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Deep Transfer Learning Techniques in Intrusion Detection System-Internet of Vehicles: A State-of-the-Art Review

computers, Materials & Continua 2024年第8期80卷 2785-2813页

作者： Wufei Wu Javad Hassannataj Joloudari Senthil Kumar Jagatheesaperumal Kandala N.V.P.SRajesh Silvia Gaftandzhieva Sadiq Hussain Rahimullah Rabih Najibullah Haqjoo Mobeen Nazar Hamed Vahdat-Nejad Rositsa Doneva School of Information Engineering Nanchang UniversityNanchang330031China Department of Computer Engineering Technical and Vocational University(TVU)Tehran***Iran Department of Computer Engineering University of BirjandBirjand***Iran Department of Computer Engineering Babol BranchIslamic Azad UniversityBabol***Iran Department of Electronics&Communication Engineering Mepco Schlenk Engineering CollegeSivakasi626005India School of Electronics Engineering VIT-AP UniversityNear Vijayawada522237India Faculty of Mathematics and Informatics University of Plovdiv Paisii HilendarskiPlovdiv4000Bulgaria Examination Branch Dibrugarh UniversityDibrugarh786004India Department of Computer Engineering Faculty of EngineeringUniversity of BirjandBirjand***Iran Faculty of Electrical and Computer Engineering University of BirjandBirjand***Iran Malaysian Institute of Information Technology Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Physics and Technology University of Plovdiv Paisii HilendarskiPlovdiv4000Bulgaria

The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles(IoV)*** functional advantages of IoV include online communication services,accident prevention,cost reduction,and enhanced traffic *** these benefits,IoV technology is susceptible to cyber-attacks,which can exploit vulnerabilities in the vehicle network,leading to perturbations,disturbances,non-recognition of traffic signs,accidents,and vehicle *** paper reviews the state-of-the-art achievements and developments in applying Deep Transfer Learning(DTL)models for Intrusion Detection Systems in the Internet of Vehicles(IDS-IoV)based on anomaly ***-IoV leverages anomaly detection through machine learning and DTL techniques to mitigate the risks posed by *** systems can autonomously create specific models based on network data to differentiate between regular traffic and *** these techniques,transfer learning models are particularly promising due to their efficacy with tagged data,reduced training time,lower memory usage,and decreased computational *** evaluate DTL models against criteria including the ability to transfer knowledge,detection rate,accurate analysis of complex data,and *** review highlights the significant progress made in the field,showcasing how DTL models enhance the performance and reliability of IDS-IoV *** examining recent advancements,we provide insights into how DTL can effectively address cyber-attack challenges in IoV environments,ensuring safer and more efficient transportation networks.

关键词： Cyber-attacks internet of things internet of vehicles intrusion detection system

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Reconfigurable Intelligent Surface Direct Data Modulation With Adaptive Beam Steering Backscatter communication

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IEEE Internet of Things Journal 2025年第11期12卷 15600-15619页

作者： Amri, Muhammad Miftahul Aziz, Arif Abdul Tran, Nguyen Minh Park, Je Hyeon Kim, Dong In Choi, Kae Won Sungkyunkwan University College of Information and Communication Engineering Department of Electrical and Computer Engineering Suwon16419 Korea Republic of University Center of Excellence for Intelligent Sensing-IoT Telkom University Bandung40257 Indonesia VNU University of Engineering and Technology Faculty of Electronics and Telecommunications Department of Wireless Communications Hanoi100000 Viet Nam

Reconfigurable intelligent surface (RIS) has emerged as a promising technology for next-generation wireless communications due to its ability to manipulate electromagnetic (EM) waves. This work introduces a novel RIS direct modulation scheme based on the backscatter communication concept. In this work, the RIS acts as a sole information modulator. Unlike conventional RIS systems that relay incoming datacarrying waves, this work enables RIS to encode its own information into unmodulated waves without requiring any hardware modifications. We propose an adaptive algorithm that maximizes modulation order while meeting the quality of service (QoS) requirements by selecting appropriate constellation points to minimize error probability. The proposed scheme was validated through simulations and experiments using a passive 5.8 GHz RIS prototype. The validations demonstrate consistent performance in both distributed and co-located transmitter- receiver scenarios. These results highlight its feasibility as an alternative approach for RIS-assisted communications and contribute to further exploration of RIS-enabled symbiotic radio (SR) and over-the-air (OTA) modulation systems. © 2014 IEEE.

关键词： Adaptive algorithms

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A Hybrid Approach for Diagnosing Diabetic Retinopathy in Retinal Fundus Images using an Adaptive Canny Edge Detection approach 15

A Hybrid Approach for Diagnosing Diabetic Retinopathy in Ret...

