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Informatica (Slovenia) 2025年第11期49卷 165-176页

作者： Ilias, Shaik Mohammad Sharmila, V. Ceronmani Durga, V. Sathya Dept. of Computer Science and Engineering Hindustan Institute of Technology and Science Chennai India Department of Information Technology Hindustan Institute of Technology and Science Chennai India Department of Computer Science&Engineering Hindustan Institute of Technology and Science Chennai India

If adversaries were to obtain quantum computers in the future, their massive computing power would likely break existing security schemes. Since security is a continuous process, more substantial security schemes must be developed. Current PQC schemes primarily focus on data security or key exchange, and further improvement towards enhanced PQC primitives is required. Our proposal in this research is an innovative paradigm for PQC-focused cloud data security. The proposed HEDT approach achieves encryption and decryption with significantly lower latency (20% improvement) and higher reliability than AES, DES, and RSA, as demonstrated through experimental results. Furthermore, ECSIDH, a hybrid key exchange mechanism combining SIDH and ECDH, improves security strength by 50% while maintaining computational costs within 1.13x of SIDH. Compared to individual key exchange schemes like SIDH, ECSIDH offers superior security as a PQC candidate. These results confirm the robustness and efficiency of the proposed framework in ensuring secure data outsourcing and key exchange in cloud environments. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Quantum computers

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Design and Experiment of a Four-Fingered Robotic Hand for T-FLoW 4.0 humanoid robot 25

Design and Experiment of a Four-Fingered Robotic Hand for T-...

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25th International Electronics Symposium, IES 2023

作者： Apriandy, Kevin Ilham Dewantara, Bima Sena Bayu Dewanto, Raden Sanggar Pramadihanto, Dadet Ryando, Catoer Dept. of Informatics and Computer Engineering Indonesia Dept. of Electrical Engineering Indonesia

ISBN: (纸本)9798350314731

In this research study, we present a novel design of a four-fingered robotic hand for T-FLoW 4.0 humanoid robot along with its experiments to validate its grasping performance. Our proposed robotic hand designed with four fingers and five Degree-of-Freedom (DoF), with a configuration of a thumb, index, middle, and ring fingers to remain within the criteria of an anthropomorphic type robot hand. Our hand is built with a modular design on each finger and its mechanism, allowing for easy assembly and achieving a compact hand result. Main controller Arduino Mega implement the system for grasping movement, and then PCA9685 PWM controller get the hand movement instructions from it and generates the required PWM signal for the servo motors. The process of manufacturing the hand involves 3D printing technology to produce hands with a realistic appearance, and use PLA filament material achieve lightweight, affordable, and easy-To-maintain outcomes. The grasping experimental results show that our proposed robotic hand could perform basic grasping movements on household objects. With the use of Cini's taxonomy of grasp as the hand functionality standard, we achieved a success rate of 8 out of 14 tests conducted. © 2023 IEEE.

关键词： Anthropomorphic robots

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Challenges of Integrating Blockchain technology into Educational Institutions

Challenges of Integrating Blockchain Technology into Educati...

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2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Ali, Abbas Hussein Yavanoǧlu, Uraz Graduate School of Informatics Gazi University Dept. Of Computer Science Ankara Turkey Gazi University Faculty of Engineering Dept. of Computer Engineering Ankara Turkey

ISBN: (纸本)9798350364910

The latest advancements in blockchain technology have significantly influenced several sectors, such as banking, healthcare, and supply chain networks. Because of its distinct attributes, like decentralization, trustworthiness, and security, this technology has recently been employed in the field of education. While the blockchain is bright, several problems, such as legal, immutability, and scalability questions, continue to hinder its adoption in education. In this paper, we look at educational application system in terms of blockchain-based solutions that have been created for educational purposes, as well as the potential challenges of blockchain technology in the field of education. © 2024 IEEE.

关键词： Blockchain technology educational application

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Effective Machine Learning Model for Disease Recognition and Categorization of Mango Leaves

Effective Machine Learning Model for Disease Recognition and...

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2024 International Conference on Computational Intelligence and Computing Applications, ICCICA 2024

作者： Kumar, Sandeep Gupta, Bhupesh Grover, Richa Chhabra, Mohit Computer Science & Engineering Dept. Ambala Mullana India Panipat Institute Of Engineering & Technology Computer Science & Engineering Dept. India

ISBN: (纸本)9798350306446

Maintaining the health and production of mango farms depends on the early detection of illnesses in mango trees. Despite the vital role agriculture plays, it remains an industry receiving limited attention from the machine-learning community. A noteworthy challenge is the lack of standardized and openly accessible agricultural datasets, impeding researchers from fully leveraging the potential of advanced computational prediction tools. The study focuses on employing deep learning and image processing techniques for diagnosing prevalent mango leaf diseases in India. The goal is to enhance both the quality and quantity of agricultural production by implementing effective disease control measures upon identifying plant diseases. The automation of plant disease detection proves particularly beneficial, reducing the monitoring efforts required by large farms. Rapid identification of leaf diseases is crucial, given that leaves serve as a plant's primary source of nutrition. Notably, none of the seven different mango leaf illnesses that have been observed in India have ever been the subject of earlier research. In this study, we provide a lightweight Resnet50 model that can reliably classify healthy mango leaves and the seven discovered illnesses on mango leaves. The performance of our proposed lightweight Resnet-50 model is evaluated against many pre-trained models, such as Exception, Resnet101, and VGG16. The findings reveal that the lightweight Resnet-50 model achieves the highest testing accuracy, reaching an impressive 95%. This underscores the model's effectiveness in automating the identification of mango leaf diseases, offering a promising solution for improving agricultural practices in India. © 2024 IEEE.

