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Block chain-based trusted smart contract for secure mobile user payment gateway in e-health systems

Soft Computing 2024年第17-18期28卷 10139-10151页

作者： Saranya, A. Naresh, R. Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur Chengalpattu Tamil Nadu Chennai603203 India Department of Networking and Communications SRM Institute of Science and Technology Kattankulathur Chengalpattu Tamil Nadu Chennai603203 India

In other instances, the cloud transfers payment information directly to the merchant’s server without first doing any fraud checks. Block authentication between the cloud and a healthcare merchant server is the goal of this study, which is designed to prevent the deployment of fraudulent servers. Smart contract verification on the blockchain will be used to this end. The cloud assault must be prevented from accessing personal payment and card information. It is via the employment of cryptography methods that this concept of privacy reservation is made possible. The Boolean crossover depth first search (DFS) technique is used to encrypt data in the payment gateway protocol at its inception. When the hospital administrator solicits card data from patients or users, our innovative approach swiftly initiates data encryption using the DFS technique. This method meticulously traverses the data structure in a depth-first manner, employing Boolean operations to systematically encrypt sensitive information. Through this process, the patient's payment and card data undergo secure transformation, rendering it unreadable to unauthorized entities. Additionally, an authentication key is generated concurrently with the encryption process, enabling verification between the system and the user before any data transmission occurs. The integration of the DFS technique serves as a fundamental layer of defense against potential cloud-based attacks. Its application ensures the utmost protection of personal payment and card details throughout the transaction process, bolstering the security infrastructure of our proposed system. A comprehensive analysis comparing our approach with existing methods showcases the efficiency and reliability of our proposed system in terms of Execution Time (ms), Encryption Time (ms), Decryption Time (ms), and Memory (bits). This study aims to bridge the gap in transactional security, ensuring robust protection against unauthorized access and data breaches in

关键词： Smart contract

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A Robust Emergency Messages Routing Scheme for Urban VANETs

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computers, Materials & Continua 2022年第8期72卷 2617-2632页

作者： Mumtaz Ali Shah Farrukh Zeeshan Khan Ghulam Abbas Department of Computer Science University of Engineering and TechnologyTaxilaPakistan Telecommunications and Networking Research Center GIK Institute of Engineering Sciences and TechnologyTopi23640Pakistan

Vehicular ad-hoc networks(VANETs)play an essential role in enhancing transport infrastructure by making vehicles intelligent and proficient in preventing traffic ***-based greedy protocols pick the next route vehicle for transmitting emergency messages(EMs)depending upon the present location of adjacent vehicles towards sink vehicles by using an optimal uni-directional road traffic ***,such protocols suffer performance degradation by ignoring the moving directions of vehicles in bi-directional road traffic where topological changes happen *** to the high number of vehicles,it is essential to broadcast EMs to all vehicles to prevent traffic delays and collisions.A cluster-based EM transmitting technique is proposed in this *** urban VANETs,this paper pioneers the clustering of bi-directional road traffic for robust and efficient routing of *** this regard,this paper introduces a routing protocol,namely,the bi-directional urban routing protocol(BURP).In addition to the paths and relative locations of vehicles,BURP takes account of the distance parameter by using the Hamming distance function to determine the direction ofmotion of vehicles and communicates EMs through the cluster head(CH).Amodified k-medoids algorithm is presented for the clustering of bi-directional road traffic.A median method is presented for selecting CH to ensure the longrunning of a *** results show that BURP provides enhanced throughput,a maximized packet delivery ratio,low energy consumption,and network delay relative to eminent routing protocols.

