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Extensive analysis of IoT Architecture and Access Control Policies in Fog Enabled Environment 2

Extensive analysis of IoT Architecture and Access Control Po...

引用

2nd international conference on advances in Computation, Communication and Information technology, ICAICCIT 2024

作者： Lalit, Mohit Maurya, Sant Kumar Khurana, Shiraz Gupta, Nishant Computer Science and Engineering Department Chandigarh University Punjab Mohali India Computer Science and Engineering Department School of ICT Gautam Buddha University Greater Noida India Computer Science and Engineering Department Sharda University Greater Noida India

ISBN: (纸本)9798331541217

Cloud technology provides solutions to a variety of software platform and data accessibility issues. However, as the industrial revolution 4.0 progresses, innovations such as healthcare 4.0 smart buildings, IoT enabled transportation services, and many other new paradigms necessitate more secure data management solutions. Meanwhile, Fog Computing (FC) arises as a supplement to cloud computing, providing a variety of solutions to issues such as low latency and real-time data transfer. However, security concerns remained, and to address such issues, a regressive access control mechanism approach study was necessary. This article addresses methods to access control mechanisms for preserving privacy and confidentiality during communication in a cloud-fog computing environment. The research goal is to investigate various access control approaches used in the recent past for fog computing enabled environments. © 2024 IEEE.

关键词： Cloud platforms

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Reconfigurable Hexapod-Serpentine Biomimetic Robot: Design and Experiments

Reconfigurable Hexapod-Serpentine Biomimetic Robot: Design a...

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2024 IEEE international conference on robotics and Biomimetics, ROBIO 2024

作者： Li, Zeyi Bai, Yang Guo, Yu Zhang, Shutao Han, Liang Huang, Yunzhi School of Electrical Engineering and Automation Hefei University of Technology Hefei2300009 China

ISBN: (纸本)9781665481090

With the development of robotics technology, traditional single-mode robots struggle to adapt to complex environments. To address this challenge, we develop a multi-modal reconfigurable robot capable of adapting to the complex environments. The robot, known as the Hexapod-Serpentine Biomimetic Robot(HSBR), features a reconfigurable interface that allows it to perform various tasks, including mobility, operational functions, and narrow pipeline detection. To achieve independent and combined movements in the HSBR, we implemented hexapod triangular gait planning, meandering gait planning, and mobile grasping operations. Additionally, we designed a controller to manage these functions. Results show that the designed robot has good performance in detection and manipulation in complex terrains. © 2024 IEEE.

关键词： Machine design

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Permissioned Blockchain Security Pqfabric from Quantum and Classical Attacks 1

Permissioned Blockchain Security Pqfabric from Quantum and C...

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1st international conference on advances in Computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Tamilarasi, C. Bhavadrarani, K. Kittappa, Thiagarajan Subashini, N. Anitha, V. Vimalraj, E. B.S.Abdur Rahman Crescent Institute of Science & Technology Department of Computer Science and Engineering Chennai India V.S.B. Engineering College Department of Computer Science and Engineering Karur India Rajalakshmi Institute of Technology Department of Mathematics Chennai600124 India Sathyabama Institute of Science and Technology Department of Mathematics Chennai600119 India Panimalar Engineering College Department of CSE Poonamallee Chennai600123 India School of Computing Mohan Babu University Andhra Pradesh Tirupati India

ISBN: (纸本)9798331518578

Old style cryptographic techniques are genuinely compromised by the development of quantum computing, which requires the formation of safety ideal models that are impervious to quantum mistakes. A new permissioned blockchain security system called PqFabric is intended to oppose both traditional and quantum attacks. PqFabric ensures the validness, mystery, and respectability of exchanges in a quantum-empowered future by including post-quantum cryptographic techniques like hash-based and grid based marks. As opposed to ordinary blockchains, PqFabric utilizes a half breed agreement process that gets information trades and members characters by melding Byzantine Fault Tolerance (BFT) with quantum-safe encryption. The system gives protection against calculation based attacks by Shor and Grover, tending to huge imperfections in existing blockchain structures. Besides, when quantum-safe guidelines advance, its secluded plan empowers smooth enhancements. With this procedure, PqFabric is situated as a ground breaking answer for organizations and areas wishing to safeguard their blockchain networks from new cryptographic risks. © 2025 IEEE.

关键词： Quantum computers

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Enhancing Face Detection and Recognition through Machine Learning Algorithm

Enhancing Face Detection and Recognition through Machine Lea...

