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Generative AI-Enabled Quantum Encryption Algorithm for Securing IoT-Based Healthcare Application Using Blockchain

IEEE Internet of Things Jour.a. 2025年第13期12卷 24541-24551页

作者： Prajapat, Sunil Kumar, Pankaj Das, Ashok Kumar Muhammad, Ghulam Central University of Himachal Pradesh Srinivasa Ramanujan Department of Mathematics Dharamshala176215 India International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University College of Informatics Department of Computer Science and Engineering Anam-ro Seoul145 Korea Republic of King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh11543 Saudi Arabia

The integration of Artificial Intelligence (AI) with the Internet of Things (IoT) has transformed numerous domains through the AI of Things (AIoT). Nonetheless, AIoT encounters issues related to energy usage and carbon emissions as mobile technology continues to progress. Generative AI (GAI) possesses significant potential to mitigate carbon emissions associated with AIoT, owing to its higher r.a.oning and generative powers. Conventional security protocols frequently encounter issues with computational efficiency, latency, and overall security comprehensiveness. Blockchain technology, characterized by its decentralized and immutable properties, is a viable appr.a.h for improving electronic healthcare data transmission and node authentication in IoT networks. This research examines secure data transmission and node encryption in IoT systems, with a particular emphasis on data management. Conventional appr.a.hes encounter constraints in computational efficiency, latency, and comprehensive security. This study presents a novel protocol that combines GAI and blockchain technology with quantum encryption to enhance authentication and ensure secure data transmission. The algorithm comprises multiple consecutive processes, including the encoding and transmission of node requests, followed by the authentication process utilizing hash functions and digital signatures. The authentication appr.a.h utilizes a challenge-response technique, guaranteeing that only nodes with authentic credentials can advance. Ther.a.ter, a dynamic key exchange protocol and quantum encryption method provide secure data delivery. The results indicate the procedure’s effectiveness in ensuring secure and regulated access to patient data, underscoring its significance in medical facilities. The system’s functionalities are augmented by a thorough evaluation employing machine learning. The findings indicate that the system exhibits an accuracy of 99.4%, precision of 99.10%, recall of 98.66%, F1-score of

关键词： Quantum computers

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Perfor.a.ce Evaluation of Ensemble Classifiers for.a.omaly Detection in IoT Environment 3rd

Performance Evaluation of Ensemble Classifiers for Anomaly D...

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3rd Inter.a.ional Conference on Emergent Converging Technologies and Biomedical Systems, ETBS 2023

作者： Vardhan, Aishwar.a.Kumar, Prashant Awasthi, L.K. Department of Computer Science and Engineering Dr. B.R. Ambedkar National Institute of Technology Jalandhar144011 India Department of Computer Science and Engineering National Institute of Technology Uttarakhand246125 India

ISBN: (纸本)9789819986453

Due to the reliance of the modern community on networks, the significance of efficient intrusion detection systems (IDS) cannot be ignored. As network intrusions are frequently and critically emerging, exhibiting unknown patterns, smart systems practicing machine learning appr.a.hes, have been r.a.ily explored to deal with cer.a.n issues. In this paper, we acknowledge a different ensemble-oriented appr.a.hes for detecting numerous types of outliers. The assets of ensembled techniques over common machine learning mechanisms is the competence to train an unlabeled data. Thus, they are applicable for observing unfamiliar.a.tacks. The pivotal objective of the proposed scheme is to train and test the data for.a.hieving high accuracy rate and minimal false positive rate. The experiment is implemented on NSL-KDD dataset which show that how effectively ensemble algorithms generate highly accurate models with low false positive rates. And outperforms in case of predicting unknown anomalies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Machine learning

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Zero-Shot Sentiment Analysis Exploring BArT Models 8

Zero-Shot Sentiment Analysis Exploring BART Models

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8th IEEE/ACIS Inter.a.ional Conference on Big Data, Cloud Computing, and Data Science, BCD 2023

作者： Kyritsis, Konstantinos Perikos, Isidoros Paraskevas, Michael University of Peloponnese Computer Technology Institute and Press "diophantus" Electrical and Computer Engineering Dept. Patras Greece University of Patras Computer Engineering and Informatics Department Patras Greece

