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Security of Images Using Pascal's Triangle Chaotic Encryption Scheme and with Biometric Authentication in Cloud Storage 4

Security of Images Using Pascal's Triangle Chaotic Encryptio...

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4th International Conference on Advances in Electrical, computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Gupta, Raghav Gullapalli, Manasa Suseela, G. School of Computing Science and Engineering Srm Institute of Science and Technology Department of Networking and Communications Tamil Nadu Kattankulathur603203 India School of Computing Science and Engineering Faculty of Engineering and Technology Srm Institute of Science and Technology Department of Networking and Communications Tamil Nadu Kattankulathur603203 India

ISBN: (纸本)9798350343670

A key component of cloud computing is cloud storage, which allows data to be stored on remote servers. The result is a reduction in the amount of storage space required on local devices, allowing data to be accessed from anywhere with an internet connection. Furthermore, cloud storage is more secure than local storage due to the use of encryption and other security measures by professional providers. This is a practical and cost-effective solution to store large images required to be safeguarded from malicious black hat hackers. Images are the most valuable yet vulnerable form of data that can be used to track down user activities and taken advantage by hackers, used to commit identity theft, fraud. Issues concerning the security and privacy of images saved in the cloud have arisen as cloud storage has grown in popularity. The proposed method will focus on the encryption of images using a chaotic encryption scheme based on Pascal's triangle. The user will authenticate their identity before uploading images to cloud storage and likewise confirm their authentication in the process of retrieval of an image. Such a secure system is better than traditional security methods for password settings as it cannot be easily stolen. Additionally, this method is more secure than other methods due to its complex encryption mechanisms, making it impossible to guess or steal the encryption key. In addition to providing extra security for sensitive images, biometric authentication will offer a stronger method of verifying and validating users on the cloud. © 2024 IEEE.

关键词： AWS Rekognition Chaotic systems Cloud Security Confusion Diffusion Facial Authentication Image Encryption Image Shuffling Pascal's Triangle Transform

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High-Efficiency Asymmetrically Designed Three-Phase Virtual 48-pulse Power Supply for Electrolytic Hydrogen

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IEEE Transactions on Power Electronics 2025年第8期40卷 10335-10342页

作者： Tian, Hanlei Cui, Haoran Han, Wei Sathik M, Jagabar Liang, Guozhuang Chen, Maolin Mekhilef, Saad Sustainable Energy and Environment Thrust The Hong Kong University of Science and Technology (GZ) Guangzhou China Electrical Engineering School of Hebei University of Science and Technology Shijiazhuang China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur India College of Electrical Engineering Sichuan University Chengdu China School of Science Computing and Engineering Technologies Swinburne University of Technology Melbourne VIC Australia

To address the low-voltage, high-current requirements in hydrogen production applications, a virtual 48-pulse three-phase rectifier is proposed, and achieves the equivalent performance of four parallel 12-pulse rectifiers (12-PR). The proposed approach builds upon the conventional 12-PR design and incorporates novel Asymmetric Current Injection Units (ACIU). The ACIU is installed on the DC side of the AC-DC converter, generating a specific current at the DC link to modulate and enhance the operating modes of the 12-PR. Consequently, the 12-pulse is extended to 48, resulting in an almost sinusoidal input current with a Total Harmonic Distortion (THD) of 3.2% and an output current with a ripple rate (RR) of 2.3%, thus significantly improving power quality. Furthermore, the asymmetric design of the current injection units eliminates the need for a phase-shifting transformer. The efficacy of the proposed rectifier for electrolytic hydrogen production is validated using a 2.2 kW experimental prototype. © 1986-2012 IEEE.

