2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)最新文献

An Enhanced Bank Customers Churn Prediction Model Using A Hybrid Genetic Algorithm And K-Means Filter And Artificial Neural Network 基于遗传算法、k均值滤波和人工神经网络的银行客户流失预测模型

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428805

R. Yahaya, O. A. Abisoye, S. Bashir

引用次数: 7

A Novel Smart CBT Model for Detecting Impersonators using Machine Learning Technique 一种利用机器学习技术检测模仿者的新型智能CBT模型

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428814

A. M. John-Otumu, O. Nwokonkwo, I. U. Izu-Okpara, O. O. Dokun, K. Susan, E. O. Oshoiribhor

{"title":"A Novel Smart CBT Model for Detecting Impersonators using Machine Learning Technique","authors":"A. M. John-Otumu, O. Nwokonkwo, I. U. Izu-Okpara, O. O. Dokun, K. Susan, E. O. Oshoiribhor","doi":"10.1109/CYBERNIGERIA51635.2021.9428814","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428814","url":null,"abstract":"The computer-based testing (CBT) platforms for conducting mass-driven examinations over computer networks in order to eliminate certain challenges such as delay in marking, misplacement of scripts, impersonation, monitoring and so on associated with the conventional Pen and Paper Type (PPT) of examination has also been seriously bedeviled with the same issue of impersonation commonly associated with the PPT system. The existing CBT systems relies solely on the CCTV system for monitoring people passively and the human invigilators (Proctors) for going round the examination halls in order to physically confirm the students face against their pictures on their respective system dashboard which takes so many time and effort just to screen people against impersonating and yet impersonation is on the increase with CBT system. The proposed Smart CBT model integrates an intelligent agent assessor to the existing CBT model using K-Nearest Neighbor (KNN) machine learning technique for detecting a likely case of impersonation threat considering the considering the level of accuracy and response time in answering the questions the agent delivers to the students shortly before the actual examination can commence. A total of 3,083 dataset was gathered, and 80% (2,466) of the dataset was used for training the model, while 20% (617) dataset was used in testing the model to enable the model detect unseen data correctly. Results revealed that 99.99% accuracy rate, precision, recall and f-score were obtained. The propose Smart CBT model is recommended for all tertiary institutions and commercial CBT software product adoption.","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124081026","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: 2

Recognition-Based Graphical Password Algorithms: A Survey 基于识别的图形密码算法综述

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428801

Jiya Gloria Kaka, Oyefolahan O. Ishaq, Joseph O. Ojeniyi

引用次数: 4

Determining Mice Sex from Chest X-rays using Deep Learning 利用深度学习从胸部x光片确定小鼠性别

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428822

A. Ajiboye, K. Babalola

引用次数: 0

Automatic Diacritic Recovery with focus on the Quality of the training Corpus for Resource-scarce Languages 基于资源稀缺语言训练语料库质量的自动变音符恢复

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428872

I. I. Ayogu, Onoja Abu

{"title":"Automatic Diacritic Recovery with focus on the Quality of the training Corpus for Resource-scarce Languages","authors":"I. I. Ayogu, Onoja Abu","doi":"10.1109/CYBERNIGERIA51635.2021.9428872","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428872","url":null,"abstract":"The development and availability of high quality corpus for many African languages is still hampered by dearth of appropriate software tools and devices. To be able to rapidly create large quantities of high quality corpus of majority of African and Nigerian languages, a diacritic tool is required. The presentation of texts of natural languages without diacritic marks presents significant problems to both human and computational processing systems due to partial or total loss of the accompanying grammatical, syntactic and or semantic information. This paper investigated the effect of diacritic quality of a small-sized training corpus on the classification accuracy of some simple and commonly used machine learning algorithms for diacritic restoration tasks following the character-based approach. The classification accuracy of eight of the diacritic-bearing characters of Yoruba language of Nigeria were investigated. The results show that the completeness and correctness of diacritics has a significant effect on the performance of the algorithms; decision tree algorithm produced the overall best accuracy response of 3.22 % to the data quality improvement. The observations from the learning behaviours of the algorithms suggests that a 100,000 words corpus is adequate to train a decision tree model for automatic diacritic restoration for Yoruba language but insufficient to obtain a state-of-the art results for the LDA, LOGREG and SVM algorithms.","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122128207","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

Leveraging Artificial Intelligence of Things for Anomaly Detection in Advanced Metering Infrastructures 利用物联网人工智能在高级计量基础设施中进行异常检测

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428792

R. Ogu, C. Ikerionwu, I. I. Ayogu

{"title":"Leveraging Artificial Intelligence of Things for Anomaly Detection in Advanced Metering Infrastructures","authors":"R. Ogu, C. Ikerionwu, I. I. Ayogu","doi":"10.1109/CYBERNIGERIA51635.2021.9428792","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428792","url":null,"abstract":"The integration of more sensory and actuation components to the Smart Grid produces high volume of data. Consequently, this big data stretches the transmission, processing, and storage capabilities of the Smart Grid infrastructures. The vulnerability of advanced metering infrastructures (AMIs) is on the rise, as more devices are connected to the Internet these days. The aforementioned realities have continued to necessitate a debate on the future of cloud-centered artificial intelligence (AI) services for latency-sensitive user-centric IoT applications. It is rapidly becoming necessary to leverage on the applicability of EdgeAI directly on IoT sensory nodes involved in energy metering. This paper proposes the applicability of Artificial Intelligence situated on smart meter, to perform micro analytics at the edge of AMI networks: Artificial Intelligence of Things. Therefore, a functional AMI model based on IoT and EdgeAI is presented herein. Additionally, an integration architecture for the anticipated Smart Grid based on IoT and EdgeAI is presented. On implementation, the proposed model would provide high performance analytics and Edge computing capabilities to enable AMIs initiate instant data check at the source and relay relevant real-time data to the Utility through the Internet.","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123837985","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: 2