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15th International Conference on Computing communication and Networking Technologies, ICCCNT 2024

作者： Manjula Devi, R. Kowsalya, M. Dinesh, P.M. Ponmurugan, P. Berlin, A. Kavin Kumar, K. Sangeetha, M. Chandrasekaran, Gokul Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Computer Science and Engineering Erode Sengunthar Engineering College Thuduppathi638057 India Department of Electronics and Communication Engineering Sona College of Technology Salem636005 India Chennai600078 India Department of Electronics and Communication Engineering Jansons Institute of Technology Coimbatore India Department of Electronics and Communication Engineering Kongu Engineering College Perundurai638060 India Department of Information Technology Dr.N.G.P. Institute of Technology Tamilnadu Coimbatore India Department of Electronics and Communication Engineering Karpagam Institute of Technology Coimbatore India

ISBN: (纸本)9798350370249

Individuals diagnosed with diabetes are susceptible to developing diabetic retinopathy (DR), a degenerative eye condition that affects the retina. When blood vessels in the retina get damaged, it can cause permanent vision impairment or even blindness if the underlying condition is not addressed quickly enough. Early diagnosis and treatment of this disease can save a patient's eyesight and prevent blindness. Successful medications for DR are available, but people with diabetes need to be identified and monitored early on. In order to diagnose diabetic retinopathy, many physical examinations have to be conducted;however, these types of exams require more time to complete. Adaptive Canny Edge Detection Training using Adaptive Skipping technique (ACEDIAS) is used in this research to speed up the detection process of diabetic retinopathy by detecting the edge and boost diagnostic accuracy. The study team chooses to use a 2063-image dataset compressed from Kaggle's library. The suggested ACEDIAS model is evaluated for its performance using the measures such as accuracy, recall, precision, and F1-score. It has been demonstrated through simulation that the suggested ACEDIAS model outperforms the existing models. ©2024 IEEE.

关键词： Ophthalmology

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Development of an Ontology-Based Technique for Labeling Land Cover Classes with Minimum Utilization of SAR Features

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SN computer Science 2023年第6期4卷 731页

作者： Gupta, Shruti Singh, Dharmendra Kumar, Sandeep Computer Science and Engineering and Information Technology Department Jaypee Institute of Information Technology Noida India Electronics and Communication Engineering Department Indian Institute of Technology Roorkee Roorkee India Computer Science and Engineering Department Indian Institute of Technology Roorkee Roorkee India

The availability of satellite imagery to "domain" experts, along with advancements in image processing and analysis techniques, has revolutionized numerous fields, enabling better understanding, planning, and management of our planet's resources. However, formalizing the knowledge gained from domain experts is essential for preserving, sharing, and leveraging their expertise. In this context, knowledge representation methods like ontology play a significant role in the development of applications based on satellite image analysis. Land cover labeling is one of the significant applications of satellite image analysis and plays a vital role in various domains by providing valuable information about the Earth's surface. Although several works have been reported to focus on land cover land use classification and labeling, very few are properly documented or formalized. Therefore, in this paper, an LCL (land cover labeling) ontology has been proposed for labeling the land cover classes using PALSAR-I satellite data. The ontology is based on an adaptive algorithm, as the labeling criterion is independent of specific range values and depends on feature image statistics. For algorithm development, four types of features, namely, polarimetric features, texture features, color features, and wavelet features were examined. For selecting optimal feature set, random forest was utilized and, consequently, for further labeling the classes a set of rules has been formed by applying Otsu thresholding on the selected class-wise feature sets. The derived rules were finally formalized to develop the ontology for labeling the land cover classes. The proposed ontology was applied to distinct study sites using PALSAR-I data which resulted in a satisfactory classification accuracy of around 85%. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Color features Ontology PALSAR Polarimetric features Random forests Texture features Wavelet features

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Smart Grid Security Framework for Data Transmissions with Adaptive Practices Using Machine Learning Algorithm

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computers, Materials & Continua 2025年第3期82卷 4339-4369页

作者： Shitharth Selvarajan Hariprasath Manoharan Taher Al-Shehari Hussain Alsalman Taha Alfakih School of Built Environment Engineering and ComputingLeeds Beckett UniversityLeedsLS13HEUK Department of Computer Science and Engineering Chennai Institute of TechnologyChennai602109India Centre for Research Impact & Outcome Chitkara UniversityChandigarh140401India Department of Electronics and Communication Engineering Panimalar Engineering CollegeChennai600123India Department of Self-Development Skill Common First Year DeanshipKing Saud UniversityRiyadh11362Saudi Arabia Department of Computer Science College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Information Systems College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