关键词： Vehicular ad hoc networks bi-directional road traffic routing protocol emergency message broadcasting direction-based greedy forwarding

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Disaster Management Based on Biodiversity Conservation Using Remote Sensing Data Analysis Using Machine Learning Model

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Remote Sensing in Earth Systems Sciences 2025年第1期8卷 191-199页

作者： Pokkuluri, Kiran Sree Mounika, Talla Devi, N. Durga Kishore, D. Ratna Balakiruthiga, B. Krishna, B. Murali Department of Computer Science and Engineering Shri Vishnu Engineering College for Women Telangana Bhimavaram India Department of CSE-DS Mallareddy College of Engineering Hyderabad India Department of Computer Science and Engineering Aditya University Andhra Pradesh Surampalem India Dept of Information Technology Lakireddy Balireddy College of Engineering Mylavram Vijayawada India Department of Networking and Communications College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad India

Artificial intelligence (AI) applications in forestry as well as wildlife domains have become more feasible due to the advancements in data science and digital and satellite technologies. However, there is a serious global threat to biodiversity due to the rapid expansion of urban, agricultural, and development initiatives. Therefore, the effective monitoring, management, and preservation of biodiversity as well as forest resources may be facilitated by integration of cutting-edge methods like AI in disciplines of forests as well as biodiversity. This study suggests a novel approach to disaster management based on biodiversity protection that makes use of machine learning models and remote sensing image analysis. In this case, the data for disaster management has been gathered and processed for normalisation and smoothing. The processed image features have been segmented using active contour Gaussian Q- histogram equalisation model and feature extracted using probabilistic Bayesian fuzzy transfer NN. Experimental analysis is carried out based on parameters like random accuracy, average precision, sensitivity, AUC, and normalized co-efficient. The proposed technique attained average precision was 95%, sensitivity was 97%, random accuracy was 98%, and normalized coefficient was 94%, AUC of 96%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Biodiversity conservation Disaster management Machine learning model Q- histogram equalisation Remote sensing

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A Review of Key Elements for Underwater Wireless Sensor Networks

A Review of Key Elements for Underwater Wireless Sensor Netw...

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

作者： Ahmed, Amjed Abbas Najim, Ali Hamza Al-Dulaimi, Aymen Mohammed Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Aliesawi, Salah A. 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 College of Engineering Techniques Department of Communication Technical Engineering Al-Farahidi University 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 College of Computer and Information Technology Department of Computer Networking Systems University of Anbar Anbar Iraq

ISBN: (纸本)9798350369106

Underwater Wireless Sensor Networks (UWSNs) are emerging and have huge prospects since they have various applications in oceanography, environmental monitoring, and underwater communication. These networks contain low-cost submerged sensors that are mostly connected by way of acoustic media. Sensors are relatively new to underwater research, and thanks to recent technological development, they can now function at different depths. In this article, the author explores what UWSNs must do to operate smoothly by exploring the basic features that they must meet for further development. Real-time Underwater communication remains an open problem due to underwater acoustic channels important for undersea data acquisition, undersea navigation, and undersea remote sensing. To mitigate such challenges and in light of the use of new technologies, researchers seek to improve the reliability and reliability of UWSNs. Finally, there is great potential with UWSNs for investigating and exploiting the underwater environment by improving scenarios of different domains in line with subaqueous data and communications. © 2024 IEEE.

关键词： Wireless sensor networks

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Dynamic edge server placement in mobile edge computing using modified red deer optimization algorithm and Markov game theory

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Journal of Ambient Intelligence and Humanized Computing 2023年第9期14卷 12297-12315页

作者： Asghari, Ali Vahdani, Alireza Azgomi, Hossein Forestiero, Agostino Department of Computer Engineering Shafagh Institute of Higher Education Tonekabon Iran Department of Computer Engineering Islamic Azad University Rasht Branch Rasht Iran Institute for High-Performance Computing and Networking National Research Council of Italy c/o University of Calabria CS Rende Italy

Today, the development of intelligent mobile communication equipment, online applications such as online games, e-commerce, e-learning, and multimedia applications, and also the advent of the fifth generation of mobile communication networks have drawn mobile cloud services providers' special attention to this area. Cloud resources are brought to the edge of the network and adjacent to cloud users to increase the quality of the service provided. Proper placement of cloud resources reduces the resource access delay and balances the workload. Numerous studies have been conducted in this field. In most studies, it is assumed that the candidate location of the resources is fixed. The resources' area is also considered flat. Since the requested services of cloud users vary at different times of the day and in different geographical areas, the resources do not have the same efficiency during different times of the same day. For example, some administrative and business areas are active during the day, and at other times the demand decreases sharply. Thus, the mobility of cloud servers can be considered a suitable solution. In the proposed method, a two-stage static (SSP-RM) and dynamic (DSP-RM) model of cloud resource placement using Red deer (RD) and Markov game (MG) algorithms is introduced. Some cloud resources will be portable according to temporal and spatial requirements so that they can be transferred to different geographical areas according to different demands to increase their efficiency and distribute a more balanced workload on them while reducing latency. In the proposed method, by clustering the cloud resource deployment area and using the RD algorithm, the complexity of the cloud resource placement problem is reduced, and by using the Markov game model, the global convergence of resource deployment is obtained. Finally, dynamic cloud resource placement is performed using the Q-Learning (QL) algorithm. The results of experiments show that the proposed algor

