN applies the graph feature representation learned by the GCN model to policy learning. Additionally, the hyperparameters of OPN are optimized by using the Addax optimization algorithm (AOA). The suggested scheme’s performance is assessed using PageRank with mean-squared error (MSE), Root mean-squared error (RMSE), mean absolute error (MAE), Privacy score, Utility Score, Clustering coefficient, privacy and information loss. © Bharati Vidyapeeth's Institute of computer Applications and Management 2025.

关键词： Addax optimization algorithm Anonymization Deep reinforcement learning Graph convolutional network Online social network Privacy preservation

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A Hybrid Harmony Search Algorithm based on Firefly Algorithm and Boltzmann Machine

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2022年第1期49卷 241-251页

作者： Yang, J. Zhang, Xiaoxia Fu, S. Hu, Y.Y. Master Student of School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China Professor of School of computer Science and Software Engineering University of Science and Technology LiaoNing Anshan11041 China

Harmony Search Algorithm (HS) is a new meta-heuristic algorithm based on music creation process. The algorithm has been widely used in many fields because of its simple and flexible structure and fewer controlled parameters. However, HS is easy to be affected by the initial harmony memory and falls into local optimization. In addition, there are also problems, such as low searching accuracy and slow convergence speed of the optimal solution. Therefore, this paper proposes a hybrid harmony search algorithm based on firefly algorithm and boltzmann machine (HSFA-BM). First, in order to avoid the possibility of harmony search algorithm falling into local optimum, boltzmann machine (BM) mechanism is used to update the harmony memory in this paper. Second, in order to enhance the ability of the algorithm to exploit optimal solutions, this paper uses the movement mode of fireflies to generate new solutions. The improved algorithm enhances the ability of global optimization and search precision, and speeds up the convergence speed. In this paper, six classical test functions are used to test the effectiveness of the algorithm, and a very obvious optimization result is obtained. © 2022. All Rights Reserved.

关键词： Flexible structures

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Advancing Personalized Recommendation Systems with a Groundbreaking Collaborative Filtering Algorithm Driven by Machine Learning 2

Advancing Personalized Recommendation Systems with a Groundb...

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2nd IEEE International Conference on Advances in Information Technology, ICAIT 2024

作者： Anbalagan, E. Sasikumar, S. Kumar, M. Guru Vimal Paramesh, J. Sriram, K.P. Professor Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Professor Department of Computer Science and Engineering Saveetha Engineering College Chennai Associate Professor Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Professor Department of Computer Science and Engineering Mohamed Sathak A.J. College of Engineering Ekattu Siruseri Chennai India Assistant Professor Information Technology St.Joseph's Institute of Technology Chennai India

ISBN: (纸本)9798350383867

By introducing this collaborative filtering algorithm, which is dependent on machine learning that can be used in enhancing the user-based recommendation systems, this paper is trying to achieve more advanced personalized recommendation systems. Utilizing recent innovative designs of networks together with relevant contextual information, the algorithm provides high accuracy recommendation, scalability, and aids in improving user experience than traditional approaches. The model is shown to perform exceedingly well in all respects by its being subjected to a thorough assessment and compared with the baseline and enhanced models. It joins ranks with the best in all the indices of performance like precision, recall, F1-score, mean average precision and user satisfaction. In addition, hyperparameter tuning, and scalability metrics, so ending efficiency for model configuring and deployment recommendation models which could deal with large-scale datasets and offer users timely suggestions are of vital importance. To summarize, these results highlight the disruptive character of the latest machine learning algorithms that might create a new reality of recommendation systems with the trend of the time of individualization of relationships in the digital world. ©2024 IEEE.

关键词： Collaborative filtering

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Design of Multiple Share Creation with Optimal Signcryption based Secure Biometric Authentication System for Cloud Environment

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International Journal of computers and Applications 2022年第11期44卷 1047-1055页

作者： Prabhu, D. Vijay Bhanu, S. Suthir, S. Department of Computer Science and Engineering Annamalai University Chidambaram India Research Supervisor & Associate Professor Department of Computer Science and Engineering Annamalai University Chidambaram India Department of Computer Science and Engineering Annamalai University Chidambaram India

Biometric authentication plays a vital role in the cloud computing (CC) environment to accomplish security and privacy. Several kinds of biometrics are used for the authentication process, particularly, the fingerprint is a commonly used biometric, which accomplishes maximum security. But it can be easily stolen, unintentionally revealed, or difficult to remember. Therefore, biometric authentication techniques are needed and an encryption process is included to improve the security of the authentication process. In this aspect, this paper proposes a multiple share creation with an optimal signcryption-based biometric authentication system (MSCOS-BAS- FLNN- PeSeOA) for the cloud environment. The proposed model enables the creation of multiple shares of the input biometric image (fingerprint) and encrypts them for a secure authentication system. In addition, the encryption of individual shares takes place with an optimal signcryption system where the key generation process is carried out using the penguin search optimization algorithm (PeSeOA). Finally, the functional link neural network (FLNN) model is applied for the biometric authentication verification process. A wide range of simulation analyses are performed to highlight the supreme efficacy of the MSCOS-BAS- FLNN- PeSeOA technique. The experimental outcomes pointed out the hopeful performance of the MSCOS-BAS- FLNN- PeSeOA technique over the recent techniques. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Authentication

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Intelligent Irrigation Mechanism to Enhance The Sensor Network Topology by Using Machine Learning And Artificial Intelligence 2

Intelligent Irrigation Mechanism to Enhance The Sensor Netwo...