引用

2023 international conference on Recent advances in science and engineering technology, ICRASET 2023

作者： Manu, Y.M. Gagana, R. Shashikala, S.V. Adichunchanagiri University Bgs Institute of Technology Department of Computer Science Mandya India

ISBN: (纸本)9798350306927

Face recognition is a rapidly growing field with multiple applications. Numerous face recognition algorithms have been developed over the years. In this research, use a Histogram of Oriented Gradients (HOG) based face detector for precise face detection, which surpasses other machine learning techniques, such as Haar Cascade. The suggested approach uses HOG for feature extraction and Contrast Limited Adaptive Histogram Equalization (CLAHE), two generally used pre-processing methods, throughout the recognition process. The test picture and the training images are both used to extract HOG features. Lastly, this system employs Support Vector Machine (SVM) for classification, as it effectively classifies the HOG features. Pre-processing techniques are utilized to equalize illumination, reduce noise, and enhance contrast. The study's findings show the dependability and effectiveness of this approach in achieving superior face recognition performance. © 2023 IEEE.

关键词： Support vector machines

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Evaluation of Classifiers Based on Neural Network for Handwritten Digit Recognition

Evaluation of Classifiers Based on Neural Network for Handwr...

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2024 international conference on advances in Computing Research on science engineering and technology, ACROSET 2024

作者： Sehta, Neha Saraf, Krupi Vinchi, Aditya Acropolis Institute of Technology and Research Department of Computer Science and Engineering Indore India

ISBN: (纸本)9798350388800

Handwritten Digit Recognition (HDR) refers to the computer' s ability to identify and categorize hand written digits from various sources into 10 predetermined categories, ranging from 0 to 9. The issue of digit recognition is significant and crucial. Due to variations in size, thickness, location, and orientation of manually written digits, several challenges need to be addressed in order to evaluate the problem of recognizing handwritten digits. The diversity and variety in the composition techniques of different persons also impact the pattern and appearance of the digits. It refers to the approach of recognizing and organizing written numbers. It offers a diverse array of uses, such as automated bank checks, postal addresses, and tax paperwork, among others. The objective of this research is to employ a classification system to accurately identify handwritten numerals. The consequences of the most widely employed deep learning algorithms, such as multilayered perceptron network, in conjunction with convolution neural networks, are being discussed. Comparison of five neural network classifier shows that accuracy up to 99% can be achieved only in few epochs of training with default configuration of hyper-parameters. © 2024 IEEE.

关键词： Deep learning

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Vulnerability Testing on IoT Networks Using Machine Learning Algorithm

Vulnerability Testing on IoT Networks Using Machine Learning...

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2024 international conference on advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Mohandas, R. Prasanna, D.S.John Deva Baiju, B.V. Nathiya, S. Rajkumar, T. Dhiliphan Sivashankar, C. Srm Institiute Of Science And Technology Department Of Computational Intelligence Chennai Kattankulathur India Srm Institiute Of Science And Technology Department Of Datascience And Business Systems Chennai Kattankulathur India Vit University TamilNadu Vellore India Prince Shri Venkateshwara Padmavathi Engineering College Department Of Electronics And Communication Engineering Ponmar Chennai India Kalasalingam Academy Of Research And Education Dept. Of Computer Science And Engineering Tamilnadu Krishnankovil India Department Of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

The increasing growth of Internet of Things (IoT) devices has created a wide attack surface for cyber criminals to carry out more destructive cyber attacks;therefore, the number of cyber attacks in the information security industry is increasing rapidly. As attackers use new and innovative methods to launch cyber-oriented attacks, many of these strikes have succeeded in their malicious goals. Anomaly-based intrusion detection systems (IDS) use machine learning techniques to detect and classify attacks on IoT networks. Faced with unpredictable network technologies and various infiltration methods, traditional machine learning technologies are powerless. In abounding areas of research, kernel learning methods prove that they accurately determine pathological abilities. © 2024 IEEE.

关键词： Internet of things

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Enhancing Road Safety with Real-Time Helmet Detection and E-Challan Issuance using YOLO and OCR 1

Enhancing Road Safety with Real-Time Helmet Detection and E-...

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1st IEEE international conference on Cognitive robotics and Intelligent Systems, ICC - ROBINS 2024

作者： Deepa, S. Vinoth Kumar, C.N.S. Duraivelu, Vivek Easwaran, Balamurugan Suguna, R. Aparna, H. Kongu Engineering College Department of Computer Technology-PG Tamilnadu Erode638060 India Srm Institute of Science and Technology College of Engineering and Technology Department of Networking and Communications Tamilnadu Chennai India B v Raju Institute of Technology Department of Computer Science and Engineering Telangana Narsapur502313 India Texila American University School of It Zambia Bannari Amman Institute of Technology Department of Computer Science and Business Systems Tamilnadu Sathyamangalam India Kongu Engineering College Perundurai Tamilnadu Erode638 060 India

ISBN: (纸本)9798350372748

This study proposes an integrated system combining Optical Character Recognition (OCR) and YOLO (You Only Look Once) for enforcing helmet laws and improving traffic safety. A user-friendly PyQT GUI facilitates vehicle registration, creating an organized CSV database for future reference. YOLOv5, an advanced object detection algorithm, identifies key elements like motorcycles, helmets, and number plates from input images. The primary objective is detecting motorcyclists without helmets, followed by OCR extraction of text from license plates. The extracted text is compared with registered bike information in the CSV file, generating e-challans and fines for matches. Automatic email notifications ensure timely communication and compliance with traffic regulations. The system's implementation not only aids helmet enforcement but also acts as a deterrent for future violations, fostering a safer driving environment. With scalability and practicality, this approach can integrate seamlessly into existing traffic control systems, leveraging AI technologies like YOLOv5 and OCR for effective problem-solving and enhanced road safety. © 2024 IEEE.

