Pub Date : 2022-11-01DOI: 10.1109/ITED56637.2022.10051478
Hakeem Babalola Akande, O. Abikoye, O. Akande, R. Jimoh
Metaheuristic algorithms such as Ant Colony Optimization (ACO) algorithm and Bat Optimization Algorithm (BOA) have been widely employed in solving different optimization problems in several fields. ACO is modelled based on the social behaviour of ants that look for appropriate answers to a given optimization issue by recasting it as the case of locating the least expensive path on a weighted graph. A set of parameters linked to graph components (either nodes or edges) whose values are changed by the ants during runtime constitute the pheromone model, which biases the stochastic solution generation process. However, the effectiveness of ACO declines as the quantity of packets rises, making them ineffective for reducing traffic congestion. As more packets are transmitted, their strength decreases, causing packet congestion, rendering them useless for reducing packet traffic congestion. On the contrary, BOA which was modelled after the behavior of bats has also been employed in fixing network routing issues by listening to every sound in a space and taking note of what is going on around it. In order to further improve ACO algorithm and decrease packet traffic congestion, packet loss, and the time it takes a packet to reach its destination in a network system, this study employs the strength of BOA. Results obtained revealed the prowess of BOA in improving the performance of ACO for network packet routing.
{"title":"Improving Optimization Prowess of Ant Colony Algorithm Using Bat Inspired Algorithm","authors":"Hakeem Babalola Akande, O. Abikoye, O. Akande, R. Jimoh","doi":"10.1109/ITED56637.2022.10051478","DOIUrl":"https://doi.org/10.1109/ITED56637.2022.10051478","url":null,"abstract":"Metaheuristic algorithms such as Ant Colony Optimization (ACO) algorithm and Bat Optimization Algorithm (BOA) have been widely employed in solving different optimization problems in several fields. ACO is modelled based on the social behaviour of ants that look for appropriate answers to a given optimization issue by recasting it as the case of locating the least expensive path on a weighted graph. A set of parameters linked to graph components (either nodes or edges) whose values are changed by the ants during runtime constitute the pheromone model, which biases the stochastic solution generation process. However, the effectiveness of ACO declines as the quantity of packets rises, making them ineffective for reducing traffic congestion. As more packets are transmitted, their strength decreases, causing packet congestion, rendering them useless for reducing packet traffic congestion. On the contrary, BOA which was modelled after the behavior of bats has also been employed in fixing network routing issues by listening to every sound in a space and taking note of what is going on around it. In order to further improve ACO algorithm and decrease packet traffic congestion, packet loss, and the time it takes a packet to reach its destination in a network system, this study employs the strength of BOA. Results obtained revealed the prowess of BOA in improving the performance of ACO for network packet routing.","PeriodicalId":246041,"journal":{"name":"2022 5th Information Technology for Education and Development (ITED)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131237337","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}
Pub Date : 2022-11-01DOI: 10.1109/ITED56637.2022.10051479
J. Wejin, J. Badejo, Oluranti Jonathan, F. Dahunsi
Since its inception, the Internet has experienced tremendous speed and functionality improvements. Among these developments are innovative approaches such as the design and deployment of Internet Protocol version six (IPv6) and the continuous modification of TCP. New transport protocols like Stream Communication Transport Protocol (SCTP) and Multipath TCP (MPTCP), which can use multiple data paths, have been developed to overcome the IP-coupled challenge in TCP. However, given the difficulties of packet modifiers over the Internet that prevent the deployment of newly proposed protocols, e.g., SCTP, a UDP innovative approach with QUIC (Quick UDP Internet Connection) has been put forward as an alternative. QUIC reduces the connection establishment complexity in TCP and its variants, high security, stream multiplexing, and pluggable congestion control. Motivated by the gains and acceptability of MPTCP, Multipath QUIC has been developed to enable multipath transmission in QUIC. While several researchers have reviewed the progress of improvement and application of MPTCP, the review on MPQUIC improvement is limited. To breach the gap, this paper provides a brief survey on the practical application and progress of MPQUIC in data communication. We first review the fundamentals of multipath transport protocols. We then provide details on the design of QUIC and MPQUIC. Based on the articles reviewed, we looked at the various applications of MPQUIC, identifying the application domain, tools used, and evaluation parameters. Finally, we highlighted the open research issues and directions for further investigations.