关键词： computer games

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Dynamic and Private Recommendation System

Dynamic and Private Recommendation System

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2023 International Conference on Digital Applications, Transformation and Economy, ICDATE 2023

作者： Lo, Gee Yen Tan, Terence Peng Lian Curtin University Malaysia Computer Systems and Networking Miri Malaysia Curtin University Malaysia Department of Electrical & Computer Engineering Miri Malaysia

ISBN: (纸本)9798350310689

The amount of data that we retrieve and use every day is increasing rapidly. As data naturally exist in different data domains, the number of data domains that we retrieve and use every day has also increased as a result. As different recommendation systems are needed for different data domains, more and more recommendation systems will need to be built. Furthermore, users will lose their privacy as many recommendation systems collect information about their users. This paper aims to solve the aforementioned issues by creating a recommendation system that will work with any data domain and upholds the privacy of its users. The Dynamic Implementation Of Privacy Based Recommendation System Application is created in this paper. The objective of this thesis is achieved as the Dynamic Implementation Of Privacy Based Recommendation System Application developed in this paper upholds the privacy of its users as it only stores users' data in their device's local database and the application has the ability to adapt to different data domains. © 2023 IEEE.

关键词： Recommender systems

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Oppositional Harris Hawks Optimization with Deep Learning-Based Image Captioning

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computer Systems Science & engineering 2023年第1期44卷 579-593页

作者： V.R.Kavitha K.Nimala A.Beno K.C.Ramya Seifedine Kadry Byeong-Gwon Kang Yunyoung Nam Department of Computer Science and Engineering Prathyusha Engineering CollegeThiruvallur602025India Department of Networking and Communications SRM Institute of Science and TechnologyChennaiIndia Department of Electronics and Communication Engineering Dr.Sivanthi Aditanar College of EngineeringTiruchendur628215India Department of Electrical and Electronics Engineering Sri Krishna College of Engineering and TechnologyCoimbatore641008India Deparmtent of Applied Data Science Noroff University CollegeKristiansandNorway Department of Information and Communication Engineering Soonchunhyang UniversityAsanKorea Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Image Captioning is an emergent topic of research in the domain of artificial intelligence(AI).It utilizes an integration of computer Vision(CV)and Natural Language Processing(NLP)for generating the image *** use in several application areas namely recommendation in editing applications,utilization in virtual assistance,*** development of NLP and deep learning(DL)modelsfind useful to derive a bridge among the visual details and textual *** this view,this paper introduces an Oppositional Harris Hawks Optimization with Deep Learning based Image Captioning(OHHO-DLIC)*** OHHO-DLIC technique involves the design of distinct levels of ***,the feature extraction of the images is carried out by the use of EfficientNet ***,the image captioning is performed by bidirectional long short term memory(BiLSTM)model,comprising encoder as well as *** last,the oppositional Harris Hawks optimization(OHHO)based hyperparameter tuning process is performed for effectively adjusting the hyperparameter of the EfficientNet and BiLSTM *** experimental analysis of the OHHO-DLIC technique is carried out on the Flickr 8k Dataset and a comprehensive comparative analysis highlighted the better performance over the recent approaches.

