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An Efficient Authenticated Elliptic Curve Cryptography Scheme for Multicore Wireless Sensor Networks

IEEE Access 2023年 11卷 1306-1323页

作者： Oladipupo, Esau Taiwo Abikoye, Oluwakemi Christiana Imoize, Agbotiname Lucky Awotunde, Joseph Bamidele Chang, Ting-Yi Lee, Cheng-Chi Do, Dinh-Thuan The Federal Polytechnic Bida Department of Computer Science Bida912211 Nigeria University of Ilorin Faculty of Information and Communication Sciences Department of Computer Science Ilorin240003 Nigeria University of Lagos Faculty of Engineering Department of Electrical and Electronics Engineering Akoka Lagos100213 Nigeria Institute of Digital Communication Ruhr University Department of Electrical Engineering and Information Technology Bochum44801 Germany National Changhua University of Education Department of Industrial Education and Technology Changhua City500 Taiwan Fu Jen Catholic University Research and Development Center for Physical Education Health and Information Technology Department of Library and Information Science New Taipei City24205 Taiwan Asia University Department of Computer Science and Information Engineering Taichung City41354 Taiwan University of Mount Union School of Engineering AllianceOH44601 United States

The need to ensure the longevity of Wireless Sensor Networks (WSNs) and secure their communication has spurred various researchers to come up with various WSN models. Prime among the methods for extending the life span of WSNs is the clustering of Wireless Sensors (WS), which reduces the workload of WS and thereby reduces its power consumption. However, a drastic reduction in the power consumption of the sensors when multicore sensors are used in combination with sensors clustering has not been well explored. Therefore, this work proposes a WSN model that employs clustering of multicore WS. The existing Elliptic Curve Cryptographic (ECC) algorithm is optimized for parallel execution of the encryption/decryption processes and security against primitive attacks. The Elliptic Curve Diffie-Helman (ECDH) was used for the key exchange algorithm, and the Elliptic Curve Digital Signature Algorithm (ECDSA) was used to authenticate the communicating nodes. Security analysis of the model and comparative performance analysis with the existing ones were demonstrated. The security analysis results reveal that the proposed model meets the security requirements and resists various security attacks. Additionally, the projected model is scalable, energy-conservative, and supports data freshness. The results of comparative performance analysis show that the proposed WSN model can efficiently leverage multiprocessors and/or many cores for quicker execution and conserves power usage. © 2013 IEEE.

关键词： Electric power utilization

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Deeply‐Recursive Attention Network for video steganography

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CAAI Transactions on Intelligence technology 2023年第4期8卷 1507-1523页

作者： Jiabao Cui Liangli Zheng Yunlong Yu Yining Lin Huajian Ni Xin Xu Zhongfei Zhang College of Computer Science and Technology Zhejiang UniversityHangzhouChina School of Software Technology Zhejiang UniversityNingboChina College of Information Science and Electronic Engineering Zhejiang UniversityHangzhouChina Shanghai SUPREMIND Technology Co. Ltd.ShanghaiChina College of Intelligence Science and Technology National University of Defense TechnologyChangshaChina Department of Computer Science Binghamton UniversityBinghamtonNew YorkUSA

Video steganography plays an important role in secret communication that conceals a secret video in a cover video by perturbing the value of pixels in the cover *** is the first and foremost requirement of any steganographic *** by the fact that human eyes perceive pixel perturbation differently in different video areas,a novel effective and efficient Deeply‐Recursive Attention Network(DRANet)for video steganography to find suitable areas for information hiding via modelling spatio‐temporal attention is *** DRANet mainly contains two important components,a Non‐Local Self‐Attention(NLSA)block and a Non‐Local Co‐Attention(NLCA)***,the NLSA block can select the cover frame areas which are suitable for hiding by computing the correlations among inter‐and intra‐cover *** NLCA block aims to effectively produce the enhanced representations of the secret frames to enhance the robustness of the model and alleviate the influence of different areas in the secret ***,the DRANet reduces the model parameters by performing similar operations on the different frames within an input video *** results show the proposed DRANet achieves better performance with fewer parameters than the state‐of‐the‐art competitors.

