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Recent Developments in Authentication Schemes Used in Machine-Type Communication Devices in Machine-to-Machine Communication: Issues and Challenges

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computers, Materials & Continua 2024年第4期79卷 93-115页

作者： Shafi Ullah Sibghat Ullah Bazai Mohammad Imran Qazi Mudassar Ilyas Abid Mehmood Muhammad Asim Saleem Muhmmad Aasim Rafique Arsalan Haider Ilyas Khan Sajid Iqbal Yonis Gulzar Kauser Hameed Department of Computer Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Department of Information Technology Balochistan University of Information TechnologyEngineeringand Management SciencesQuetta87300Pakistan Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Management Information Systems College of Business AdministrationKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Software Engineering College of ComputingRiphah International UniversityFaisalabad44000Pakistan Department of Electrical Engineering Balochistan University of Information Technology Engineeringand Management SciencesQuetta87300Pakistan Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.

关键词： Authentication cyber security internet of things machine-type communication devices machine-to-machine communication

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Indic Language Empowerment in E-commerce: Integrating Generative Translations and Vectorized Searches 1

Indic Language Empowerment in E-commerce: Integrating Genera...

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1st International Conference on AIML-Applications for engineering and technology, ICAET 2025

作者： Bhosale, Parth Gopale, Kunal Taware, Karan Bewoor, Laxmi Vishwakarma Institute Of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350355611

E-commerce has revolutionized the retail landscape, offering consumers unparalleled convenience and a vast array of choices from the comfort of their homes. Enabling e-commerce in native languages is crucial for creating an inclusive shopping experience, allowing businesses to effectively reach and engage diverse linguistic communities. India is renowned for its multilingual and cultural legacy and this work is an attempt to reach a wider consumer base and increase market potential in India by providing online shopping for cultural festivals. The proposed work is an attempt to develop native language E-commerce platform for various festivals celebrated in India by using Large Language Models (LLM) to generate contextually rich and relevant contents making the user experience more intuitive and personalized. Finally, we talk about making search features better by using modern technology. By using smart algorithms and models, we help users search for products in their own language, and show them results that are most relevant to what they're looking for. Through careful testing and analysis, we show that our solution works well in improving how people interact with e-commerce websites, reaching more customers, and making more sales. Our research is important because it helps bridge the language gap online, giving businesses new opportunities to grow and making online shopping more accessible for everyone. © 2025 IEEE.

关键词： Marketplaces

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Safe Route - IoT and AI-based Fire Evacuation System for Smart Buildings 1

Safe Route - IoT and AI-based Fire Evacuation System for Sma...

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1st International Conference on Electronics, Communication and Signal Processing, ICECSP 2024

作者： Kuchewar, Prajwal Patil, Yash Achrekar, Atharva Shewale, Suyash Aher, Chetan N. Computer Engineering AISSMS Institute of Information Technology Pune India

ISBN: (纸本)9798350364590

This research introduces an innovative approach using IoT sensors and Ant Colony Optimization (ACO) to optimize evacuation routes in emergency preparedness. The system architecture allows for seamless communication between IoT sensors and the ACO algorithm, enabling timely decision-making in emergency scenarios. The study uses diverse datasets to enhance adaptability and comprehensiveness, paving the way for a transformative paradigm in fire safety for smart buildings. The ACO algorithm's performance is compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC) algorithm. Evaluation criteria include convergence time, number of iterations, and total running time. Results show that the ACO algorithm consistently outperforms or matches other algorithms across all graph complexities. It converges faster and achieves shorter runtimes, with improvements becoming more pronounced as graph complexity increases. The ACO algorithm's effectiveness in solving complex shortest path problems is demonstrated through rigorous analysis and comparison. © 2024 IEEE.

关键词： Genetic algorithms

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Unveiling the Art of Effective Learning through Spaced Repetition and Evidence-Based Techniques 2

Unveiling the Art of Effective Learning through Spaced Repet...

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2nd IEEE International Conference on Contemporary Computing and Communications, InC4 2024

作者： Narkhede, Kshitij Patil, Ratnakar Kasat, Aman Gawas, Atharva More, Priyanka Vishwakarma Institute of Information Technology Computer Engineering Pune India

ISBN: (纸本)9798350383652

This study critically examines the limitations of traditional learning methods, such as cramming, re-reading, and massed practice, which often result in suboptimal long-term retention and understanding. The paper proposes an integrated approach, emphasizing the pivotal role of Spaced Repetition alongside other evidence-based techniques. By exploring Active Recall, Desirable Difficulties, Elaboration, Interleaving, Concrete Examples, Dual Coding, and Distributed Practice, this research harmonizes cognitive psychology and neuroscience principles. The integrated approach outlined in the paper aims to enhance memory, comprehension, and problem-solving, catering to learners of diverse paces and abilities. The essence of evidence-based learning is embodied in the strategies presented, promising effective and enduring knowledge acquisition. Ultimately, this paper offers insights for educators and students, demonstrating practical applications for teaching and learning that leverage these evidence-based techniques, particularly emphasizing the significance of Spaced Repetition. © 2024 IEEE.