关键词： Diseases

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Leveraging Artificial Intelligence for Active Cyber Defense Against to Advanced Persistent Threats to Homeland Security

Leveraging Artificial Intelligence for Active Cyber Defense ...

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2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Özbay, Recep Yavanoǧlu, Uraz Graduate School of Informatics Gazi University Dept. Of Computer Forensics Ankara Turkey Gazi University Faculty of Engineering Dept. of Computer Engineering Ankara Turkey

ISBN: (纸本)9798350364910

Increasing cyber threats have rendered traditional security solutions such as firewalls and intrusion-detection/prevention systems insufficient in providing adequate protection against advanced persistent threats to homeland security. To enhance protection, the implementation of active cyber defense is recommended, offering alternative yet effective measures against these threats. This paper examines the phases of the cyber kill chain, one of the cyber defense techniques, which has been enhanced to analyze and understand advanced persistent threats. It explains the use of deception, slowdown, and counterattacks for active cyber defense. Additionally, the utilization of artificial intelligence in active cyber defense techniques is discussed. Finally, the paper elucidates how these techniques can be employed within the scope of active cyber defense to enhance security. © 2024 IEEE.

关键词： Network intrusion

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Secured Entry Control: An IoT and Deep Learning based Mask Detection System for COVID-19 Suspected Patient Screening and Access Regulation 3

Secured Entry Control: An IoT and Deep Learning based Mask D...

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3rd International Conference on Advancement in Electrical and Electronic engineering, ICAEEE 2024

作者： Sultana, Abida Peyal, Hasibul Islam Islam, Md. Injamul Abdal, Md. Nazmul Miraz, Shafiun Kontho, Md. Mahin Rahaman Leion, Zannatul Mawa Mamun, Abdul Al Rajshahi University of Engineering & Technology Dept. of Electrical & Computer Engineering Rajshahi Bangladesh Uttara University Dept. of Computer Science & Engineering Dhaka Bangladesh University of Liberal Arts Bangladesh Dept. of Computer Science and Engineering Dhaka Bangladesh Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi Bangladesh Tejgaon College Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350388282

The new coronavirus SARS-CoV-2, which triggered the COVID-19 pandemic, has had an unparalleled effect on economies, cultures, and world health. In response to the critical need for strict COVID-19 screening systems in public areas, this study presents a creative Secured Entry Control system. Detecting and controlling possible COVID-19 carriers attempting to enter the country is made possible by this system, which makes use of deep learning algorithms and IoT technology. The mask detection algorithm, MobileNetV2 model, has an exceptional validation accuracy of 98.96\%. The model's reliability is supported by performance evaluations using ROC curves, confusion matrix analysis, and an AUC value of 98.96\%, which is close to the optimal AUC score of 100\%. Because MobileNetV2 is well-suited for low-processing devices, it is easy to deploy it on Raspberry Pi, which helps to create an affordable system. Furthermore, by spotting increased body temperatures, a contactless temperature sensor improves the system's ability to identify possible COVID-19 carriers. The functioning of the system is confirmed by the working prototype that is presented in the Experimental Results section. The main goal of this research is to create an autonomous system that is affordable and selectively allows access to people who are less likely to transmit COVID-19 in public areas. To achieve the overall objective of reducing the spread of COVID-19 in public spaces, this research highlights the successful integration of mask identification algorithms and IoT. © 2024 IEEE.

关键词： COVID-19

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An Overview on IoT in Electric Vehicles: Efficiency and Sustainability 2

An Overview on IoT in Electric Vehicles: Efficiency and Sust...

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2nd IEEE International Conference on IoT, Communication and Automation technology, ICICAT 2024

作者： Gupta, Shashank Sounkhla, Indu Dubey, Ranjeet Kumar Yadav, Mithilesh Kumar Singh Yadav, Sandeep NIT Dept. of Computer Science and Engineering Jalandhar India KIPM Dept. of Computer Science and Engineering Gorakhpur India Buddha Institute of Technology Dept. of Computer Science and Engineering Gorakhpur India