{"title":"A Brief Survey on the Experimental Application of MPQUIC Protocol in Data Communication","authors":"J. Wejin, J. Badejo, Oluranti Jonathan, F. Dahunsi","doi":"10.1109/ITED56637.2022.10051479","DOIUrl":"https://doi.org/10.1109/ITED56637.2022.10051479","url":null,"abstract":"Since its inception, the Internet has experienced tremendous speed and functionality improvements. Among these developments are innovative approaches such as the design and deployment of Internet Protocol version six (IPv6) and the continuous modification of TCP. New transport protocols like Stream Communication Transport Protocol (SCTP) and Multipath TCP (MPTCP), which can use multiple data paths, have been developed to overcome the IP-coupled challenge in TCP. However, given the difficulties of packet modifiers over the Internet that prevent the deployment of newly proposed protocols, e.g., SCTP, a UDP innovative approach with QUIC (Quick UDP Internet Connection) has been put forward as an alternative. QUIC reduces the connection establishment complexity in TCP and its variants, high security, stream multiplexing, and pluggable congestion control. Motivated by the gains and acceptability of MPTCP, Multipath QUIC has been developed to enable multipath transmission in QUIC. While several researchers have reviewed the progress of improvement and application of MPTCP, the review on MPQUIC improvement is limited. To breach the gap, this paper provides a brief survey on the practical application and progress of MPQUIC in data communication. We first review the fundamentals of multipath transport protocols. We then provide details on the design of QUIC and MPQUIC. Based on the articles reviewed, we looked at the various applications of MPQUIC, identifying the application domain, tools used, and evaluation parameters. Finally, we highlighted the open research issues and directions for further investigations.","PeriodicalId":246041,"journal":{"name":"2022 5th Information Technology for Education and Development (ITED)","volume":"1074 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132847853","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}
Pub Date : 2022-11-01DOI: 10.1109/ITED56637.2022.10051208
Temitayo Balogun, Rilwan Saliu, S. Faluyi, Kofoworola Fapohunda
In recent years, diabetic retinopathy (DR), particularly in the elderly, has gained widespread recognition as a cause of blindness. The DR, which comes in a variety of forms and also has a variety of causes, is easily curable with early detection. Early detection of DR is challenging when manual medical approaches are used, and results are frequently inaccurate despite how long they take to complete. Therefore, a better approach to DR detection and prediction is required. Therefore, the purpose of this paper is to detect and classify diabetic retinopathy in patients using deep learning and compare different machine learning models to determine the one that performs best. The models employed are Convolutional Neural Network (CNN) that uses a four-layer VGG net plus an additional neural network to make it a custom five-layer network, K Nearest Neighbour (KNN) and Support Vector Machine (SVM). The IDRID which is the Indian Diabetic Retinopathy Image Dataset is where the dataset was acquired. When compared to other deep learning systems like KNN and SVM, which had an accuracy of 86% and 66% respectively, CNN attained an accuracy of 92%.
