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2nd International Conference on cyber Physical Systems, Power Electronics and Electric Vehicles, ICPEEV 2024

作者： Busari, Wareez A. Bello, Abeeb A. Department of Cyber Security Science Federal University of Technology Niger State Minna Nigeria Department of Electrical and Computer Engineering Mahindra University Hyderabad India

ISBN: (纸本)9798350388664

This paper explores the convergence of physical and computational components in cyber-Physical Systems (CPS). security, trust, and privacy are paramount for reliable and resilient operation of these interconnected systems across diverse sectors like healthcare and smart cities. The paper analyses the complex interplay of these factors, identifying practical challenges and proposing solutions to enhance system robustness. By analysing trends, research gaps, and offering actionable recommendations, the study aims to empower stakeholders in fortifying CPS against evolving cyber threats. It emphasizes the need for comprehensive strategies to mitigate risks, protect sensitive information, and ensure data integrity and system reliability. Through a holistic approach integrating security, trust, and privacy mechanisms, the research contributes to advancing effective security measures in CPS, ultimately fostering a culture of trust and resilience in the digital era. © 2024 IEEE.

关键词： Differential privacy

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Ensemble of deep learning models with Walrus Optimization Algorithm for accurate botnet recognition and classification

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Iran Journal of computer Science 2025年 1-18页

作者： Chacko, Ashwathy Anda Edwin, E. Bijolin Thanka, M. Roshni Ebenezer, V. Division of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Division of Data Science and Cyber Security Karunya Institute of Technology and Sciences Coimbatore India

The rapid growth of Internet of Things (IoT) networks has introduced significant security challenges, with botnet attacks being one of the most prevalent threats. These attacks exploit vulnerabilities in IoT devices, leading to severe disruptions and damage to critical infrastructures. Detecting botnet attacks in IoT environments is challenging due to the large volume of data, the dynamic nature of traffic, and the diverse attack patterns. To address these issues, we propose a novel approach called Walrus Optimized Ensemble Deep Learning for Anomaly-Based Recognition Classifier (WOAEDL-ABRC), which leverages a combination of advanced machine learning techniques for effective botnet detection. The methodology of this research involves four key components: (1) data preprocessing through min–max normalization to scale the features appropriately, (2) feature selection using the social cooperation search algorithm (SCSA) to identify the most informative attributes, (3) an ensemble deep learning model combining convolutional autoencoder (CAE), bidirectional gated recurrent unit (BiGRU), and deep belief network (DBN) for robust anomaly detection, and (4) hyperparameter optimization using the Walrus Optimization Algorithm (WAOA), which fine-tunes the model parameters for optimal performance. This ensemble approach ensures that the model benefits from the strengths of each individual technique while mitigating the weaknesses of others. The dataset used for this research includes network traffic data from IoT environments, consisting of various botnet attack scenarios and normal traffic patterns. The data undergoes extensive preprocessing and feature selection to reduce dimensionality and enhance the model’s performance. The implementation is carried out in Python using TensorFlow for deep learning, with the WAOA applied to optimize hyperparameters. The results demonstrate the effectiveness of the WOAEDL-ABRC in detecting botnet attacks, achieving superior accuracy, precision

关键词： Botnet recognition Deep learning Feature selection Internet of things Walrus Optimization Algorithm

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Smart Water-Powered Renewable Energy System with IoT Integration

Smart Water-Powered Renewable Energy System with IoT Integra...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Najim, Ali Hamza Ibraheem, Ahmed Salman Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisha Hassan Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq Department of Computer Technical Engineering Baghdad Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

An advanced hybrid renewable energy collecting and storage system prototype that utilizes water flow as its primary power source. Additionally, the system incorporates an energy monitoring system based on the Internet of Things (IoT) technology. The device effectively harnesses energy from the movement of water, storing it for future use in low-voltage applications. It demonstrates a maximum daily energy capture capacity of about 100Wh. The energy monitoring system, based on the Internet of Things (IoT), enables the real-time and remote monitoring of energy harvesting and usage. We thoroughly assessed the energy harvesting component across different situations to identify the crucial parameters that impact energy output. The results of our study demonstrate that several elements, including the spatial separation 'between the energy harvester and the water source, Water flow' speed, sensor orientation, and sensor density, all play significant roles in determining the quantity of energy collected. This research shows that it is possible to integrate IoT technology with hydropower renewable energy systems. It provides significant perspectives on enhancing energy extraction efficiency in practical scenarios. © 2024 IEEE.

关键词： harvesting renewable energy IoT storage energy water flow energy

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Strategies for Building and Maintaining Secure Web Applications 5

Strategies for Building and Maintaining Secure Web Applicati...