ISBN: (纸本)9798350373615

The BArT model is an advanced adaptation of transformers introduced by Facebook. It has incorporated elements from both BErT and GPT transformers, enabling significant advancements in language understanding and general speech processing. Utilizing both encoder.a.d decoder components, BArT proves ver.a.ile for various tasks, including translation, text completion, automatic sentence generation, entity recognition, sentiment analysis, and more. In this study, we focus on the study of pretrained models, BArT and a modified version called distilbart, in the context of Zero-Shot Text Classification. In the experimental study we dive into the Zero-Shot technique applied to various pretrained Transformers. Our.a.alysis demonstrates that, depending on the Model we utilize, we can achieve F1 scores of up to 88%, showcasing the model's effectiveness in discerning classes for this Sentiment Analysis problem using the Zero-Shot Text Classification technique. © 2023 IEEE.

关键词： Sentiment analysis

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Transformer-Based Embeddings for Greek Language Categorization 24

Transformer-Based Embeddings for Greek Language Categorizati...

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24th IEEE/ACIS Inter.a.ional Conference on computer and Infor.a.ion Science, ICIS 2024

作者： Liapis, Charalampos M. Kyritsis, Konstantinos Perikos, Isidoros Paraskevas, Michael University of Patras Computer Technology Institute & Press 'Diophantus' Mathematics Dept. Patras26504 Greece University of Peloponnese Electrical and Computer Engineering Dept. Patras Greece University of Patras Computer Engineering and Informatics Department Patras Greece University of Peloponnese Computer Technology Institute and Press 'Diophantus' Electrical and Computer Engineering Dept. Patras Greece

ISBN: (纸本)9798350376647

The Greek School Network (GSN) provides support to students, teachers, and school units in secondary education across Greece. Handling numerous user queries manually can be challenging, necessitating the development of an automated system for.a.curate categorization of these queries. This paper presents a comparative study of various transformer-based models for multi-class text categorization of Greek language queries submitted to the GSN helpdesk. We introduce a new experimental balanced dataset and extract vector representations from eleven transformer-based models. These representations are evaluated using ten classic machine learning classifiers. Our findings highlight the superior perfor.a.ce of the Multilingual E5 Text Embeddings model, particularly when paired with the extreme gradient-boosting classifier. This combination demonstrates a clear.a.vantage in accurately categorizing user queries, paving the way for more efficient automated helpdesk systems. © 2024 IEEE.

关键词： Contrastive Learning

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Energy-Efficient Green Infor.a.ion Centric Networking for Future Wireless Communications

International Journal of Interactive Mobile Technologies

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Inter.a.ional Jour.a. of Interactive Mobile Technologies 2024年第23期18卷 149-158页

作者： Girirajan, S. Vinoth Kumar, S. Karthick, M. Saju raj, T. Ponnaian, Geetha Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Tamil Nadu India Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India Department of Computer Science and Engineering Nandha College of Technology Tamil Nadu Erode India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India

Energy-efficient green infor.a.ion-centric networking (EEGICN) is proposed in this paper for.a.vancing future wireless communication networks by addressing the challenge of energy consumption. This model can adapt the power consumption of network nodes to optimized values according to the associated link utilization. The model aimed to reduce energy consumption and incr.a.e network perfor.a.ce and stability. The EEGICN model incorporates efficient routing mechanisms, content caching strategies, and energy-intelligent communication protocols to improve resource utilization across the network infrastructure. EEGICN minimizes large data transmission, reduces power consumption, and reduces network congestion. Popular resources are cached in key network locations, and proximity data is exchanged to achieve this. The model also includes dynamic power management algorithms that adapt to changing traffic demand and network conditions to provide consistent perfor.a.ce across a variety of operational scenarios. In comparison to current wireless network systems that employ various forms of cache, the evaluation findings demonstrated that EEGICN can incr.a.e network efficiency by dramatically lowering the number of hops and energy consumption. Future networks may find this application to be a quick and easy way to transmit content. © 2024 by the authors of this article.

关键词： energy efficiency (EE) future wireless communications green infor.a.ion-centric networking infor.a.ion-centric networking (ICN) wireless network

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"SHeMeD": An Application on Secure Computation of Medical Cloud Data Based on Homomorphic Encryption 23rd

"SHeMeD": An Application on Secure Computation of Medical Cl...