关键词： Contrastive Learning

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Improved Harris Hawks Algorithm and Its Application in Feature Selection

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computers, Materials & Continua 2024年第10期81卷 1251-1273页

作者： Qianqian Zhang Yingmei Li Jianjun Zhan Shan Chen School of Computer Science and Information Engineering Harbin Normal UniversityHarbin150025China College of Systems Engineering National University of Defense TechnologyChangsha410073China

This research focuses on improving the Harris’Hawks Optimization algorithm(HHO)by tackling several of its shortcomings,including insufficient population diversity,an imbalance in exploration ***,and a lack of thorough exploitation *** tackle these shortcomings,it proposes enhancements from three distinct perspectives:an initialization technique for populations grounded in opposition-based learning,a strategy for updating escape energy factors to improve the equilibrium between exploitation and exploration,and a comprehensive exploitation approach that utilizes variable neighborhood search along with mutation *** effectiveness of the Improved Harris Hawks Optimization algorithm(IHHO)is assessed by comparing it to five leading algorithms across 23 benchmark test *** findings indicate that the IHHO surpasses several contemporary algorithms its problem-solving ***,this paper introduces a feature selection method leveraging the IHHO algorithm(IHHO-FS)to address challenges such as low efficiency in feature selection and high computational costs(time to find the optimal feature combination and model response time)associated with high-dimensional *** analyses between IHHO-FS and six other advanced feature selection methods are conducted across eight *** results demonstrate that IHHO-FS significantly reduces the computational costs associated with classification models by lowering data dimensionality,while also enhancing the efficiency of feature ***,IHHO-FS shows strong competitiveness relative to numerous algorithms.

关键词： HHO IHHO population diversity energy factor update strategy deep exploitation strategy feature selection

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Analysis of Software Trustworthiness Based on FAHP-CRITIC Method

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Journal of Shanghai Jiaotong university(Science) 2024年第3期29卷 588-600页

作者：高晓彤马艳芳周伟 School of Computer Science and Technology Huaibei Normal UniversityHuaibei 235000AnhuiChina School of Computer Science and Information Engineering Changzhou Institute of TechnologyChangzhou 213000JiangsuChina

Software trustworthiness includes many *** weight allocation of trustworthy at-tributes plays a key role in the software trustworthiness *** practical application,attribute weight usually comes from experts'evaluation to attributes and hidden information derived from ***,when the weight of attributes is researched,it is necessary to consider weight from subjective and objective ***,a novel weight allocation method is proposed by combining the fuzzy analytical hierarchy process(FAHP)method and the criteria importance though intercrieria correlation(CRITIC)***,based on the weight allocation method,the trustworthiness measurement models of component-based software are estab-lished according to the seven combination structures of ***,the model reasonability is verified via proving some metric ***,a case is carried *** to the comparison with other models,the result shows that the model has the advantage of utilizing hidden information fully and analyzing the com-bination of components *** is an important guide for measuring the trustworthiness measurement of component-based software.

关键词： trustworthiness weight component-based software measurement

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Motor Imagery Classification Using Single Channel of EEG in Online Brain-computer Interface 10

Motor Imagery Classification Using Single Channel of EEG in ...

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10th International Conference on Web Research, ICWR 2024

作者： Taghizadeh, Maryam Chalechale, Abdolah Razi University Computer Engineering and Information Technology Kermanshah Iran

ISBN: (纸本)9798350394986

This paper presents an efficient method with simplified calculations for classifying left and right hand movement imagery using a single channel of EEG to design a brain-computer interface (BCI) system. The proposed method utilizes wavelet transform to decompose EEG signals into multiple frequency bands. The classification task is performed using the support vector machine (SVM) with the radial basis function (RBF) kernel and the K-nearest neighbor (KNN) algorithm. This paper introduces and compares two techniques that are based on the sixth and eighth levels produced from a deconstructed single C3 channel. For feature extraction, statistical information such as variance, standard deviation, and signal power are individually considered. The achieved results indicate high accuracy for left and right-hand movement, with 100% accuracy for left-hand movement and 87.47% accuracy for right-hand movement. These results were accomplished using SVM with the RBF kernel and KNN algorithms, based on power features extracted from the eighth-level EEG signal. Compared to prior methods utilizing single-channel and multi-channel approaches, this method demonstrates superior performance. © 2024 IEEE.