{"title":"Comparative analysis of deep learning models for the detection and classification of Diabetes Retinopathy","authors":"Temitayo Balogun, Rilwan Saliu, S. Faluyi, Kofoworola Fapohunda","doi":"10.1109/ITED56637.2022.10051208","DOIUrl":"https://doi.org/10.1109/ITED56637.2022.10051208","url":null,"abstract":"In recent years, diabetic retinopathy (DR), particularly in the elderly, has gained widespread recognition as a cause of blindness. The DR, which comes in a variety of forms and also has a variety of causes, is easily curable with early detection. Early detection of DR is challenging when manual medical approaches are used, and results are frequently inaccurate despite how long they take to complete. Therefore, a better approach to DR detection and prediction is required. Therefore, the purpose of this paper is to detect and classify diabetic retinopathy in patients using deep learning and compare different machine learning models to determine the one that performs best. The models employed are Convolutional Neural Network (CNN) that uses a four-layer VGG net plus an additional neural network to make it a custom five-layer network, K Nearest Neighbour (KNN) and Support Vector Machine (SVM). The IDRID which is the Indian Diabetic Retinopathy Image Dataset is where the dataset was acquired. When compared to other deep learning systems like KNN and SVM, which had an accuracy of 86% and 66% respectively, CNN attained an accuracy of 92%.","PeriodicalId":246041,"journal":{"name":"2022 5th Information Technology for Education and Development (ITED)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129514959","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}
Pub Date : 2022-11-01DOI: 10.1109/ITED56637.2022.10051407
S. Ilesanmi, Agbaegbu JonhBosco, W. Ahiara, Janet Akiode, Uchenna H. Udeani, T. Olaleye, Olalekan A. Okewale
The trio of data, technology, and man constitutes a formidable tripartite synergy towards enhancing health informatics through data science. This avails state-of-the-arts which employ tools like the interquartile range, probability density function, predictive analytics etc. the opportunity of medical data evaluation for pathology and medical diagnosis purposes. However, such evaluations are seldom carried out on medical image embedding acquired through transfer learning. This study therefore employs the SqueezeNet deep embedder on computerized tomography scan signals for feature extraction of pneumonia attributes. An ensemble statistical tool is used for the evaluation after the feature selection of significant attributes by analysis of variance. To answer research question that seeks to discover most significant data feature, experimental result returns an external data attribute as one with the most discriminative information for pneumonia detection. An interquartile range of 40000 to 240000 with a dispersed probability density function in the second quartile also indicates a positive case of pneumonia medical condition
{"title":"An ensemble statistical evaluation of medical image embedding with SqueezeNet neural network","authors":"S. Ilesanmi, Agbaegbu JonhBosco, W. Ahiara, Janet Akiode, Uchenna H. Udeani, T. Olaleye, Olalekan A. Okewale","doi":"10.1109/ITED56637.2022.10051407","DOIUrl":"https://doi.org/10.1109/ITED56637.2022.10051407","url":null,"abstract":"The trio of data, technology, and man constitutes a formidable tripartite synergy towards enhancing health informatics through data science. This avails state-of-the-arts which employ tools like the interquartile range, probability density function, predictive analytics etc. the opportunity of medical data evaluation for pathology and medical diagnosis purposes. However, such evaluations are seldom carried out on medical image embedding acquired through transfer learning. This study therefore employs the SqueezeNet deep embedder on computerized tomography scan signals for feature extraction of pneumonia attributes. An ensemble statistical tool is used for the evaluation after the feature selection of significant attributes by analysis of variance. To answer research question that seeks to discover most significant data feature, experimental result returns an external data attribute as one with the most discriminative information for pneumonia detection. An interquartile range of 40000 to 240000 with a dispersed probability density function in the second quartile also indicates a positive case of pneumonia medical condition","PeriodicalId":246041,"journal":{"name":"2022 5th Information Technology for Education and Development (ITED)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131016883","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}
Pub Date : 2022-11-01DOI: 10.1109/ITED56637.2022.10051598
J. Eneh, S. Nwafor, E. C. Nnadozie, O. Ani
An aerial manipulator is a highly coupled and unstable complicated system. The movement of the robot manipulator will influence the stability of the quadcopter. This paper presents adaptive fuzzy sliding mode control (AFSMC) to improve the stability of the aerial manipulator. The proposed control strategy employs fuzzy compensation with regards to friction to improve tracking performance with fuzzy set rules. Simulation results indicate that the proposed AFSMC has minimum tracking error compared to sliding mode control (SMC) and PID controllers.