ISBN: (纸本)9798350368109

Internal combustion engine (ICE) vehicles are very polluting and release high nitrogen oxides, carcinogens, and soot into the environment. ICE vehicles are the best choice in this era, but replacing ICE vehicles with electric vehicles (EVs) and automated vehicle control is a potential transition process. The most important turning point in the history of the automobile occurred with the entry of EVs into the vehicle market. The rise of the Internet of Things (IoT) paradigm in electric vehicles (EVs) has changed the way we look at large-scale transportation by making it intelligent and more sustainable. Recently, with the advent of connectivity through IoT platforms, IoT in EVs has improved performance and reduced environmental impact: from any on-off switch and adoption of IoT through our smartphones placed on the charging base. We can implement smart charging solutions for better energy consumption management, reduction of grid load, and battery life enhancement. IoT allows electric vehicles to communicate directly with charging stations and even the power grid, providing a better way to create balanced transportation networks. But implementing IoT in electric vehicles also raises some issues, including data security and user privacy. With all of these issues, there is huge potential in IoT usage with electric vehicles to help produce cleaner transportation and create a more sustainable future. © 2024 IEEE.

关键词： Electric Vehicles Internal Combustion engine Internet of Things

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Moth flame optimization algorithm for efficient feature selection and hybrid classification technique for intrusion detection system

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Multimedia Tools and Applications 2025年 1-21页

作者： Keerthanarani, U. Selvakumar, V. Singaravelan, S. Raja, S. Edwin Thenmozhi, K. Shunmugam, D. Arun Dept. of Computer Science and Engineering P.S.R Engineering College Sivakasi India Dept.Of Computer Science and Engineering Vel Tech Rangarajan Dr Sagunthala R & d Institute of Science and Technology Chennai Avadi India Dept. Of Computer Science and Engineering Coimbatore Institute of Engineering and Technology Coimbatore India Dept. Of Electronics and Communication Engineering P.S.R Engineering College Sivakasi India

The rapid expansion of the Internet of Things (IoT) brings numerous benefits but further presents fresh difficulties, especially in terms of security. The distributed and interconnected nature of IoT devices makes them susceptible to various security threats. An Intrusion Detection System (IDS) plays a crucial role in safeguarding IoT networks by monitoring, detecting, and responding to potential security incidents. The Internet of Things (IoT) connects billions of devices, sensors, and systems, transforming industries and everyday life. However, this extensive interconnectivity also introduces significant security risks, making Intrusion Detection Systems (IDS) a critical component for safeguarding IoT environments. Feature selection is a crucial aspect of building effective Intrusion Detection Systems (IDS). Selecting relevant features not only helps in achieving better classification accuracy but also contributes to reducing false alarm rates. In the proposed system a moth flame optimizer is utilized to select the efficient features from the dataset, overall accuracy of over 97%. Further it is classified employing Random Forest and J48 classifier which attains high classification accuracy and low false alarm rate. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Feature Selection

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An Intelligent Controller for Demand-Side Management in Residential Electrical Networks

An Intelligent Controller for Demand-Side Management in Resi...

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2024 Panhellenic Conference on Electronics and Telecommunications, PACET 2024

作者： Zigirkas, Gregory Kalomiros, John International Hellenic University Dept. of Computer Informatics and Telecommunications Engineering Serres Greece

ISBN: (纸本)9798350318845

A novel embedded controller is proposed for the management of electrical consumption in residential installations. The proposed system is designed to implement well-established DSM techniques. It can be placed directly into the electrical board of a residential circuit and can be connected to the smart grid. The controller is based on a PIC microcontroller and incorporates a series of perceptrons which adjust the duty cycle of PWM modules according to user defined preferences. The system is tested in laboratory conditions and is proved to be able to adjust the total current to a predefined threshold, without violating user comfort and priorities. The proposed embedded controller is a flexible solution in the form of a final product, ready for the smart grid and able to support microgrids. © 2024 IEEE.

关键词： Microcontrollers

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J-NECORA: A Framework for Optimal Resource Allocation in Cloud-Edge-Things Continuum for Industrial Applications With Mobile Nodes

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IEEE Internet of Things Journal 2025年第11期12卷 16525-16542页

作者： Pettorali, Marco Righetti, Francesca Vallati, Carlo Das, Sajal K. Anastasi, Giuseppe Univ. of Pisa Dept. of Information Engineering Italy Missouri Univ. of Science and Technology Dept. of Computer Science RollaMO United States

In the Industrial Internet of Things (IIoT) landscape, where the Cloud-to-Things Continuum (C2TC) paradigm is now a reality, industrial applications need to cope with highly heterogeneous network and computing resources. Moreover, many industrial applications also involve Mobile Nodes (MNs). Efficient allocation of network and computing resources to meet the stringent requirements of such applications is often a very challenging task. In this paper, we propose J-NECORA (Joint NEtwork and COmputing Resource Allocation), a comprehensive analytical framework to derive the optimal joint allocation of network and computing resources in the C2TC, that guarantees the application requirements, even in the presence of MNs. If the optimal allocation does not exist, J-NECORA provides a best-effort allocation that minimizes the delay. The proposed framework is highly modular and flexible, and can be easily customized to different scenarios. We validated its effectiveness through simulation experiments, focusing on a specific use case. For the considered scenarios, the performance predicted by our framework matches quite closely the simulation results. © 2014 IEEE.

关键词： Cloud platforms

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