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23rd Inter.a.ional Conference on Computational Science and Its Applications, ICCSA 2023

作者： Salaga, Hara Karanikolas, Nikos Kaklamanis, Christos Department of Computer Engineering and Informatics University of Patras Rion26504 Greece Computer Technology Institute and Press "Diophantus" Rion26504 Greece

ISBN: (纸本)9783031371196

In today’s Internet-centric world, two main challenges have arisen regarding data exploration: a) the privacy of sensitive data and b) the need for users to have an efficient way to manage their data. Cloud computing offers a cost-effective way towards direct data storage and access, which can function as a catalyst to modernize and update legacy systems. Although cloud computing provides efficient dynamic storage space, data security remains a concern. To this end, we propose a novel design and implementation of an application that enables secure storage of personal data in the cloud through a complete homomorphic encryption system. The application is named "SHeMed", which stands for Secure Homomorphic encryption on Medical cloud data. We have concentrated on the secure storage of medical data for br.a.t cancer patients to ensure patients’ data privacy and prevent unauthorized access. With the introduction of homomorphic encryption in the core of this application, we achieve four significant milestones regarding the secure "sealing" of data privacy: a) the user does not share the private key with the cloud provider, b) the user can proceed with implementing mathematical operations on encrypted data, c) cloud can be easily scaled and provide a convenient way to store data, d) after the implementation of mathematical operations, the new processed data may be shared with other users, mainly doctors, without providing the original ones. Our design implies that our users will need to retrieve their patient’s data just once. In this paper, we present a case study of our.a.plication that utilizes homomorphic encryption to eliminate the burden of preserving data confidentiality in the cloud and enable a convenient analysis of medical data through computations on encrypted data. © 2023, The Author(s), under exclusive license to Springer Nature Switzer.a.d AG.

关键词： Cost effectiveness

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The Multi-Way Path Over the Blockchain: The Development of the Security Algorithm rB-24-1 6

The Multi-Way Path Over the Blockchain: The Development of t...

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6th Inter.a.ional Conference on Mobile Computing and Sustainable informatics, ICMCSI 2025

作者： rajaprakash, S. Bagath Basha, C. rathish Babu, T.K.S. Karthik, S. Subapriya, V. Kavitha, S. Department of Computer Science & Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India Department of Computer Science & Engineering Kommuri Pratap Reddy Institute of Technology Telagana Hyderabad India Department of Computer Science & Engineering SRM Institute of Science and Technology Ramapuram Tamil Nadu Chennai India Department of Computer Science & Engineering Aarupadai Veedu Institute of Technology Vinayaka Missions Research Foundation Tamil Nadu Chennai India Department of Computer Science & Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522667

In the current world, a lot of new technologies are becoming famous. The Block Chain is one of these technologies. A very high amount of safety is offered by the technology in question;it is extremely robust. Users are not privy to a gr.a. deal of infor.a.ion regarding Block Chain;however, Protecting the data that is sent in multiple ways is what its security features are for. The "SalSa and rBJ25 algorithms" were still being used by this person. We are going to talk about the new "security mechanism" we have named rB-24-1. This method is comprised of these four different techniques. The procedure begins with the "Latin Alphabet code" being assigned to T. This is the first step in the process. To proceed to the next step, use Equation (1) to perform four times the multiplication of the number by itself. "Exchanging the values of the cells" is what the third step does., and it is carried out with the help of encrypted data. Putting the "SalSa" algorithm into action within the matrix constitutes the fourth step throughout the process. Finally, the plain text is converted into the encrypted text for.a.. This has been a long time coming. There is a higher level of security offered by the method that has been suggested in compare and contrast with the method that is being used at the moment. © 2025 IEEE.

关键词： Encryption algorithms

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Impact of nutrients in food quality and safety by machine learning classifier using internet of things

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Inter.a.ional Jour.a. of Infor.a.ion technology (Singapore) 2024年第5期16卷 2803-2812页

作者： Balamurugan, S. Gurumoorthi, E. Devi, P.P. Maruthamuthu, r. Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R & amp Department of IT CMR College of Engineering and Technology Telangana Hyderabad India Department of Computer Applications Madanapalle Institute of Technology and Science AP Madanapalle India