关键词： data privacy video processing

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Recognition of Urdu Handwritten Alphabet Using Convolutional Neural Network (CNN)

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computers, Materials & Continua 2022年第11期73卷 2967-2984页

作者： Gulzar Ahmed Tahir Alyas Muhammad Waseem Iqbal Muhammad Usman Ashraf Ahmed Mohammed Alghamdi Adel A.Bahaddad Khalid Ali Almarhabi Department of Computer Science University of South AsiaLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Handwritten character recognition systems are used in every field of life nowadays,including shopping malls,banks,educational institutes,*** is the national language of Pakistan,and it is the fourth spoken language in the ***,it is still challenging to recognize Urdu handwritten characters owing to their cursive *** paper presents a Convolutional Neural Networks(CNN)model to recognize Urdu handwritten alphabet recognition(UHAR)offline and online *** research contributes an Urdu handwritten dataset(aka UHDS)to empower future works in this *** offline systems,optical readers are used for extracting the alphabets,while diagonal-based extraction methods are implemented in online ***,our research tackled the issue concerning the lack of comprehensive and standard Urdu alphabet datasets to empower research activities in the area of Urdu text *** this end,we collected 1000 handwritten samples for each alphabet and a total of 38000 samples from 12 to 25 age groups to train our CNN model using online and offline ***,we carried out detailed experiments for character recognition,as detailed in the *** proposed CNN model outperformed as compared to previously published approaches.

关键词： Urdu handwritten text recognition handwritten dataset convolutional neural network artificial intelligence machine learning deep learning

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COVID-19 Classification from X-Ray Images:An Approach to Implement Federated Learning on Decentralized Dataset

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computers, Materials & Continua 2023年第5期75卷 3883-3901页

作者： Ali Akbar Siddique S.M.Umar Talha M.Aamir Abeer D.Algarni Naglaa F.Soliman Walid El-Shafai Department of Telecommunication Engineering Sir Syed University of Engineering&TechnologyKarachi75300Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

The COVID-19 pandemic has devastated our daily lives,leaving horrific repercussions in its *** to its rapid spread,it was quite difficult for medical personnel to diagnose it in such a big *** who test positive for Covid-19 are diagnosed via a nasal PCR *** comparison,polymerase chain reaction(PCR)findings take a few hours to a few *** PCR test is expensive,although the government may bear expenses in certain ***,subsets of the population resist invasive testing like ***,chest X-rays or computerized Vomography(CT)scans are preferred in most cases,and more importantly,they are non-invasive,inexpensive,and provide a faster response *** advances in Artificial Intelligence(AI),in combination with state-of-the-art methods,have allowed for the diagnosis of COVID-19 using chest *** article proposes a method for classifying COVID-19 as positive or negative on a decentralized dataset that is based on the Federated learning *** order to build a progressive global COVID-19 classification model,two edge devices are employed to train the model on their respective localized dataset,and a 3-layered custom Convolutional Neural Network(CNN)model is used in the process of training the model,which can be deployed from the *** two edge devices then communicate their learned parameter and weight to the server,where it aggregates and updates the *** proposed model is trained using an image dataset that can be found on *** are more than 13,000 X-ray images in Kaggle Database collection,from that collection 9000 images of Normal and COVID-19 positive images are *** edge node possesses a different number of images;edge node 1 has 3200 images,while edge node 2 has *** is no association between the datasets of the various nodes that are included in the *** doing it in this manner,each of the nodes will have access to a separate image collection that has no correl

关键词： Artificial intelligence deep learning federated learning COVID-19 decentralized image dataset

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Self-adaptive Bat Algorithm With Genetic Operations

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1284-1294页

作者： Jing Bi Haitao Yuan Jiahui Zhai MengChu Zhou H.Vincent Poor School of Software Engineering Faculty of Information TechnologyBeijing University of TechnologyBeijing 100124China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Department of Electrical Engineering Princeton UniversityPrinceton NJ 08544 USA IEEE

Swarm intelligence in a bat algorithm(BA)provides social *** operations for reproducing individuals in a genetic algorithm(GA)offer global search ability in solving complex optimization *** integration provides an opportunity for improved search ***,existing studies adopt only one genetic operation of GA,or design hybrid algorithms that divide the overall population into multiple subpopulations that evolve in parallel with limited interactions *** from them,this work proposes an improved self-adaptive bat algorithm with genetic operations(SBAGO)where GA and BA are combined in a highly integrated ***,SBAGO performs their genetic operations of GA on previous search information of BA solutions to produce new exemplars that are of high-diversity and *** by these exemplars,SBAGO improves both BA’s efficiency and global search *** evaluate this approach by using 29 widely-adopted problems from four test *** is also evaluated by a real-life optimization problem in mobile edge computing *** results show that SBAGO outperforms its widely-used and recently proposed peers in terms of effectiveness,search accuracy,local optima avoidance,and robustness.