关键词： Voltage Hydrogen Rectifiers Production Windings Circuits Inductors Transformers Harmonic analysis Electrochemical processes

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Performance Evaluation of 10G-PON FTTH Access Networks 14

Performance Evaluation of 10G-PON FTTH Access Networks

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14th IEEE International Conference on Control System, computing and engineering, ICCSCE 2024

作者： Abbas, Sura Adil Abdulqader, Aya Hasan Jurn, Yaseen Naser College of Engineering University of Information Technology and Communications Mobile Communications and Computing Department Baghdad Iraq

ISBN: (纸本)9798350364507

5G promises faster speeds and ubiquitous coverage, which requires a robust transport network. A Fiber to the Home (FTTH) access network based on 10 Gbps passive optical network (10G-PON) technology can be an attractive and cost-effective way to support this transport. The design of a cheap and tunable transmitter in the central office (CO) is essential for 10G-PON FTTH. This manuscript has been prepared with the aforementioned goal in mind. To evaluate the performance of the 10G-PON FTTH, a design simulation model based on the transmitter is executed using OptiSystem simulation. The simulation results show that the best performance is demonstrated when phase shift equals 135°. The demodulated signal with a 10 Gbps downlink data stream is dropped after a 40 km transmission distance. This transmitter is economical and requires no additional components, such as a filter, which makes it an attractive candidate for next-generation G-PON FTTH Access Networks. © 2024 IEEE.

关键词： Fiber to the x

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AudioMorse: A Morse-based Covert Channel That Leverages Audio Streaming Platforms

AudioMorse: A Morse-based Covert Channel That Leverages Audi...

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2024 International Conference on Artificial Intelligence, Metaverse and Cybersecurity, ICAMAC 2024

作者： Brits, Jarryd Abdo, Saleem Masoud, Osama Saadeh, Huda Department of Electrical Engineering & Computing Sciences Rochester Institute of Technology Dubai United Arab Emirates

ISBN: (纸本)9798350353488

In recent years, the significance of secure data transmission has been underscored, particularly within governmental sectors. Consequently, there has been a growing emphasis on the field of covert communication, which prioritizes the security and privacy of data transmission channels [1]. This has spurred advancements and research in the domain, leading to the development of many techniques. One area of interest pertains to covert channels that leverage social media as a medium for data transfer. In this study, we conducted a comprehensive review of existing literature on covert communications via social media and assessed the strengths and weaknesses of the reviewed papers concerning detection, bandwidth, latency, and ease of implementation. Subsequently, we propose a novel encoding technique, AudioMorse, predicated on Morse code and ASCII code, which utilizes the duration of a designated song track to generate concealed messages. © 2024 IEEE.

关键词： Audio streaming

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Comparing Deep Learning Object detection Methods for Real Time Cow Detection 38

Comparing Deep Learning Object detection Methods for Real Ti...

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38th IEEE Region 10 Conference, TENCON 2023

作者： Martha, Gichuki Wambui Waweru Mwangi, Ronald Aramvith, Supavadee Rimiru, Richard Jomo Kenyatta University of Agriculture & Technology Computing Department School of Computing & Information Technology Nairobi Kenya Chulalongkorn University Department of Electrical Engineering Faculty of Engineering Bangkok Thailand

ISBN: (纸本)9798350302196

Deep learning algorithms particularly Convolutional Neural Networks (CNNs) are the state-of-the-art techniques for object detection, classification, segmentation and behaviour classification. These algorithms have extensive application across various domains including agriculture. However, cow identification in dairy farming still relies on methods like direct visual monitoring which are time consuming, costly and inaccurate;or use of invasive contact devices such as sensors which can cause discomfort during attachment or removal. This research compared three deep learning object detection models i.e. YOLOv5, YOLOv7 and YOLOv8, which were selected based on their performance in object detection tasks. We generated cow images from videos captured from a housed dairy cattle barn. The dataset had 11,828 cow images, augmented to depict different illumination conditions and using makesense AI tool, we annotated the images in YOLO format, trained and validated the three models to visualize cow bounding boxes. Our approach demonstrates efficiency of the YOLOv8 model, achieving an accuracy of 94.7% and 93 % before and after data augmentation respectively. YOLOv8 baseline model was finetuned using the Ray Tune library achieving a mAP@O.50 score of 92. 9%. This research makes a significant contribution in the future research direction of the YOLO algorithm and highlights the practical implementation of deep learning models for cow detection, applicable in livestock management. © 2023 IEEE.