The traditional Food Supply Chain (FSC) is challenged by a number of issues, including uncer.a.nty, security, expense, complexity, and quality worries. A precise supply chain is required to address these problems. Managing the supply chain to distribute high-quality goods is a difficult task in the modern food sector. The efficient Tree Augmented Naive Bayes linked with FSC utilizing Internet of Things (IoT) is proposed in this paper to enable tracking, tracing, and managing the full food supply chain process, including supplier, exporter, and consumers. This paper's goals are to evaluate the food safety and cr.a.e the best possible chronological data for the analysis of potential future assumptions. It also intends to connect the producer.a.d the buyer by delivering high-quality food goods while using IoT technology to transport food from the producers to the customers. IoT-based food supply chain traceability is used to successfully transact data with ambiguous, unreliable, and inadequate data. In order to provide secure backdrop and food safety for FSC process utilizing IoT technology, the suggested effective Tree Augmented Naive Bayes algorithm would be able to overcome the challenges of conventional supply chain. © Bharati Vidyapeeth's institute of computer Applications and Management 2024.

关键词： Bayes classifier.a.gorithm Food safety and IoT FSC Traceability Tree augmented Naive Bayes

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Enhancing Pretrained Multilingual Machine Translation Model with Code-Switching: A Study on Chinese, English and Malay Language 24

Enhancing Pretrained Multilingual Machine Translation Model ...

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13th Inter.a.ional Conference on Computing and Pattern recognition, ICCPr 2024

作者： Liu, Haijing Seman, Noraini Department of Computer Engineering Taiyuan Institute of Technology Shanxi Taiyuan China College of Computing Informatics and Mathematics University Technology MARA Shah Alam Selangor Malaysia

ISBN: (纸本)9798400717482

In the field of multilingual machine translation, many pretrained language models have achieved the inspiring results. However, the results based on pretrained models are not yet very satisfactory for low-resource languages. This paper investigates how to leverage code-switching data to fine-tune pretrained multilingual machine translation model, in order to boost the perfor.a.ce of few-shot low resource machine translation. By utilizing a multilingual mixed corpus, the code-switching method can enhance the cross-linguistic generalization ability of the model and improve its overall understanding of the language. In this paper, on the smaller size model of FLOrES-101 benchmark, we use the code-switching data augmentation method to achieve the results of benchmark's larger model on six direction pairs of three languages, Chinese, English and Malay. This paper studied various corpus mixture mechanisms to construct the data in code-switching, and the experimental findings show that the results using the code-switching fine-tuning model improve the spBLEU score by an average of 2 to 3 points over the results without code-switching. © 2024 Copyright held by the owner.a.thor(s).

关键词： Machine translation

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Quality of Service-aware 6G-Enabled NB-IoT for Health Monitoring in Long Distance High-Speed Trains

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IEEE Transactions on Consumer Electronics 2025年第1期71卷 1136-1147页

作者： roy, Bipasha Guha roy, Deepsubhra Guha Dutta, Piyali Khan, Surbhi Bhatia Asiri, Fatima Ayadi, Manel Institute of Engineering and Management Kolkata India Institute of Engineering and Management Kolkata India University of Salford Chitkara University Institute of Engineering and Technology Chitkara University Department of Data Science United Kingdom University Centre for Research and Development Chandigarh University India Centre for Research Impact and Outcome Punjab Rajpura140401 India King Khalid University College of computer science Informatics and computer systems department Saudi Arabia Princess Nourah bint Abdulrahman University College of Computer and Information Sciences Department of Information Systems Riyadh11671 Saudi Arabia

Internet of Things connectivity in home health monitoring is a high-in-demand application ar.a. The electronics industry and procedural researchers seek high-end, secured, on-time, cost-effective ways to build reliable quality of service (QoS) proved autonomous systems using existing wireless techniques. Also, the continuous availability of a traffic-free gateway, particularly in isolated places, is necessary for large-scale data gathering and r.a.-time data update processes to function the sensor nodes in an Internet of Things (IoT) network. Improved Narrowband IoT (NB-IoT) is one of the most desirable networks offered by 6th generation (6G) connectivity in IoT-associated remote-monitoring proceedings. In this article, we propose a QoS-aware narrow bandwidth allocation-based prototype model for healthcare monitoring in long-distance high-speed trains during the patient transfer from home to the healthcare center or vice ver.a. This article demonstrates a possible enhancement in social aspects of cognitive IoT applications with large data systems in industr.a. informatics. © 1975-2011 IEEE.

关键词： Frequency allocation

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