International Journal of Computer Network and Information Security最新文献

Secure Data Storage and Retrieval over the Encrypted Cloud Computing 加密云计算上的安全数据存储和检索

International Journal of Computer Network and Information Security Pub Date : 2024-08-08 DOI: 10.5815/ijcnis.2024.04.04

Jaydip Kumar, Hemant Kumar, K. Singh, Vipin Saxena

{"title":"Secure Data Storage and Retrieval over the Encrypted Cloud Computing","authors":"Jaydip Kumar, Hemant Kumar, K. Singh, Vipin Saxena","doi":"10.5815/ijcnis.2024.04.04","DOIUrl":"https://doi.org/10.5815/ijcnis.2024.04.04","url":null,"abstract":"Information security in cloud computing refers to the protection of data items such as text, images, audios and video files. In the modern era, data size is increasing rapidly from gigabytes to terabytes or even petabytes, due to development of a significant amount of real-time data. The majority of data is stored in cloud computing environments and is sent or received over the internet. Due to the fact that cloud computing offers internet-based services, there are various attackers and illegal users over the internet who are consistently trying to gain access to user’s private data without the appropriate permission. Hackers frequently replace any fake data with actual data. As a result, data security has recently generated a lot of attention. To provide access rights of files, the cloud computing is only option for authorized user. To overcome from security threats, a security model is proposed for cloud computing to enhance the security of cloud data through the fingerprint authentication for access control and genetic algorithm is also used for encryption/decryption of cloud data. To search desired data from cloud, fuzzy encrypted keyword search technique is used. The encrypted keyword is stored in cloud storage using SHA256 hashing techniques. The proposed model minimizes the computation time and maximizes the security threats over the cloud. The computed results are presented in the form of figures and tables.","PeriodicalId":36488,"journal":{"name":"International Journal of Computer Network and Information Security","volume":"20 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Enhanced Process Scheduler Using Multi-Access Edge Computing in An IoT Network 物联网网络中使用多接入边缘计算的增强型进程调度器

International Journal of Computer Network and Information Security Pub Date : 2024-08-08 DOI: 10.5815/ijcnis.2024.04.09

P. S., S. Kuzhalvaimozhi, Bhuvan K., Ramitha R., Tanisha Machaiah M.

{"title":"An Enhanced Process Scheduler Using Multi-Access Edge Computing in An IoT Network","authors":"P. S., S. Kuzhalvaimozhi, Bhuvan K., Ramitha R., Tanisha Machaiah M.","doi":"10.5815/ijcnis.2024.04.09","DOIUrl":"https://doi.org/10.5815/ijcnis.2024.04.09","url":null,"abstract":"Multi-access edge computing has the ability to provide high bandwidth, and low latency, ensuring high efficiency in performing network operations and thus, it seems to be promising in the technical field. MEC allows processing and analysis of data at the network edges but it has finite number of resources which can be used. To overcome this restriction, a scheduling algorithm can be used by an orchestrator to deliver high quality services by choosing when and where each process should be executed. The scheduling algorithm must meet the expected outcome by utilizing lesser number of resources. This paper provides a scheduling algorithm containing two cooperative levels with an orchestrator layer acting at the center. The first level schedules local processes on the MEC servers and the next layer represents the orchestrator and allocates processes to nearby stations or cloud. Depending on latency and throughput, the processes are executed according to their priority. A resource optimization algorithm has also been proposed for extra performance. This offers a cost-efficient solution which provides good service availability. The proposed algorithm has a balanced wait time (Avg) and blocking percentage (Avg) of 2.37ms and 0.4 respectively. The blocking percentage is 1.65 times better than Shortest Job First Scheduling (SJFS) and 1.3 times better than Earliest Deadline First Scheduling (EDFS). The optimization algorithm can work on many kinds of network traffic models such as uniformly distributed and base stations with unbalanced loads.","PeriodicalId":36488,"journal":{"name":"International Journal of Computer Network and Information Security","volume":"18 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Universal On-board Neural Network System for Restoring Information in Case of Helicopter Turboshaft Engine Sensor Failure 用于在直升机涡轮轴发动机传感器故障时恢复信息的通用机载神经网络系统