关键词： Bat algorithm(BA) genetic algorithm(GA) hybrid algorithm learning mechanism meta-heuristic optimization algorithms

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Eliciting Requirements from Stakeholders’ Responses Using Natural Language Processing

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computer Modeling in engineering & sciences 2021年第4期127卷 99-116页

作者： Mohammed Lafi Bilal Hawashin Shadi AlZu’bi Department of Software Engineering Faculty of Science and Information TechnologyAl-Zaytoonah University of JordanAmman11733Jordan Department of Computer Information Systems Faculty of Science and Information TechnologyAl-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science Faculty of Science and Information TechnologyAl-Zaytoonah University of JordanAmman11733Jordan

Most software systems have different stakeholders with a variety of *** process of collecting requirements from a large number of stakeholders is vital but *** propose an efficient,automatic approach to collecting requirements from different stakeholders’responses to a specific *** use natural language processing techniques to get the stakeholder response that represents most other stakeholders’*** study improves existing practices in three ways:Firstly,it reduces the human effort needed to collect the requirements;secondly,it reduces the time required to carry out this task with a large number of stakeholders;thirdly,it underlines the importance of using of data mining techniques in various software engineering *** approach uses tokenization,stop word removal,and word lemmatization to create a list of frequently accruing *** then creates a similarity matrix to calculate the score value for each response and selects the answer with the highest *** experiments show that using this approach significantly reduces the time and effort needed to collect requirements and does so with a sufficient degree of accuracy.

关键词： software requirements requirements elicitation natural language processing

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SPUFChain: Permissioned Blockchain Lightweight Authentication Scheme for Supply Chain Management Using PUF of IoT

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IEEE Access 2025年 13卷 88662-88682页

作者： Assaqty, Mohammad Iqbal Saryuddin Gao, Ying Alqarni, Abeer D. Khan, Siraj Chakraborty, Mohuya Nur Siddiqi, Hafied Ahmad, Sadique South China University of Technology School of Computer Science and Engineering Guangzhou510006 China Universitas Nahdlatul Ulama Indonesia Faculty of Engineering and Computer Science Jakarta10320 Indonesia Princess Nourah bint Abdulrahman University College of Computer and Information Sciences Department of Information Technology P.O. Box 84428 Riyadh11671 Saudi Arabia Research Institute for Future Media Computing College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China University of Engineering and Management Cybersecurity Centre of Excellence Kolkata700160 India Riyadh12435 Saudi Arabia

The complexity of the entire process of supply chain management (SCM) is quite cumbersome and traditional way of handling it is devoid of proper authentication and security and very often suffers from human errors in dealing with flaws in quality control process of SCM. While it may have started with shipment tracking, the outcome of using IoT on supply chains has spread to every link in the chain. For instance, manufacturers are employing Internet-enabled sensors in production to find product faults, resulting in higher-quality production runs. Physical Unclonable Function (PUF) is a defense countermeasure that exploits the exclusive, unrepeatable features of hardware components to generate distinct cryptographic keys or identifiers, typically for a semiconductor device like an Internet of Things (IoT) device. The distinctive proof of identity of IoT devices in the supply chain is employed by means of PUFs as inviolable IDs. Blockchain, the distributed, immutable ledger, on the other hand is the disruptive technology that provides higher security as compared to traditional centralized systems. The integration of PUF and blockchain proves to be quite interesting while handling the above issues of authentication. A smart contract on the blockchain is a software code that executes spontaneously as and when the conditions of the contract or agreement are satisfied. Hence after authentication process the results are fed to blockchain smart contract for the final validation. This paper presents a novel permissioned blockchain smart contract-based lightweight authentication scheme for SCM using PUF of IoT known as SPUFChain. Informal and formal security analysis (using AVISPA and BAN logic) of the proposed framework show its efficiency to resist several threat scenarios like man-in-the middle, non-repudiation, impersonation, replay attacks and many other security features as compared to other related schemes. The processing time (~13.8ms) is better than existing lightweig

关键词： Supply chain management

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DERLight: A Deep Reinforcement Learning Traffic Light Control Algorithm with Dual Experience Replay

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Journal of Internet technology 2024年第1期25卷 79-86页