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2nd IEEE International Conference on Advances in Information Technology, ICAIT 2024

作者： Sriram, K.P. Anbalagan, E. Sasikumar, S. Kumar, M. Guru Vimal Paramesh, J. Sujatha, P. Kola Assistant Professor Information technology St.Joseph's Institute of Technology OMR Chennai – 600119 Professor Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Professor Department of Computer Science and Engineering Saveetha Engineering College Chennai Associate Professor Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Professor Department of Computer Science and Engineering Mohamed Sathak A.J. College of Engineering Ekattur OMR Siruseri Chennai Associate Professor Department of Information Technology MIT Campus Anna University Chennai Tamil Nadu India – 600044

ISBN: (纸本)9798350383867

This research paper is about the effectiveness of a fusion of machine learning and artificial intelligence into smart irrigation systems in terms of both safety and benefit of the environment and the economy in farming. We've experienced a intensive process of experiment and application of this succeeded method in a real world scenario and we've also detailed the performance of the dynamic irrigation scheduling and the adapter sensor network optimization. Results indicate a significant improvement in key metrics: scheduling was done dynamically which on average was a 10% rise in crop yield and 15% water saving, on the other hand, sensor network optimization with adaptive technology resulted into a 15% increase in cover area and 20% improvement achieved in data transmission reliability. Furthermore, the introduction of the smart irrigation system got impressive results signified by a 10 kg more production per hectare, irrigation efficiency that rose from 70% to 85%, and saving 20% of the water consumed. This calls to mind the capability of cutting-edge technologies to contribute to innovative water management paradigms, improved resource use, and security in food production in face of unpredictable climatic variability. ©2024 IEEE.

关键词： Adversarial machine learning

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A Study of Deep Learning Techniques for Predicting Breast Cancer Types

A Study of Deep Learning Techniques for Predicting Breast Ca...

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International Conference on Intelligent Systems and Sustainable Computing, ICISSC 2022

作者： Ashwini, P. Suguna, N. Vadivelan, N. Research Scholar Department of Computer Science and Engineering Faculty of Engineering and Technology Annamalai University Chidambaram India Associate Professor Department of Computer Science and Engineering Faculty of Engineering and Technology Annamalai University Chidambaram India Professor Department of Computer Science and Engineering Teegala Krishna Reddy Engineering College Hyderabad India

ISBN: (纸本)9789819947164

Breast cancer is today’s deadly health issue which causes high mortality in woman worldwide. The preliminary detection and classification may help for proper treatment of the same. Understanding the causes of this cancer using traditional machine learning techniques misread feature extraction are leading to a complication. Traditional machine learning models are best suited for feature-based raw data. The novel deep learning techniques have been introduced for diagnosis of breast abnormalities using various imaging modalities like mammogram, magnetic resonance imaging (MRI) and ultrasound with high accuracy. This survey focuses on challenges of classical machine learning models and supervene efficient prediction models using novel deep learning techniques. This review presents comparison analysis of traditional machine learning and deep learning models. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Magnetic resonance imaging

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Blockchain Technology for Secure Smart Grid Access Control

Blockchain Technology for Secure Smart Grid Access Control

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International Conference on Power engineering and Intelligent Systems, PEIS 2023

作者： Maurya, Vijendra Kumar Kothari, Rakshit Sachdev, Payal Rathore, Narendra Singh Associate Professor Department of Computer Science and Engineering Geetanjali Institute of Technical Studies Dabok Udaipur India Assistant Professor Department of Computer Science and Engineering Geetanjali Institute of Technical Studies Dabok Udaipur India Campus Director Geetanjali Institute of Technical Studies Dabok Udaipur India

ISBN: (纸本)9789819972159

The use of smart grid technologies, in the energy sector has brought about upgrade, such as high efficiency, lower operating costs and better energy management. However, it has also established security aspects. Safeguarding the smart grid is of importance due to its role as essential infrastructure. The innovative potential of blockchain holds promise in enhancing the security of the grid. This paper aims to explore how blockchain technology can be utilized for protecting the grid. It delves into the security issues associated with grids and investigates how blockchain can address them. Additionally, it provides an analysis of studies on blockchain and its application, in grid protection while considering the pros and cons of utilizing blockchain based solutions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Smart power grids

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