{"title":"Adaptive Fuzzy Sliding Mode Control for an Aerial Manipulator as a Payload on a Quadcopter","authors":"J. Eneh, S. Nwafor, E. C. Nnadozie, O. Ani","doi":"10.1109/ITED56637.2022.10051598","DOIUrl":"https://doi.org/10.1109/ITED56637.2022.10051598","url":null,"abstract":"An aerial manipulator is a highly coupled and unstable complicated system. The movement of the robot manipulator will influence the stability of the quadcopter. This paper presents adaptive fuzzy sliding mode control (AFSMC) to improve the stability of the aerial manipulator. The proposed control strategy employs fuzzy compensation with regards to friction to improve tracking performance with fuzzy set rules. Simulation results indicate that the proposed AFSMC has minimum tracking error compared to sliding mode control (SMC) and PID controllers.","PeriodicalId":246041,"journal":{"name":"2022 5th Information Technology for Education and Development (ITED)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134458818","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}
Pub Date : 2022-11-01DOI: 10.1109/ITED56637.2022.10051182
M. M. Abubakar, A. Z. Umar, M. Abubakar
Personal data and privacy protection has been a hot topic of discussion due to the increasing impact of computing technologies in everyday life. In recent years, there have been reports of breaches of personal data either from organizations that collected it or from mischievous third parties. The global responses against the breaches have been the enactment of various policies and regulations to protect personal data against all forms of potential abuses. Nigeria Data Protection Regulation was also issued as the regulatory framework for personal data and privacy protection on Nigerian soil. This paper, aimed at analysing the state of compliance of Ministries, Departments, and Agencies with the regulatory framework. An online questionnaire was designed and hosted on Google Forms. The link to the questionnaire was sent to 110 staff, selected based on convenience, and representing various Ministries, Departments, and Agencies. The results have shown that about 70% of the organizations were aware of the provision of Nigeria Data Protection Regulation but only 34% indicated that they started the implementation. Nonetheless, about 45% Ministries, Departments, and Agencies completed the preparatory stage of compliance as they indicated that they have conducted detailed audits on their organizational operations to determine the changes and the new practices required to comply with the Nigeria Data Protection Regulation. The surveyed organizations indicated 37% to 60% compliance with other components of Nigeria Data Protection Regulation. The paper concluded that more advocacy and enforcement are required to speed up compliance with regulations.
{"title":"Personal Data and Privacy Protection Regulations: State of compliance with Nigeria Data Protection Regulations (NDPR) in Ministries, Departments, and Agencies (MDAs)","authors":"M. M. Abubakar, A. Z. Umar, M. Abubakar","doi":"10.1109/ITED56637.2022.10051182","DOIUrl":"https://doi.org/10.1109/ITED56637.2022.10051182","url":null,"abstract":"Personal data and privacy protection has been a hot topic of discussion due to the increasing impact of computing technologies in everyday life. In recent years, there have been reports of breaches of personal data either from organizations that collected it or from mischievous third parties. The global responses against the breaches have been the enactment of various policies and regulations to protect personal data against all forms of potential abuses. Nigeria Data Protection Regulation was also issued as the regulatory framework for personal data and privacy protection on Nigerian soil. This paper, aimed at analysing the state of compliance of Ministries, Departments, and Agencies with the regulatory framework. An online questionnaire was designed and hosted on Google Forms. The link to the questionnaire was sent to 110 staff, selected based on convenience, and representing various Ministries, Departments, and Agencies. The results have shown that about 70% of the organizations were aware of the provision of Nigeria Data Protection Regulation but only 34% indicated that they started the implementation. Nonetheless, about 45% Ministries, Departments, and Agencies completed the preparatory stage of compliance as they indicated that they have conducted detailed audits on their organizational operations to determine the changes and the new practices required to comply with the Nigeria Data Protection Regulation. The surveyed organizations indicated 37% to 60% compliance with other components of Nigeria Data Protection Regulation. The paper concluded that more advocacy and enforcement are required to speed up compliance with regulations.","PeriodicalId":246041,"journal":{"name":"2022 5th Information Technology for Education and Development (ITED)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134573943","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}
Pub Date : 2022-11-01DOI: 10.1109/ITED56637.2022.10051439
O. Awoniran, M. Oyelami, Rhoda Ikono, R. Famutimi, T. Famutimi
The need for early detection of diabetes mellitus has led to the development of various intelligent systems using machine learning and artificial intelligence for the recognition of the presence of the disease. However, most of the techniques have yielded a comparatively lower accuracy. This research applied data science techniques to a dataset of diabetes mellitus to improve the accuracy of the prediction of the disease. This was achieved by pre-processing the data with dummy categories and applying principal components analysis for reduced dimensionality. Support vector machine, random forest classifier, and deep neural networks were then used to train the system. Support vector machine, random forest classifier, and deep neural networks yielded accuracies of 0.76, 0.77, and 0.89 respectively. Correspondingly, deep neural networks yielded the highest accuracy. The study concluded that better pre-processing will improve the accuracy of machine learning algorithms in the prediction of diabetes mellitus.