作者： Yang, Zhichao Kong, Yan Hsia, Chih-Hsien School of Computer and Software Nanjing University of Information Science and Technology China Department of Computer Science and Information Engineering National Ilan University Taiwan Department of Business Administration Chaoyang University of Technology Taiwan

In recent years, with the increasingly severe traffic environment, most cities are facing various traffic congestion problems, and the demand for intelligent regulation of traffic signals is also increasing. In this study, we propose a new intelligent traffic light control algorithm, dual experience replay light (DERLight), which innovatively and efficiently designs a dual experience replay training mechanism based on the classic deep Q network (DQN) framework and considers the dynamic epoch function. As results show that compared with some state-of-the-art algorithms, DERLight can shorten the average travel time of vehicles, increase the throughput at intersections, and also speed up the convergence of the network. In addition, the design of this algorithm framework is not only limited to the field of intelligent transportation, but also has transferability for some other fields. © 2024 Taiwan Academic Network Management Committee. All rights reserved.

关键词： Reinforcement learning

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TinyML-Based Gait Recognition for User Detection on an STM32L4 IoT Node 9

TinyML-Based Gait Recognition for User Detection on an STM32...

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9th IEEE International Conference for Convergence in technology, I2CT 2024

作者： Hassan, Hateem Abdullah, M. Hussain, Muhammad Zunnurain Hasan, Muhammad Zulkifl Mustafa, Muzzamil Khalid, Aqsa Awan, Rimsha Hussain, Usman Khan, Zohaib Ahmed Javaid, Arslan University Lahore Department of Computer Engineering Information Technology Punjab Pakistan Bahria University Lahore Campus Dept. of Computer Science Pakistan University of Central Punjab Lahore Pakistan Faculty of Information Technology Department of Computer Science Pakistan National College of Business Administration And Economics Department of Computer Science Lahore Pakistan Information Technology University Lahore Pakistan University of Home Economics Pakistan

ISBN: (纸本)9798350394474

Gait recognition stands out as a robust biometric tool for discerning users. Yet, adapting it to devices with limited resources, such as the STM32L4 microcontroller, demands cutting-edge strategies. This research unveils an innovative TinyML methodology, leveraging a specially-designed Convolutional Neural Network (CNN). Notably, our bespoke CNN model showcased a remarkable 97.3% accuracy in pinpointing users on the STM32L4 system. © 2024 IEEE.

关键词： Convolutional neural networks

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A Three-Dimensional Real-Time Gait-Based Age Detection System Using Machine Learning

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computers, Materials & Continua 2023年第4期75卷 165-182页

作者： Muhammad Azhar Sehat Ullah Khalil Ullah Habib Shah Abdallah Namoun Khaliq Ur Rahman Department of Computer Science&IT University of MalakandChakdara18800Pakistan Department of Software Engineering University of MalakandChakdara18800Pakistan College of Computer Science King Khalid UniversityAbha62529Saudi Arabia Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Statistics Abdul Wali Khan UniversityMardan23200Pakistan

Human biometric analysis has gotten much attention due to itswidespread use in different research areas, such as security, surveillance,health, human identification, and classification. Human gait is one of the keyhuman traits that can identify and classify humans based on their age, gender,and ethnicity. Different approaches have been proposed for the estimation ofhuman age based on gait so far. However, challenges are there, for which anefficient, low-cost technique or algorithm is needed. In this paper, we proposea three-dimensional real-time gait-based age detection system using a machinelearning approach. The proposed system consists of training and testingphases. The proposed training phase consists of gait features extraction usingthe Microsoft Kinect (MS Kinect) controller, dataset generation based onjoints’ position, pre-processing of gait features, feature selection by calculatingthe Standard error and Standard deviation of the arithmetic mean and bestmodel selection using R2 and adjusted R2 techniques. T-test and ANOVAtechniques show that nine joints (right shoulder, right elbow, right hand, leftknee, right knee, right ankle, left ankle, left, and right foot) are statisticallysignificant at a 5% level of significance for age estimation. The proposedtesting phase correctly predicts the age of a walking person using the resultsobtained from the training phase. The proposed approach is evaluated on thedata that is experimentally recorded from the user in a real-time *** (50) volunteers of different ages participated in the experimental *** the limited features, the proposed method estimates the age with 98.0%accuracy on experimental images acquired in real-time via a classical generallinear regression model.

关键词： Age estimation gait biometrics classical linear regression model

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