International Journal of Computer Network and Information Security Pub Date : 2024-08-08 DOI: 10.5815/ijcnis.2024.04.05

Serhii Vladov, Ruslan Yakovliev, Victoria Vysotska, Dmytro Uhryn, Yuriy Ushenko

{"title":"Universal On-board Neural Network System for Restoring Information in Case of Helicopter Turboshaft Engine Sensor Failure","authors":"Serhii Vladov, Ruslan Yakovliev, Victoria Vysotska, Dmytro Uhryn, Yuriy Ushenko","doi":"10.5815/ijcnis.2024.04.05","DOIUrl":"https://doi.org/10.5815/ijcnis.2024.04.05","url":null,"abstract":"This work focuses on developing a universal onboard neural network system for restoring information when helicopter turboshaft engine sensors fail. A mathematical task was formulated to determine the occurrence and location of these sensor failures using a multi-class Bayesian classification model that incorporates prior knowledge and updates probabilities with new data. The Bayesian approach was employed for identifying and localizing sensor failures, utilizing a Bayesian neural network with a 4–6–3 structure as the core of the developed system. A training algorithm for the Bayesian neural network was created, which estimates the prior distribution of network parameters through variational approximation, maximizes the evidence lower bound of direct likelihood instead, and updates parameters by calculating gradients of the log-likelihood and evidence lower bound, while adding regularization terms for warnings, distributions, and uncertainty estimates to interpret results. This approach ensures balanced data handling, effective training (achieving nearly 100% accuracy on both training and validation sets), and improved model understanding (with training losses not exceeding 2.5%). An example is provided that demonstrates solving the information restoration task in the event of a gas-generator rotor r.p.m. sensor failure in the TV3-117 helicopter turboshaft engine. The developed onboard neural network system implementing feasibility on a helicopter using the neuro-processor Intel Neural Compute Stick 2 has been analytically proven.","PeriodicalId":36488,"journal":{"name":"International Journal of Computer Network and Information Security","volume":"17 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

BSHOA: Energy Efficient Task Scheduling in Cloud-fog Environment BSHOA：云雾环境中的高能效任务调度

International Journal of Computer Network and Information Security Pub Date : 2024-08-08 DOI: 10.5815/ijcnis.2024.04.06

Santhosh Kumar Medishetti, Ganesh Reddy

{"title":"BSHOA: Energy Efficient Task Scheduling in Cloud-fog Environment","authors":"Santhosh Kumar Medishetti, Ganesh Reddy","doi":"10.5815/ijcnis.2024.04.06","DOIUrl":"https://doi.org/10.5815/ijcnis.2024.04.06","url":null,"abstract":"Cloud-fog computing frameworks are innovative frameworks that have been designed to improve the present Internet of Things (IoT) infrastructures. The major limitation for IoT applications is the availability of ongoing energy sources for fog computing servers because transmitting the enormous amount of data generated by IoT devices will increase network bandwidth overhead and slow down the responsive time. Therefore, in this paper, the Butterfly Spotted Hyena Optimization algorithm (BSHOA) is proposed to find an alternative energy-aware task scheduling technique for IoT requests in a cloud-fog environment. In this hybrid BSHOA algorithm, the Butterfly optimization algorithm (BOA) is combined with Spotted Hyena Optimization (SHO) to enhance the global and local search behavior of BOA in the process of finding the optimal solution for the problem under consideration. To show the applicability and efficiency of the presented BSHOA approach, experiments will be done on real workloads taken from the Parallel Workload Archive comprising NASA Ames iPSC/860 and HP2CN (High-Performance Computing Center North) workloads. The investigation findings indicate that BSHOA has a strong capacity for dealing with the task scheduling issue and outperforms other approaches in terms of performance parameters including throughput, energy usage, and makespan time.","PeriodicalId":36488,"journal":{"name":"International Journal of Computer Network and Information Security","volume":"52 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141928029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Targeted Attacks Detection and Security Intruders Identification in the Cyber Space 网络空间定向攻击检测和安全入侵者识别