关键词： Object detection

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Classification of Privacy Preserved Medical Data with Fractional Tuna Sailfish Optimization Based Deep Residual Network in Cloud

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Annals of Data Science 2024年 1-26页

作者： Shikalgar, Shabanam K. Kumar, N. V. S. Pavan Singh, Gavendra Rashid, Faizur Sharad Institute of Technology College of Engineering Yadrav India Koneru Lakshmiah Education Foundation Vijayawada India Department of Software Engineering College of Computing and Informatics Haramaya University Dire Dawa138 Ethiopia College of Computing and Informatics Haramaya University Dire Dawa138 Ethiopia

Nowadays, with the growth of emerging technologies, increased attention has been paid to the classification of privacy-preserved medical data and development of various privacy-preserving models for the promotion of online medical pre-diagnosis systems. Medical data is highly sensitive and it is essential to ensure privacy of medical records from third-party users to increase service quality, satisfy patients and earn trust. The classification of medical preserved data is helpful to build a clinical decision system by classifying patients based on their disease and symptoms. In this article, a hybrid optimization-based deep learning model named Fractional Tuna Sailfish Optimization–Deep Residual Network (FractionalTSFO-DRN) is designed to precisely classify the privacy preserved medical data. A privacy utility coefficient matrix is used to ensure the privacy of medical data by generating a key matrix using Tuna Sailfish Optimization (TSFO) algorithmic technique. The privacy-preserved medical data is allowed for the classification process using DRN and the introduced Fractional TSFO is used to optimize and enhance the classification in DRN. The assessment followed by using heart disease prediction databases proved that the employed classification technique recorded an accuracy of 94.67%, a True Positive Rate of 93.56%, and a True Negative Rate of 89.68% respectively. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Classification (of information)

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Quantum Secure Email Communication for Phishing Prevention 7

Quantum Secure Email Communication for Phishing Prevention

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7th IEEE Pune Section International Conference, PuneCon 2024

作者： Chandre, Pankaj Sontakke, Palash Patil, Rajkumar Shendkar, Bhagyashree D Dhotre, Dhanraj Vanarote, Viresh Mit Art Design and Technology University Mit School of Computing Department of Computer Science and Engineering Pune India Mit Art Design and Technology University Mit School of Computing Department of Information Technology Pune India

ISBN: (纸本)9798331527822

The rise of sophisticated phishing attacks has necessitated stronger security measures for email communication, especially in sensitive environments. This paper proposes a Quantum Secure Email Communication Framework designed to prevent phishing by integrating Quantum Key Distribution (QKD) with traditional email security mechanisms. The framework leverages quantum keys to encrypt email communication, ensuring that only legitimate users with the correct quantum key can send and receive secure emails. The architecture also incorporates a Phishing Detection Engine that validates email content and sender information using quantum-encrypted keys, alerting users to potential phishing threats. The system operates through the secure exchange of quantum keys between the sender's email server and the user via a QKD Channel, with quantum encryption applied to secure outgoing and incoming emails. In parallel, the phishing detection module analyses all email traffic for signs of malicious activity, using a QKD-based Email Validator to confirm the legitimacy of emails. This hybrid approach ensures both the privacy of communication and the proactive detection of phishing attempts, offering a robust defense mechanism in the increasingly hostile landscape of digital communication. © 2024 IEEE.

关键词： Phishing

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Optimizing Building Energy Consumption using Smart Grid Data 5

Optimizing Building Energy Consumption using Smart Grid Data

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5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Neelakandan, Viduran Voleti, Sai Suraj Srinivasan, Dhanush Gouthaman, P. SRM Institute of Science and Technology School of Computing College of Engineering and Technology Department of Networking and Communications Kattankulathur603203 India