关键词： Object detection

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Geometric Control Methods for On-Orbit Assembly of Modular Spacecraft Cluster 3

Geometric Control Methods for On-Orbit Assembly of Modular S...

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3rd international conference on Mechatronics, Control and robotics, ICMCR 2025

作者： Wang, Jingxian Chen, Rong Bai, Yuzhu Zhao, Yong College of Aerospace Science and Engineering National University of Defense Technology Changsha China

ISBN: (纸本)9798331544546

In this paper, a cluster geometry control method is proposed for the problem of on-orbit assembly of modular spacecraft clusters. The method bases the cluster system on a manifold. A collision avoidance constraint that does not generate terminal position mutual exclusion is designed for the characteristics of the assembly problem. Assembly and task time constraints are further considered to integrate the non-convex multiple constraints with the system metric matrix. Finally, model predictive control is used to realize tracking control. Simulation results show that the method can arrive at the target position to complete the on-orbit assembly within any initial position and different fixed time constraints and achieve the purpose of energy optimization. © 2025 IEEE.

关键词： Tracking (position)

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Optimized Constrained Application Protocol for IoT Smart Home Data Security: A Novel Lightweight Approach

Optimized Constrained Application Protocol for IoT Smart Hom...

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2024 IEEE international conference on Recent advances in science and engineering technology, ICRASET 2024

作者： Subhashini, R. Jyothi, D.G. Bangalore Institute of Technology Affiliated to Visvesvaraya Technological University Department of Computer Science and Engineering Karnataka India Bangalore Institute of Technology Affiliated to Visvesvaraya Technological University Department of Artificial Intelligence and Machine Learning Karnataka India

ISBN: (纸本)9798350388602

By increasing simplicity and efficiency, a smart environment aims to enhance human existence. The IoT paradigm has evolved into a crucial technology for creating smart buildings, and the majority of computer networks now have IoT technologies. Nevertheless, during this shift, IoT devices are susceptible to cyberattacks. Thus, in practical smart home applications, security and privacy are key issues. In order to improve data security in smart home settings while lowering computing costs, this publication proposes the Broken-Stick Regressive Lightweight Speck Ephemeral Cryptography-based Constrained Application Protocol (BRLSC-CoAP). Real-time data is gathered by IoT devices and sent to authorized users. BRLSC-CoAP includes processes for authentication, encryption, decryption, and registration to safeguard this process. Forbes indexive Broken-stick regression is used to verify user authentication, and a lightweight Speck ephemeral cryptography technique is utilized for encryption. The experimental findings demonstrate that BRLSC-CoAP performs better than traditional techniques by increasing confidentiality, accuracy, and precision in authentication while lowering computing overhead, delay, and cost.. © 2024 IEEE.

关键词： Smart homes

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Omnidirectional Vector Measurement Method for Accurate Laser Positioning System 7

Omnidirectional Vector Measurement Method for Accurate Laser...

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7th international conference on Intelligent robotics and Control engineering, IRCE 2024

作者： Pan, Xiao Liu, Fei Liu, Qing Wang, Zhen Li, Jiapei Cheng, Pengfei Xi'an Aerocomm Measurement and Control Technology Co. Ltd. Xi'an China Xi'an University of Science and Technology School of Materials Science and Engineering Xi'an China Xi'an University of Technology School of Automation and Information Engineering Xi'an China Xi'an University of Technology School of Mechanical and Precision Instrument Engineering Xi'an China

ISBN: (纸本)9798350352399

The accurate laser positioning system (ALPS) is an emerging distributed large-scale laser positioning system, which has shown broad prospects in industrial production, navigation, and other fields. Addressing the issue of reduced measurement accuracy in complex large-space measurement scenarios due to laser signal obstruction encountered by traditional planar and spherical receiver units, this paper analyzes the measurement principle of ALPS. Based on omnidirectional photoelectric array units, a comprehensive vector measurement model is established, and a position and attitude calculation method for omnidirectional vector measurement is studied. Employing the Monte Carlo method based on statistical principles, the feasibility of the position and attitude calculation method is verified through simulation. Additionally, field experiments are conducted in conjunction with a laser tracking system to evaluate the absolute accuracy of the proposed model under point and attitude changes. The results indicate that the point accuracy exceeds 0.24mm with a standard deviation of less than 0.026mm. When attitude changes occur, the horizontal and pitch directions are superior to 0.28mm and 0.47mm, respectively, with standard deviations of less than 0.030mm and 0.032mm, meeting the system's sub-millimeter-level requirements and expanding the application scope of the ALPS system. © 2024 IEEE.

关键词： Monte Carlo methods

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