{"title":"A Machine Learning Technique for Detection of Diabetes Mellitus","authors":"O. Awoniran, M. Oyelami, Rhoda Ikono, R. Famutimi, T. Famutimi","doi":"10.1109/ITED56637.2022.10051439","DOIUrl":"https://doi.org/10.1109/ITED56637.2022.10051439","url":null,"abstract":"The need for early detection of diabetes mellitus has led to the development of various intelligent systems using machine learning and artificial intelligence for the recognition of the presence of the disease. However, most of the techniques have yielded a comparatively lower accuracy. This research applied data science techniques to a dataset of diabetes mellitus to improve the accuracy of the prediction of the disease. This was achieved by pre-processing the data with dummy categories and applying principal components analysis for reduced dimensionality. Support vector machine, random forest classifier, and deep neural networks were then used to train the system. Support vector machine, random forest classifier, and deep neural networks yielded accuracies of 0.76, 0.77, and 0.89 respectively. Correspondingly, deep neural networks yielded the highest accuracy. The study concluded that better pre-processing will improve the accuracy of machine learning algorithms in the prediction of diabetes mellitus.","PeriodicalId":246041,"journal":{"name":"2022 5th Information Technology for Education and Development (ITED)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114569534","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}
Pub Date : 2022-11-01DOI: 10.1109/ITED56637.2022.10051180
Abbas Nna Halima, Mohammed D. Abdulmalik, Solomon Adelowo Adepoju, E. F. Aminu
Recently digital watermarking techniques played an essential role in protecting and authenticating the copyright of multimedia content in a cloud. Based on the literature, there are several digital watermarking techniques used for data protection in cloud computing. However, each of these techniques has its own limitations such as high levels of piracy, theft, and unauthorized distribution of multimedia content. This Survey employs a content-based analysis approach to investigate the watermarking techniques that are more secure, imperceptible, and robust against various kinds of multimedia attacks. The survey shows that the hybridization of watermarking techniques and feature descriptors is more efficient in comparison to a single watermarking technique. This research work concludes that the hybridization technique and use of descriptors are more secure.
{"title":"A Survey of Digital Watermarking Techniques for Data Protection in Cloud Computing","authors":"Abbas Nna Halima, Mohammed D. Abdulmalik, Solomon Adelowo Adepoju, E. F. Aminu","doi":"10.1109/ITED56637.2022.10051180","DOIUrl":"https://doi.org/10.1109/ITED56637.2022.10051180","url":null,"abstract":"Recently digital watermarking techniques played an essential role in protecting and authenticating the copyright of multimedia content in a cloud. Based on the literature, there are several digital watermarking techniques used for data protection in cloud computing. However, each of these techniques has its own limitations such as high levels of piracy, theft, and unauthorized distribution of multimedia content. This Survey employs a content-based analysis approach to investigate the watermarking techniques that are more secure, imperceptible, and robust against various kinds of multimedia attacks. The survey shows that the hybridization of watermarking techniques and feature descriptors is more efficient in comparison to a single watermarking technique. This research work concludes that the hybridization technique and use of descriptors are more secure.","PeriodicalId":246041,"journal":{"name":"2022 5th Information Technology for Education and Development (ITED)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122816605","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}
Pub Date : 2022-11-01DOI: 10.1109/ITED56637.2022.10051615
Wilson Nwankwo, Anazia E. Kizito, Wifred Adigwe, C. Nwankwo, Francis Uwadia, Samaila Mande
Digital forensics is intended to unearth evidence from concluded activities in the cyberspace and such workflow is data-intensive. A typical workflow would include gathering, analysis, preservation, authentication, and presentation. Generally, building a cyber-forensic system that supports digital evidence, forensic analysis, investigation, and collaborative engagements among anti-cybercrime agencies, and stakeholders is a complex task. In this paper, we present a practical model that could support the management of forensic workflows and collaborations among agencies such as the Economic and Financial Crimes Commission (EFCC), and the Police. We adopt a modified object-oriented methodology in the investigation, analysis, and design of components required to implement a cloud store for forensic operations. The model was validated against the forensic procedures of an anti-crime agency as well as a cloud database service provider using the MongoDB NoSQL platform, to ascertain the level of assurance on its implementability.