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5th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2024

作者： Sathiyapriyan, C. Manikandan, B. Gokul, S. Satheesh, Rewin Nivetha, S. Leelavathy, S. Aarupadai Veedu Institute of Technology Cyber Security Department of Computer Science and Engineering Chennai603104 India Aarupadai Veedu Institute of Technology Department of Computer Science and Engineering Chennai603104 India Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai600119 India

ISBN: (纸本)9798350395235

Ensuring the security of web applications is paramount in safeguarding sensitive data and maintaining user trust. This study presents a comprehensive overview of strategies for building and maintaining secure web applications, acknowledging their inherent limitations and outlining potential areas for future work. The strategies discussed encompass fundamental aspects of web application security, including input validation and sanitization, robust authentication and authorization mechanisms, secure communication through HTTPS, timely security patching, implementation of security headers, monitoring and logging, client-side security measures, and vigilance in handling third-party components.. This research employed algorithms include Routing Algorithms, Middleware Execution Order Algorithms, Eloquent ORM Algorithms, Encryption and Hashing Algorithms, Session Handling Algorithms, Queue Management Algorithms, and Dependency Injection Algorithms. © 2024 IEEE.

关键词： Sensitive data

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Randomization Strategies in Image Steganography Techniques:A Review

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computers, Materials & Continua 2024年第8期80卷 3139-3171页

作者： AFM Zainul Abadin Rossilawati Sulaiman Mohammad Kamrul Hasan Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan Malaysia(UKM)BangiSelangor43600Malaysia Department of Information and Communication Engineering Pabna University of Science and TechnologyPabna6600Bangladesh

Image steganography is one of the prominent technologies in data hiding *** system performance mostly depends on the embedding *** goal is to embed strictly confidential information into images without causing perceptible changes in the original *** randomization strategies in data embedding techniques may utilize random domains,pixels,or region-of-interest for concealing secrets into a cover image,preventing information from being discovered by an *** implementation of an appropriate embedding technique can achieve a fair balance between embedding capability and stego image imperceptibility,but it is challenging.A systematic approach is used with a standard methodology to carry out this *** review concentrates on the critical examination of several embedding strategies,incorporating experimental results with state-of-the-art methods emphasizing the robustness,security,payload capacity,and visual quality metrics of the stego *** fundamental ideas of steganography are presented in this work,along with a unique viewpoint that sets it apart from previous works by highlighting research gaps,important problems,and ***,it offers a discussion of suggested directions for future study to advance and investigate uncharted territory in image steganography.

关键词： Information hiding image steganography randomized embedding techniques payload capacity imperceptibility

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Improving VANET Localization Performance with Data Verification: Challenges and Solutions

Improving VANET Localization Performance with Data Verificat...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Kadhim, Aqeel Kamil Najim, Ali Hamza Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisa Hassan Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

In VANETs, the important and effective applications of vehicle localization include safety and communication applications. Thus, it is difficult to get very accurate localization in the dynamic and often very fluctuating environment of VANET. This research responds to this challenge with a keen thrust on improving vehicle localization using the Mobility Data Verification process. The primary goal of this work is to achieve high accuracy of vehicle positioning within VANET by checking the coherence of mobility data of moving vehicles. Hence, we present a concept that builds upon Mobility Data Verification to provide real-time location details from vehicles. Both GPS and onboard sensors feed this method, which uses a multi-level verification to flag out or eliminate the errors of deliberately spoofed data points. We use simulations to evaluate and validate the effectiveness of the proposed verification approach. As the proposed system, our previously developed and fine-tuned weighted localization (OWL) strategy does so. The performance evaluation results suggest that our proposed solution is feasible to distinguish automobiles that are not trustworthy and improve the performance of the localization algorithm. © 2024 IEEE.

关键词： Vane pumps

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Real-time Autonomous Vehicle Maneuver Generation Algorithm Based on Hierarchical Planning 24

Real-time Autonomous Vehicle Maneuver Generation Algorithm B...

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2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence, DEAI 2024

作者： Zhai, WenHao School of Computer Science and Engineering School of Cyber Security University of Electronic Science and Technology of China Sichua Chengdu China

ISBN: (纸本)9798400717147

Global path planning, whether based on sampling-based algorithms or heuristic search algorithms, can search for a global path from the start point to the destination in a relatively short time. However, they often struggle to avoid local obstacles and have limited adaptability to local dynamic environments, making it difficult to meet the requirements of obstacle avoidance in unknown environments. On the other hand, the local path planning DWA algorithm can perform online real-time planning and has excellent obstacle avoidance capabilities. However, in large-scale and complex environments, it may fail to obtain the optimal path or even reach the target point if there is a lack of intermediate waypoint guidance. Therefore, to leverage the strengths of both approaches, an instruction generation algorithm based on a hierarchical plan approach is introduced. This algorithm utilizes the global path points as relay points for the DWA algorithm, enabling real-time obstacle avoidance tasks. Finally, the superiority of the fusion algorithm is verified through comparative simulation experiments. © 2024 ACM.