This research presents an analysis of smart grid units to enhance connected units’security during data *** major advantage of the proposed method is that the system model encompasses multiple aspects such as network flow monitoring,data expansion,control association,throughput,and *** addition,all the above-mentioned aspects are carried out with neural networks and adaptive optimizations to enhance the operation of smart grid ***,the quantitative analysis of the optimization algorithm is discussed concerning two case studies,thereby achieving early convergence at reduced *** suggested method ensures that each communication unit has its own distinct channels,maximizing the possibility of accurate *** results in the provision of only the original data values,hence enhancing *** power and line values are individually observed to establish control in smart grid-connected channels,even in the presence of adaptive settings.A comparison analysis is conducted to showcase the results,using simulation studies involving four scenarios and two case *** proposed method exhibits reduced complexity,resulting in a throughput gain of over 90%.

关键词： Machine learning power systems security smart grid

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A Deep Analysis on Security Aspects of Cloud Computing Ontologies 5

A Deep Analysis on Security Aspects of Cloud Computing Ontol...

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5th IEEE International Conference on Computing, Power, and communication Technologies, IC2PCT 2024

作者： Bisht, Girish Singh Gobi, N. Kapse, Vinod Mansiram Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Science and Information Technology Bangalore India Noida Institute of Engineering and Technology Department of Electronics and Communication Engineering Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350383522

The primary objective of this research is to get a comprehensive understanding of Cloud Computing ontologies, their applications, and their specific areas of interest. The proposed research methodology for this systematic review comprises a well-defined research topic, criteria for including and excluding studies, and a comprehensive search strategy to identify relevant source papers for the review. The chosen research is categorized into four main areas: elucidation of cloud resources and services, elaboration of cloud security, clarity of cloud interoperability, and understanding of cloud services discovery and selection. Utilizing ontologies to improve the security and smooth integration of cloud computing services uncovers various challenges and identifies areas for more research. © 2024 IEEE.

关键词： Cloud Computing Cloud service ontology systematic review

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A Novel Approach Based on Hybrid Algorithm for Energy Efficient Cluster Head Identification in Wireless Sensor Networks

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computer Systems Science & engineering 2022年第10期43卷 259-273页

作者： C.Ram Kumar K.Murali Krishna Mohammad Shabbir Alam K.Vigneshwaran Sridharan Kannan C.Bharatiraja Department of Electronics and Communication Engineering Dr.N.G.P.Institute of TechnologyCoimbatore641048India Department of Electronics and Communication Engineering Vignan’s Institute of Information TechnologyDuvvadaVisakhapatnam530049India Department of Computer Science College of Computer Science and Information TechnologyJazan UniversityJizan45142Kingdom of Saudi Arabia Department of Electronics and Communication Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science and Engineering JKK Munirajah College of TechnologyErode638506India Department of Electrical and Electronics Engineering SRM Institute of Science and TechnologyChennai603203India

The Wireless Sensor Networks(WSN)is a self-organizing network with random deployment of wireless nodes that connects each other for effective monitoring and data *** clustering technique employed to group the collection of nodes for data transmission and each node is assigned with a cluster *** major concern with the identification of the cluster head is the consideration of energy consumption and hence this paper proposes an hybrid model which forms an energy efficient cluster head in the Wireless Sensor *** proposed model is a hybridization of Glowworm Swarm Optimization(GSO)and Artificial Bee Colony(ABC)algorithm for the better identification of cluster *** performance of the proposed model is compared with the existing techniques and an energy analysis is performed and is proved to be more efficient than the existing model with normalized energy of 5.35%better value and reduction of time complexity upto 1.46%.Above all,the proposed model is 16%ahead of alive node count when compared with the existing methodologies.

关键词： Wireless sensor network cluster cluster head hybrid model glowworm swarm optimization artificial bee colony algorithm energy consumption

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Towards Mutation Testing of Embedded Software: A Framework and Case Study 35

Towards Mutation Testing of Embedded Software: A Framework a...

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35th IEEE International Symposium on Software Reliability engineering Workshops, ISSREW 2024

作者： Jiang, Wei Dong, Sijin Zhang, Jiaming Tang, Jin Zhang, Zichao Sun, Chang-Ai Zhang, Xiaoyi China Electronics Technology Group Corporation Information Science Academy Beijing China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China

ISBN: (纸本)9798350367041

Embedded software commonly executes safety-critical tasks and thus is expected to be highly reliable, which calls for stronger quality assurance techniques. As a fault-based testing technique, mutation testing is widely recognized to have stronger fault detection capability than those coverage or function-based testing techniques. However, some unique features of embedded software, such as limited hardware resources, real-time requirements, and differences between development and execution environments, pose challenging issues for the application of mutation testing. In this study, we explore the application of mutation testing to embedded software. As a result, we propose a mutation testing framework for embedded software, and evaluate the simulation capability of mutation operators for real-life faults in embedded software. A case study was conducted on a realistic open-source embedded software to evaluate the effectiveness and efficiency of the proposed technique. The experimental results demonstrate that mutation testing is able to detect various faults of embedded software, thus delivering a promising supplement for embedded software testing. © 2024 IEEE.