ISBN: (纸本)9798331530013

This research discusses how data analytics techniques can be applied in the enhancement of building energy management. It is therefore with the purpose of stimulating the right utilization of the practically inexhaustible quantity of data obtained through smart grids that this research seeks to design original approaches to energy management, building performance, and counteracting of negative impacts on the environment. Since Apache spark process is very efficient we do an excellent job in pre-processing and analyzing the data collected. Combining high-level artificial intelligence decision making tools like linear regression as well as the random forest, the relationship was established between energy utilization and determinants, forecast patterns and create accurate prognosis models. In order to present the results in a format that can be easily understood with the help of Tableau to build a data visualization where depending on the values chosen by the stakeholders further steps can be taken in achieving a more efficient use of energy and less expenditure. In our work, we strive to generate knowledge that will support improved energy efficiency of the built environment, and therefore a more sustainable future. The implications of our work have the ability to affect the processes within and energy usage of buildings, saving energies and making cities greener. Furthermore, our work can help with the creation of further reference points for future research in the field of building energy optimization. © 2024 IEEE.

关键词： Big Data Building Efficiency Energy Optimization Machine Learning Predictive Analytics Smart Grids Sustainability

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Sustainable Development Goal-17 and Nigeria Data Protection Regulation Adoption among Organizations in Nigeria

Sustainable Development Goal-17 and Nigeria Data Protection ...

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2024 International Conference on Science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Babangida-Sabo, Sumayya Avemaria Utulu, Samuel C. Ajibesin, Abel American University of Nigeria Department of Informaton Systems School of Informtaon Technology and Computing Yola Nigeria Amerucan University of Nigeria Department of Software Engineering School of Information Technology and Computing Yola Nigeria

ISBN: (纸本)9798350358155

Adoption of computerized systems by organizations in Nigeria poses some data security challenges to citizens and people from other nations. The challenges require organizations to deploy personal data security that are in line with global standards, hence, Nigeria Data Protection Regulation (NDPR) was introduced. NDPR is to promote ethical personal data security and Nigeria's attainment of the sustainable development goal-17. However, only small number of organizations in Nigeria are able to adopt the NDPR because its adoption is complex and necessitate the implementation of organizational change management (OCM) project. Experience shows that OCM projects usually fails because many OCM frameworks used for OCM projects do not align with both scientifically proven ideas and organizational realities. Our study addresses the benefits of collaborative practice research studies to the production of OCM frameworks that incorporates both theoretical ideas and organizational realities. Our study provides viable solutions to the problem of lack of practice oriented OCM frameworks that organizations in Nigeria can use to drive the adoption the NDPR. © 2024 IEEE.

关键词： Sustainable development goals

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A Near Optimal Patient Scheduling for effective Doctor Appointment System

A Near Optimal Patient Scheduling for effective Doctor Appoi...

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2024 IEEE International Conference on Electronic Systems and Intelligent computing, ICESIC 2024

作者： Gupta, Swayam Veshala, Asish Kowsigan, M. Ramamoorthy, S. Madhavan, P. SRM Institute of Science and Technology College of Engineering and Technology Department of Computing Technologies Kattankulathur Tamilnadu Chengalpattu603203 India

ISBN: (纸本)9798331522988

The research work introduces the concept of a Doctor Appointment Website, a digital platform designed to optimize the process of scheduling and managing medical appointments. The platform allows patients to search for doctors based on specialty, location, and availability, and book appointments in real-time. In addition to appointment scheduling, the website enables users to access their medical history, prescriptions, and reports, offering a centralized system for managing healthcare needs. The platform also incorporates advanced features like automated notifications via email and SMS, dynamic scheduling, and real-time updates, reducing the likelihood of missed appointments and improving overall efficiency. With support for telemedicine, patients can have remote consultations, receive e-prescriptions, and engage in follow-up *** system addresses common healthcare challenges by reducing administrative burdens on medical staff, enhancing patient satisfaction, and streamlining communication between patients and doctors. The paper explores the key benefits of such a system, including improved patient engagement and better resource management. It also delves into potential implementation challenges, such as ensuring data security, achieving compliance with healthcare regulations, and integrating with existing medical infrastructure. Finally, the paper discusses areas for further improvement, focusing on enhancing user experience, scalability, and the integration of advanced analytics for better healthcare outcomes. © 2024 IEEE.

关键词： Electronic health record

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