关键词： Image captioning natural language processing artificial intelligence machine learning deep learning

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Evaluation of CyPACH: A Cyber Privacy Advisor Chatbot 2

Evaluation of CyPACH: A Cyber Privacy Advisor Chatbot

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2nd International Conference on computer System, Information Technology, and Electrical engineering, COSITE 2023

作者： Syamsuddin, Irfan Nur, Rini Irmawati Kasim, Kasim Raharjo, Muhammad Fajri Muchtar, Kahlil Department of Computer and Networking Engineering Politeknik Negeri Ujung Pandang Makassar90245 Indonesia Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh23111 Indonesia

ISBN: (纸本)9798350343069

Digital identity and assets have been increasingly more important in current digital society. Unfortunately, those who in charge in securing their own digital privacy in the form of digital identity and assets are often be the weakest link in digital security chain. Carelessness in maintaining the confidentiality of personal data repeatedly results in data leakage in the organization where the person works or even data leakage at the country level. Education and training are required to deal with the issue to enhance user awareness about cyber privacy. This paper proposes a Cyber Privacy Advisor in the form of chatbot to be learning trainer for those who want to achieve appropriate level of cyber privacy awareness. The chatbot is powered by Artificial Intelligence Scripting Language implemented by PandoraBot and AndroidJS to mimic human communications. At the end, two evaluation tools were applied to measure its technical correctness and content validity aspects which eventually indicate acceptable results. © 2023 IEEE.

关键词： Data privacy

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VANET Handoff from IEEE 80.11p to Cellular Network Based on Discharging with Handover Pronouncement Based on Software Defined Network (DHP-SDN) 22nd

VANET Handoff from IEEE 80.11p to Cellular Network Based on ...

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22nd International Conference on Hybrid Intelligent Systems, HIS 2022 and the 18th International Conference on Information Assurance and Security, IAS 2022

作者： Sarvavnan, M. Narayanan, R. Lakshmi Kavitha, K. Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Networking and Communications SRM Institute of Science and Technology Chennai India Department of Computer Science and Engineering Kongu Engineering College Erode India

ISBN: (纸本)9783031274084

In Vehicular Adhoc Network (VANET) is an emerging domain with high dynamic mobility and disrupted network in Discharging with Handover Pronouncement based on Software Defined Network (DHP-SDN) with advance predictive management tool described in this work for discharging of vehicle-to-infrastructure communication with Software Defined Network (SDN) architecture. Various parameters were addressed in research articles like maintaining connectivity, identifying appropriate intermediate node for carrying signal and transferring of data but in the proposed model SDN monitors the discharging signal based on the speediness, terrestrial location, nearby vehicle RSU from the vehicle which has cellular and IEEE 802.11p network boundary. SDN regulator computes when the due time is to settle on a choice, chooses whether it is appropriate or not have the vehicle to handoff from cell organization to the ahead IEEE 802.11p organization. The simulation results that using DHP-SDN method maintains the networking quality by reducing the load and traffic congestion. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Vehicles

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A novel feature selection approach with integrated feature sensitivity and feature correlation for improved prediction of heart disease

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Journal of Ambient Intelligence and Humanized Computing 2023年第9期14卷 12005-12019页

作者： Saranya, G. Pravin, A. Department of Computer Science and Engineering School of Computing Sathyabama Institute of Science and Technology Chennai600119 India Department of Networking and Communications School of Computing SRM Institute of Science and Technology Chennai603203 India

This paper presents a random forest-feature sensitivity and feature correlation (RF-FSFC) technique for enhanced heart disease prediction. The proposed methodology is implemented using the Cleveland heart disease dataset which comprises a total of 120 heart disease patient records. Data imputation was utilized for missing values, and min–max normalization was utilized for data transformation. We attempted to construct an RF-based classifier for coronary heart disease in this paper by combining feature sensitivity and correlation analysis. The sensitivity-based feature selection process ranks features according to their value in assessing CHD risk, and the feature correlation analysis phase analyses if there are any correlations between features. The heart disease prediction accuracy of 81.16% was obtained using the proposed RF-FSFCA technique by omitting five features (sex, hemoglobin, TD, CRF, and cirrhosis). When compared to the Naïve Bayes, decision tree, regression analysis, and support vector machine models, the proposed model offered a higher accuracy of 86.141% without omitting any features. It also offered sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) scores of 87.321%, 87.364%, 91.23, and 91.02 respectively. Experiment findings demonstrated that the proposed RF-FSFC approach significantly improves prediction accuracy as compared to other approaches that do not use the integrated Feature selection method. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Sensitivity analysis

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