Applicability of Distributed IoT-powered Triage Units in the Management of Infectious Diseases in Developing Countries: The COVID-19 case 分布式物联网分诊装置在发展中国家传染病管理中的适用性:以COVID-19为例

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428853

R. Ogu, L. Uzoechi, Yusuf U. Mshelia, Izuchukwu Azubuike Erike, Chinomso D. Okoronkwo

{"title":"Applicability of Distributed IoT-powered Triage Units in the Management of Infectious Diseases in Developing Countries: The COVID-19 case","authors":"R. Ogu, L. Uzoechi, Yusuf U. Mshelia, Izuchukwu Azubuike Erike, Chinomso D. Okoronkwo","doi":"10.1109/CYBERNIGERIA51635.2021.9428853","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428853","url":null,"abstract":"Medical pandemics disrupt human activities and threaten the existence of man. Oftentimes, health care delivery services and personnel become overwhelmed by health interventions in the context of pandemics. Currently, the COVID-19 respiratory health pandemic has troubled the world economy. This paper presents the Phase One of a health care delivery architecture based on the Internet of Things $(mathbf{IoT})$ technology. The architecture proposed herein comprises of three layers: physical, communication and cloud. The architecture considered the peculiarity of developing countries like Nigeria, where there is inadequate electricity and limited communication bandwidth with poor Quality of Services $(mathbf{QoS})$ of the Internet. The $mathbf{IoT}$ triage architectural model developed in this work aims to address priority on assignment of the limited health facilities such as bed spaces, ventilators, medical professionals, etc., based on comparative analytics on vital health signals updates from $mathbf{IoT}$ devices of patients. In this work, much emphasis is placed on the physical layer of the architecture. By this, a use case diagram for the physical triage outfit is developed in addition to the architecture. It is expected that the proper implementation of this architecture in health care delivery services across the globe will go a long in managing and minimizing the effects of pandemics like the COVID-19.","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133075621","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

Detecting Advance Fee Fraud Using NLP Bag of Word Model 基于词模型的NLP袋检测预付费欺诈

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428793

M. Hamisu, Ali Mansour

引用次数: 4

An Optimized Customers Sentiment Analysis Model Using Pastoralist Optimization Algorithm (POA) and Deep Learning 基于牧民优化算法(POA)和深度学习的客户情感分析优化模型

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428863

Safiya A. Shehu, A. Mohammed, Ibrahim M. Abdullahi

{"title":"An Optimized Customers Sentiment Analysis Model Using Pastoralist Optimization Algorithm (POA) and Deep Learning","authors":"Safiya A. Shehu, A. Mohammed, Ibrahim M. Abdullahi","doi":"10.1109/CYBERNIGERIA51635.2021.9428863","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428863","url":null,"abstract":"Users usually express their sentiment online which influences purchased products and services. The computational study of people's feelings and thoughts on entities is known as sentiment analysis. The Long Short-Term Memory (LSTM) model is one of the most common deep learning models for solving sentiment analysis problems. However, they possess some drawbacks such as longer training time, more memory for training, easily over fits, and sensitivity to randomly generated parameters. Hence, there is a need to optimize the LSTM parameters for enhanced sentiment analysis. This paper proposes an optimized LSTM approach using a newly developed novel Pastoralist Optimization Algorithm (POA) for enhanced sentiment analysis. The model was used to analyze sentiments of customers retrieved from Amazon product reviews. The performance of the developed POA-LSTM model shows an optimal accuracy, precision, recall and F1 measure of 77.36%, 85.06%, 76.29%, and 80.44% respectively, when compared with LSTM model with 71.62%, 78.26%, 74.23%, and 76.19% respectively. It was also observed that POA with 20 pastoralist population size performs better than other models with 10, 15, 25 and 30 population size.","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"189 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114049123","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

Analysis of Cybercrime in Nigeria 尼日利亚网络犯罪分析

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428848

M. Hamisu, Abubakar M. Idris, A. Mansour, M. Olalere

{"title":"Analysis of Cybercrime in Nigeria","authors":"M. Hamisu, Abubakar M. Idris, A. Mansour, M. Olalere","doi":"10.1109/CYBERNIGERIA51635.2021.9428848","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428848","url":null,"abstract":"Nigeria has both the largest economy and population in Africa, and this contribute to the growth and fast expansion of ICT and the use of Internet in Nigeria. Like other technologies, Internet has been used by both good and bad actors. The use of internet and computer to commit crime is costing global economy the loss of billions of dollars. In Nigeria, the majority of the population use the Internet for good but some few are using it to commit criminal activities such as Fraud. Cybercriminals in Nigeria, widely called Yahoo Boys in the country specialize in Internet fraud that target mostly International victims. The Nigeria government is stepping efforts to bring an end the activities of these criminals as their actions tarnishes the image of the country. While the efforts of the government had yielded some positive results, the threat of Cybercrime in Nigeria is still high, as criminals continue to take advantage of flaws in the law enforcement tactical approach in addressing the crime. This paper discusses an overview of Cybercrime in Nigeria, the common types of Cybercrime that is perpetuated from the country and the reason of doing so. It also discusses the government's success and areas of strength in its fight against Cybercrime and highlight the areas of weaknesses. Recommendations and suggestions are made on how law enforcement and the government at large can improve to tackle Cybercrime better in Nigeria.","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126320224","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