International Journal of Computer Network and Information Security Pub Date : 2024-08-08 DOI: 10.5815/ijcnis.2024.04.10

Z. Avkurova, Sergiy Gnatyuk, Bayan Abduraimova, Kaiyrbek Makulov

{"title":"Targeted Attacks Detection and Security Intruders Identification in the Cyber Space","authors":"Z. Avkurova, Sergiy Gnatyuk, Bayan Abduraimova, Kaiyrbek Makulov","doi":"10.5815/ijcnis.2024.04.10","DOIUrl":"https://doi.org/10.5815/ijcnis.2024.04.10","url":null,"abstract":"The number of new cybersecurity threats and opportunities is increasing over time, as well as the amount of information that is generated, processed, stored and transmitted using ICTs. Particularly sensitive are the objects of critical infrastructure of the state, which include the mining industry, transport, telecommunications, the banking system, etc. From these positions, the development of systems for detecting attacks and identifying intruders (including the critical infrastructure of the state) is an important and relevant scientific task, which determined the tasks of this article. The paper identifies the main factors influencing the choice of the most effective method for calculating the importance coefficients to increase the objectivity and simplicity of expert assessment of security events in cyberspace. Also, a methodology for conducting an experimental study was developed, in which the goals and objectives of the experiment, input and output parameters, the hypothesis and research criteria, the sufficiency of experimental objects and the sequence of necessary actions were determined. The conducted experimental study confirmed the adequacy of the models proposed in the work, as well as the ability of the method and system created on their basis to detect targeted attacks and identify intruders in cyberspace at an early stage, which is not included in the functionality of modern intrusion detection and prevention systems.","PeriodicalId":36488,"journal":{"name":"International Journal of Computer Network and Information Security","volume":"56 50","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141928930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Attack Modeling and Security Analysis Using Machine Learning Algorithms Enabled with Augmented Reality and Virtual Reality 利用增强现实和虚拟现实技术的机器学习算法进行攻击建模和安全分析

International Journal of Computer Network and Information Security Pub Date : 2024-08-08 DOI: 10.5815/ijcnis.2024.04.08

Momina Mushtaq, Rakesh Kumar Jha, Manish Sabraj, Shubha Jain

{"title":"Attack Modeling and Security Analysis Using Machine Learning Algorithms Enabled with Augmented Reality and Virtual Reality","authors":"Momina Mushtaq, Rakesh Kumar Jha, Manish Sabraj, Shubha Jain","doi":"10.5815/ijcnis.2024.04.08","DOIUrl":"https://doi.org/10.5815/ijcnis.2024.04.08","url":null,"abstract":"Augmented Reality (AR) and Virtual Reality (VR) are innovative technologies that are experiencing a widespread recognition. These technologies possess the capability to transform and redefine our interactions with the surrounding environment. However, as these technologies spread, they also introduce new security challenges. In this paper, we discuss the security challenges posed by Augmented reality and Virtual Reality, and propose a Machine Learning-based approach to address these challenges. We also discuss how Machine Learning can be used to detect and prevent attacks in Augmented reality and Virtual Reality. By leveraging the power of Machine Learning algorithms, we aim to bolster the security defences of Augmented reality and Virtual Reality systems. To accomplish this, we have conducted a comprehensive evaluation of various Machine Learning algorithms, meticulously analysing their performance and efficacy in enhancing security. Our results show that Machine Learning can be an effective way to improve the security of Augmented reality and virtual reality systems.","PeriodicalId":36488,"journal":{"name":"International Journal of Computer Network and Information Security","volume":"42 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141929415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Chaotic Map based Random Binary Key Sequence Generation 基于混沌图的随机二进制密钥序列生成

International Journal of Computer Network and Information Security Pub Date : 2024-08-08 DOI: 10.5815/ijcnis.2024.04.07