关键词： Wavelet transforms

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Cat Swarm Algorithm Generated Based on Genetic Programming Framework Applied in Digital Watermarking

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computers, Materials & Continua 2025年第5期83卷 3135-3163页

作者： Shu-Chuan Chu Libin Fu Jeng-Shyang Pan Xingsi Xue Min Liu School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210000China College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266000China Department of Information Management Chaoyang University of TechnologyTaichung40601TaiwanChina School of Information Science and Engineering Fujian University of TechnologyFuzhou350000China Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resource Nanjing University of Information Science and TechnologyNanjing210000China

Evolutionary algorithms have been extensively utilized in practical ***,manually designed population updating formulas are inherently prone to the subjective influence of the *** programming(GP),characterized by its tree-based solution structure,is a widely adopted technique for optimizing the structure of mathematical models tailored to real-world *** paper introduces a GP-based framework(GPEAs)for the autonomous generation of update formulas,aiming to reduce human *** modifications to tree-based GP have been instigated,encompassing adjustments to its initialization process and fundamental update operations such as crossover and mutation within the *** designing suitable function sets and terminal sets tailored to the selected evolutionary algorithm,and ultimately derive an improved update *** Cat Swarm Optimization Algorithm(CSO)is chosen as a case study,and the GP-EAs is employed to regenerate the speed update formulas of the *** validate the feasibility of the GP-EAs,the comprehensive performance of the enhanced algorithm(GP-CSO)was evaluated on the CEC2017 benchmark ***,GP-CSO is applied to deduce suitable embedding factors,thereby improving the robustness of the digital watermarking *** experimental results indicate that the update formulas generated through training with GP-EAs possess excellent performance scalability and practical application proficiency.

关键词： Cat swarm algorithm genetic programming digital watermarking update mode mode generation framework

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Comparative Study and Analysis of Health Care System for Heart Patients: Formal Review 1

Comparative Study and Analysis of Health Care System for Hea...

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1st International Conference on AIML-Applications for engineering and technology, ICAET 2025

作者： Agrawal, Chanchal G. Uke, Nilesh J. Vishwakarma Institute of Information Technology Computer Engineering Pune India Indira College of Engineering and Management Computer Engineering Pune India

ISBN: (纸本)9798350355611

Nationwide in today's day to life the fundamental root causes of deaths and hospitalization is heart diseases which will put enormous economic burden on health care system and on the Human life. Prediction at early stage for this type of crucial diseases is one of the best results in morbidity which can be achieve by Clinical Data Analysis. The assessment of cardiovascular events relies on numerous risk factors. Central to effective cardiovascular disease prevention is risk evaluation. In medical systems, data mining and machine learning techniques play a crucial role in developing models to predict heart or cardiovascular disease. These techniques assist researchers in estimating the likelihood of heart disease in vulnerable patients and comparing various ML models. Researchers and practitioners have proposed multiple solutions at both data and algorithm levels over time. This study employs a formal literature review (FLR) approach to provide a comprehensive overview of existing literature and uncover challenges related to imbalanced data in heart disease predictions. Prior to writing, an extensive analysis was conducted using 100 reference papers from reputable journals published between 2017 and 2023. A thorough examination of 52 referenced papers was performed, considering factors such as heart disease type, algorithms, applications, and solutions across various scientific databases, including the Ryerson University Library and Archives (RULA) online system. The primary search databases accessed through RULA were PubMed Central, Springer, Elsevier, Multidisciplinary Digital Publishing Institute (MDPI), IEEE Xplore, Web of Science, Hindawi, and Frontiers. The FLR study revealed that current approaches face several unresolved issues when handling heart disease datasets. © 2025 IEEE.

关键词： Cardiology

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A secured internet of robotic things (IoRT) for long-term care services in a smart building

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Journal of Supercomputing 2023年第5期79卷 5276-5290页

作者： Chang, Shih-Hao Hsia, Chih-Hsien Hong, Wei-Zhi Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan Department of Computer Science and Information Engineering National Ilan University Yilan Taiwan Department of Business Administration Chaoyang University of Technology Taichung Taiwan Department of Computer Science and Information Engineering Tamkang University New Taipei Taiwan

Long-term care refers to any support, both medical and non-medical, provided to the elderly with a chronic illness or disability due to physical or mental conditions. Since the cost of long-term care insurance is not inexpensive, low-cost devices and sensors can be used to create medical assistance systems to reduce human maintenance costs. The requirement of security and privacy under healthcare information protection is a critical issue for internet of medical things (IoMT) data transmission. In this paper, we designed an IoMT security robot for a long-term care system. The goal of this IoMT security robot is to provide secure transmission of the residents’ private information. It is composed of three layers, namely, collection, encryption, and transmission. The function of the IoMT security robot is to first collect data from the patient or the elderly, then provide efficient data encryption, and deliver secured data transmission mechanisms to send the valuable data to the cloud. This IoMT security robot also has a server authentication mechanism, and a support IoT and IoMT devices inspection function. Our evaluation results showed that even when we utilized a low power consumption device like Raspberry Pi, AES algorithm achieved an encrypt and decrypt of 100–100 K bytes under 9 ms, which is a lot better than ECC, which takes about 104 ms. Further, we found that the AES only takes 0.00015 s to decrypt 100 Bytes data, which is way faster than the ECC algorithm, which takes 0.09 s. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Cryptography

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