{"title":"A Community Cloud-Based Store for Forensic Operations in Cybercrime Control","authors":"Wilson Nwankwo, Anazia E. Kizito, Wifred Adigwe, C. Nwankwo, Francis Uwadia, Samaila Mande","doi":"10.1109/ITED56637.2022.10051615","DOIUrl":"https://doi.org/10.1109/ITED56637.2022.10051615","url":null,"abstract":"Digital forensics is intended to unearth evidence from concluded activities in the cyberspace and such workflow is data-intensive. A typical workflow would include gathering, analysis, preservation, authentication, and presentation. Generally, building a cyber-forensic system that supports digital evidence, forensic analysis, investigation, and collaborative engagements among anti-cybercrime agencies, and stakeholders is a complex task. In this paper, we present a practical model that could support the management of forensic workflows and collaborations among agencies such as the Economic and Financial Crimes Commission (EFCC), and the Police. We adopt a modified object-oriented methodology in the investigation, analysis, and design of components required to implement a cloud store for forensic operations. The model was validated against the forensic procedures of an anti-crime agency as well as a cloud database service provider using the MongoDB NoSQL platform, to ascertain the level of assurance on its implementability.","PeriodicalId":246041,"journal":{"name":"2022 5th Information Technology for Education and Development (ITED)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121375599","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}
Pub Date : 2022-11-01DOI: 10.1109/ITED56637.2022.10051243
J. Isabona, Christian Chizoba Ugochukwu, A. Imoize, N. Faruk
The rapid deployment of wireless cellular communication technologies has witnessed a progressive trend globally, particularly in the last two decades. The need to constantly conduct a regular and proper empirical network performance of these cellular communication technologies towards managing and optimizing service quality is imperative. Previous research has primarily relied on the existing system simulations. Only a few works of literature conducted experimental measurements to evaluate the QoS delivered by these networks. However, an empirical comparative analysis of the different wireless networks remains. This study presents an empirical-based comparative analysis of 5G NR and 4G LTE networks. The analysis is based on available measurements extracted from the Verizon network in the united states. The quality of service (QoS) of the tested wireless network was evaluated. In terms of signal coverage, the 4G network proved superior while the 5G network took the lead in terms of signal quality. The limited coverage of the investigated 5G network could be attributed to the fewer numbers of 5G antennas recently deployed in the environment of study.
{"title":"An Empirical Comparative Analysis of 4G LTE Network and 5G New Radio","authors":"J. Isabona, Christian Chizoba Ugochukwu, A. Imoize, N. Faruk","doi":"10.1109/ITED56637.2022.10051243","DOIUrl":"https://doi.org/10.1109/ITED56637.2022.10051243","url":null,"abstract":"The rapid deployment of wireless cellular communication technologies has witnessed a progressive trend globally, particularly in the last two decades. The need to constantly conduct a regular and proper empirical network performance of these cellular communication technologies towards managing and optimizing service quality is imperative. Previous research has primarily relied on the existing system simulations. Only a few works of literature conducted experimental measurements to evaluate the QoS delivered by these networks. However, an empirical comparative analysis of the different wireless networks remains. This study presents an empirical-based comparative analysis of 5G NR and 4G LTE networks. The analysis is based on available measurements extracted from the Verizon network in the united states. The quality of service (QoS) of the tested wireless network was evaluated. In terms of signal coverage, the 4G network proved superior while the 5G network took the lead in terms of signal quality. The limited coverage of the investigated 5G network could be attributed to the fewer numbers of 5G antennas recently deployed in the environment of study.","PeriodicalId":246041,"journal":{"name":"2022 5th Information Technology for Education and Development (ITED)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129572813","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}
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