Vishwas C. G. M., R. Kunte

{"title":"Chaotic Map based Random Binary Key Sequence Generation","authors":"Vishwas C. G. M., R. Kunte","doi":"10.5815/ijcnis.2024.04.07","DOIUrl":"https://doi.org/10.5815/ijcnis.2024.04.07","url":null,"abstract":"Image encryption is an efficient mechanism by which digital images can be secured during transmission over communication in which key sequence generation plays a vital role. The proposed system consists of stages such as the generation of four chaotic maps, conversion of generated maps to binary vectors, rotation of Linear Feedback Shift Register (LFSR), and selection of generated binary chaotic key sequences from the generated key pool. The novelty of this implementation is to generate binary sequences by selecting from all four chaotic maps viz., Tent, Logistic, Henon, and Arnold Cat map (ACM). LFSR selects chaotic maps to produce random key sequences. Five primitive polynomials of degrees 5, 6, 7, and 8 are considered for the generation of key sequences. Each primitive polynomial generates 61 binary key sequences stored in a binary key pool. All 61 binary key sequences generated are submitted for the NIST and FIPS tests. Performance analysis is carried out of the generated binary key sequences. From the obtained results, it can be concluded that the binary key sequences are random and unpredictable and have a large key space based on the individual and combination of key sequences. Also, the generated binary key sequences can be efficiently utilized for the encryption of digital images.","PeriodicalId":36488,"journal":{"name":"International Journal of Computer Network and Information Security","volume":"23 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141928124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quality of Experience Improvement and Service Time Optimization through Dynamic Computation Offloading Algorithms in Multi-access Edge Computing Networks 通过多接入边缘计算网络中的动态计算卸载算法提高体验质量和优化服务时间

International Journal of Computer Network and Information Security Pub Date : 2024-08-08 DOI: 10.5815/ijcnis.2024.04.01

Marouane Myyara, Oussama Lagnfdi, A. Darif, Abderrazak Farchane

{"title":"Quality of Experience Improvement and Service Time Optimization through Dynamic Computation Offloading Algorithms in Multi-access Edge Computing Networks","authors":"Marouane Myyara, Oussama Lagnfdi, A. Darif, Abderrazak Farchane","doi":"10.5815/ijcnis.2024.04.01","DOIUrl":"https://doi.org/10.5815/ijcnis.2024.04.01","url":null,"abstract":"Multi-access Edge Computing optimizes computation in proximity to smart mobile devices, addressing the limitations of devices with insufficient capabilities. In scenarios featuring multiple compute-intensive and delay-sensitive applications, computation offloading becomes essential. The objective of this research is to enhance user experience, minimize service time, and balance workloads while optimizing computation offloading and resource utilization. In this study, we introduce dynamic computation offloading algorithms that concurrently minimize service time and maximize the quality of experience. These algorithms take into account task and resource characteristics to determine the optimal execution location based on evaluated metrics. To assess the positive impact of the proposed algorithms, we employed the Edgecloudsim simulator, offering a realistic assessment of a Multi-access Edge Computing system. Simulation results showcase the superiority of our dynamic computation offloading algorithm compared to alternatives, achieving enhanced quality of experience and minimal service time. The findings underscore the effectiveness of the proposed algorithm and its potential to enhance mobile application performance. The comprehensive evaluation provides insights into the robustness and practical applicability of the proposed approach, positioning it as a valuable solution in the context of MEC networks. This research contributes to the ongoing efforts in advancing computation offloading strategies for improved performance in edge computing environments.","PeriodicalId":36488,"journal":{"name":"International Journal of Computer Network and Information Security","volume":"58 35","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141928905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cascaded Machine Learning Approach with Data Augmentation for Intrusion Detection System 入侵检测系统的级联机器学习方法与数据增强

International Journal of Computer Network and Information Security Pub Date : 2024-08-08 DOI: 10.5815/ijcnis.2024.04.02