关键词： Motion planning

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IoMT-Based Healthcare Framework for Ambient Assisted Living Using a Convolutional Neural Network

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computers, Materials & Continua 2023年第3期74卷 6867-6878页

作者： Waleed T.Al-Sit Nidal A.Al-Dmour Taher M.Ghazal Ghassan F.Issa Department of Computer Engineering Mutah UniversityAl-KarakJordanHigher Colleges of TechnologyDubaiUAE Department of Computer Engineering College of EngineeringMutah UniversityJordan School of Information Technology Skyline University CollegeUniversity City SharjahSharjahUAE Center for Cyber Security Faculty of Information Science and TechnologyUKM43600BangiSelangorMalaysia

In the age of universal computing,human life is becoming smarter owing to the recent developments in the Internet of Medical Things(IoMT),wearable sensors,and telecommunication innovations,which provide more effective and smarter healthcare *** has the potential to shape the future of clinical research in the healthcare *** sensors,patients,healthcare providers,and caregivers can connect through an IoMT network using software,information,and communication *** assisted living(AAL)allows the incorporation of emerging innovations into the routine life events of *** learning(ML)teaches machines to learn from human experiences and to use computer algorithms to“learn”information directly instead of relying on a *** the sample size accessible for learning increases,the performance of the algorithms *** paper proposes a novel IoMT-enabled smart healthcare framework for AAL to monitor the physical actions of patients using a convolutional neural network(CNN)algorithm for fast analysis,improved decision-making,and enhanced treatment *** simulation results showed that the prediction accuracy of the proposed framework is higher than those of previously published approaches.

关键词： Smart healthcare system neural network machine learning

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An Efficient Key Establishment and Distribution Scheme for Wireless Body Area Networks

An Efficient Key Establishment and Distribution Scheme for W...

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

作者： Taofeek, Yusuf Victor, Waziri Onomza Olalere, Morufu Abdullahi, Muhammad Bashir Federal University of Technology Cyber Security Science Department Minna Nigeria Federal University of Technology Computer Science Department Minna Nigeria

ISBN: (纸本)9798350358155

Secure communication in wireless body area network (WBAN) depends on efficient key management system. However, to ensure robustness, key management schemes must not only be lightweight but also support the establishment of communication keys efficiently in this paper, an efficient key management scheme is proposed based on elliptic curve cryptography (ECC) algorithm. The proposed scheme adopts a novel authentication mechanism base on authentication tables We analyzed and compare the resilience and performance of our work with concurrent schemes in terms of computation, storage and communication overheads. The results showed an improvement in our scheme in comparison with related work as displayed in table 4. Therefore, WBAN as an innovative part of the industry 4.0 have revolutionized the health-care industry. The application of the technology has transformed laboratory based medical diagnosis and data collections such as blood pressure, glucose level and blood oxygen through remote monitoring, sensing and transmission to health-care service provider for diagnosing different medical treatments. Thus, the design of such critical system requires secure and efficient technique as proposed in this work. © 2024 IEEE.

关键词： Authentication Protocol

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Edge-based AI solution for enhancing urban safety: helmet compliance monitoring with YOLOv9 on Raspberry Pi

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Discover Internet of Things 2025年第1期5卷 1-14页

作者： Tahilramani, Nikunj Ahir, Param Saxena, Shruti Talreja, Vandana P. Charanarur, Panem Adani Institute of Digital Technology Management Gandhinagar India School of Cyber Security and Digital Forensics National Forensic Sciences University Gandhinagar India Electrical Engineering Department R.C. Technical Institute Ahmedabad India Department of Cyber Security and Digital Forensics National Forensic Sciences University Tripura India

This paper presents an automated helmet detection system leveraging Raspberry Pi and advanced deep learning techniques, specifically the YOLOv9 object detection model that focuses on real-time object detection. The system captures real-time video frames of motorcyclists, processes these frames to detect helmet usage, and interfaces with the vehicle’s ignition control unit to inhibit engine start if a helmet is not detected. This edge computing solution addresses the inefficiencies of manual inspections by providing a scalable, cost-effective, and real-time enforcement mechanism for helmet compliance. The YOLOv9 model, trained on a robust dataset, ensures high detection accuracy and low latency, demonstrating effective performance in real-world scenarios. The YOLOv9 model achieved a precision of 0.894, recall of 0.943, mAP50 of 0.967, and an inference speed of 21.0 ms per image. This research highlights significant advancements in intelligent transportation systems and road safety, achieved through integrating convolutional neural networks and embedded hardware platforms. © The Author(s) 2025.

关键词： Convolutional neural networks

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