关键词： Case Study Embedded software Mutation Operators Mutation testing Software testing

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Defaulter detection based on Spearman correlation with hyper tuned SVM classification for preventing non-performing assets occurring in bank

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Multimedia Tools and Applications 2024年 1-23页

作者： Mallik, Rajib Puri, Shalini Bhansali, Ashok Manikandan, R. Rahunathan, L. Agartala799046 India Department of Information Technology Manipal University Jaipur Rajasthan303007 India Department of Computer Engineering and Applications GLA University Uttar Pradesh Mathura281406 India Department of Electronics and Communication Engineering Panimalar Engineering College Tamil Nadu Chennai600123 India Department of Computer Applications Kongu Engineering College Tamil Nadu Perundurai Erode638060 India

A common problem in the banking industry is loan default prediction, which may help identify defaulters who are most likely to stop making payments on their loan payments. Additionally, this information may be used to change the terms and conditions of loans, set aside additional money to guard against potential losses, or even refuse or restrict loans to clients that present a high risk. Although there are numerous conventional techniques for extracting data from loan applications, the majority of these techniques appear to be underperforming, which results in numerous problematic loans. In this proposed model, the detection of defaulter based on Spearman rank correlation with hyper tuned SVM classification is designed for preventing non-performing assets occurring in the bank. For novelty of the model, the missing value replacement is done with the Classification and Regression Tree (CART), which is an imputation as well as classification model that can impute values at missing column based on replacing the different values place at missing place by attaining the best classification accuracy. Then the Z-score normalization and Spearman rank correlation coefficient has been used for normalizing the data and correlation based feature reduction helps to classify then model with low computational complexity. In this hyper tuned SVM model, the traditional SVM model based on grid search cross validation is used for tuning the SVM parameters to accurately detect the defaulter from preventing the non-performing assets occurring in the bank. For evaluating the performance of the proposed loan prediction model, the precision, specificity, accuracy, recall, and Error are 95%, 97%, 96%, 96% and 4%. According to this evaluations, the proposed design performs better than existing model. Thus, the loan defaulter detection using Spearman’s correlation and hyper tuned SVM classification prevents the Non-Performing Assets (NPA) occurring in the bank. © The Author(s), under exclusiv

关键词： CART Defaulter Hyper tuned SVM Loan Spearman rank correlation Z-score

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GuardianForest: Cloud-Powered Patient Health Assurance through Isolation Forests 7

GuardianForest: Cloud-Powered Patient Health Assurance throu...

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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Subramanian, M. Gokulakrishnan, K. Nirmala, B. Vijaya Vijay Shankar, S. Krishnan, R. Santhana Vinoth Rajkumar, G. Scad College of Engineering And Technology Department of Computer Science And Engineering Cheranmahadevi India College of Engineering Guindy Anna University Department of Electronics And Communication Engineering Chennai India Psna College of Engineering And Technology Department of Information Technology Dindigul India Sona College of Technology Department of Electrical And Electronics Engineering Salem India Scad College of Engineering And Technology Department of Electronics And Communication Engineering Cheranmahadevi India J.P. College of Engineering Department of Electronics And Communication Engineering Thenkasi India

ISBN: (纸本)9798350359299

The proposed patient monitoring system is a substantial progression in healthcare technology. It integrates various sensors and communication modules to provide real-time patient data to caregivers and medical professionals. The array of sensors includes a non-contact temperature sensor, a rain sensor, a Max30100 sensor, and a load cell sensor. The non-contact temperature sensor vigilantly tracks the patient's body temperature, alerting caregivers to any deviations. The rain sensor serves as a communication channel for patients unable to express needs, detecting urination. The Max30100 sensor monitors critical health metrics like heart rate and blood oxygen levels for early detection of conditions. The load cell sensor observes saline levels in IV bags, triggering alerts on nearing critical thresholds. Powered by an Arduino microcontroller, the system aggregates data, relaying it to a dedicated server via Wi-Fi for remote accessibility. The Isolation Forest-based IsoSentry Algorithm enhances anomaly detection, identifying aberrations in health readings. Adding reliability, a GSM module connected to Arduino dispatches real-time alerts via text messages. In essence, "GuardianForest"epitomizes a transformative leap in healthcare, integrating cutting-edge hardware, wireless communication, and cloud-based data management to enhance overall healthcare responsiveness and efficacy. © 2024 IEEE.

关键词： Internet of things

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