Argha Chandra Dhar, Arna Roy, M. Akhand, Md Abdus Samad Kamal, Kou Yamada

{"title":"Cascaded Machine Learning Approach with Data Augmentation for Intrusion Detection System","authors":"Argha Chandra Dhar, Arna Roy, M. Akhand, Md Abdus Samad Kamal, Kou Yamada","doi":"10.5815/ijcnis.2024.04.02","DOIUrl":"https://doi.org/10.5815/ijcnis.2024.04.02","url":null,"abstract":"Cybersecurity has received significant attention globally, with the ever-continuing expansion of internet usage, due to growing trends and adverse impacts of cybercrimes, which include disrupting businesses, corrupting or altering sensitive data, stealing or exposing information, and illegally accessing a computer network. As a popular way, different kinds of firewalls, antivirus systems, and Intrusion Detection Systems (IDS) have been introduced to protect a network from such attacks. Recently, Machine Learning (ML), including Deep Learning (DL) based autonomous systems, have been state-of-the-art in cyber security, along with their drastic growth and superior performance. This study aims to develop a novel IDS system that gives more attention to classifying attack cases correctly and categorizes attacks into subclass levels by proposing a two-step process with a cascaded framework. The proposed framework recognizes the attacks using one ML model and classifies them into subclass levels using the other ML model in successive operations. The most challenging part is to train both models with unbalanced cases of attacks and non-attacks in the datasets, which is overcome by proposing a data augmentation technique. Precisely, limited attack samples of the dataset are augmented in the training set to learn the attack cases properly. Finally, the proposed framework is implemented with NN, the most popular ML model, and evaluated with the NSL-KDD dataset by conducting a rigorous analysis of each subclass emphasizing the major attack class. The proficiency of the proposed cascaded approach with data augmentation is compared with the other three models: the cascaded model without data augmentation and the standard single NN model with and without the data augmentation technique. Experimental results on the NSL-KDD dataset have revealed the proposed method as an effective IDS system and outperformed existing state-of-the-art ML models.","PeriodicalId":36488,"journal":{"name":"International Journal of Computer Network and Information Security","volume":"59 47","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141929042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Parameter Estimation of Cellular Communication Systems Models in Computational MATLAB Environment: A Systematic Solver-based Numerical Optimization Approaches 计算 MATLAB 环境中蜂窝通信系统模型的参数估计：基于求解器的系统数值优化方法

International Journal of Computer Network and Information Security Pub Date : 2024-06-08 DOI: 10.5815/ijcnis.2024.03.06

J. Isabona, Sayo A. Akinwumi, Theophilus E. Arijaje, Odesanya Ituabhor, A. Imoize

{"title":"Parameter Estimation of Cellular Communication Systems Models in Computational MATLAB Environment: A Systematic Solver-based Numerical Optimization Approaches","authors":"J. Isabona, Sayo A. Akinwumi, Theophilus E. Arijaje, Odesanya Ituabhor, A. Imoize","doi":"10.5815/ijcnis.2024.03.06","DOIUrl":"https://doi.org/10.5815/ijcnis.2024.03.06","url":null,"abstract":"Model-based parameter estimation, identification, and optimisation play a dominant role in many aspects of physical and operational processes in applied sciences, engineering, and other related disciplines. The intricate task involves engaging and fitting the most appropriate parametric model with nonlinear or linear features to experimental field datasets priori to selecting the best optimisation algorithm with the best configuration. Thus, the task is usually geared towards solving a clear optimsation problem. In this paper, a systematic-stepwise approach has been employed to review and benchmark six numerical-based optimization algorithms in MATLAB computational Environment. The algorithms include the Gradient Descent (GRA), Levenberg-Marguardt (LEM), Quasi-Newton (QAN), Gauss-Newton (GUN), Nelda-Meald (NEM), and Trust-Region-Dogleg (TRD). This has been accomplished by engaging them to solve an intricate radio frequency propagation modelling and parametric estimation in connection with practical spatial signal data. The spatial signal data were obtained via real-time field drive test conducted around six eNodeBs transmitters, with case studies taken from different terrains where 4G LTE transmitters are operational. Accordingly, three criteria in connection with rate of convergence Results show that the approximate hessian-based QAN algorithm, followed by the LEM algorithm yielded the best results in optimizing and estimating the RF propagation models parameters. The resultant approach and output of this paper will be of countless assets in assisting the end-users to select the most preferable optimization algorithm to handle their respective intricate problems.","PeriodicalId":36488,"journal":{"name":"International Journal of Computer Network and Information Security","volume":" 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141370390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0