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

A Review of Dna Cryptograhic Approaches Dna密码方法综述

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428855

M. Iliyasu, O. A. Abisoye, S. Bashir, J. Ojeniyi

{"title":"A Review of Dna Cryptograhic Approaches","authors":"M. Iliyasu, O. A. Abisoye, S. Bashir, J. Ojeniyi","doi":"10.1109/CYBERNIGERIA51635.2021.9428855","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428855","url":null,"abstract":"Cryptography is described as the encryption analysis of data or secret data writing using logical and mathematical data protection principles. It is an information technology for banking, medical systems, transportation and other Internet of things applications. Cryptography has become more important, and it is subjected to growing security concerns. Each system is built with its own strength in cryptography; symmetric encryption provides an economical data protection solution without compromise but it is important to share or distribute the secret key during encryption and decryption process. In comparison, the asymmetric encryption addresses the issue of secret key distribution; however, the stand-alone technique is slow and needs more computing resources than the symmetric encryption approach. In this context, a study of papers relating to DNA cryptographic approaches are presented and the research was centered from 2015 to 2020. The primary sources of information are Science Direct and Research Gate publication platforms. The existing shortcomings of DNA cryptographic approaches were established and analysis was performed on the most frequently used encryption technique based on the literature. The significant findings of this research reviewed that DNA digital coding is the most adopted cryptographic technique used to improve information security and the most common limitations of the DNA cryptographic approaches are high time complexity and algorithm complexity which is possible to infer from the literature.","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"6 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":"126647878","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: 7

Design of a Customer-Centric Surveillance System for ATM Banking Transactions using Remote Certification Technique 基于远程认证技术的以客户为中心的ATM银行交易监控系统设计

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428795

Olugbemiga Solomon Popoọla, Ibraheem Temitope Jimoh, A. O. Adetunmbi, Kayode Boniface Alese, Chukwuemeka Christian Ugwu

{"title":"Design of a Customer-Centric Surveillance System for ATM Banking Transactions using Remote Certification Technique","authors":"Olugbemiga Solomon Popoọla, Ibraheem Temitope Jimoh, A. O. Adetunmbi, Kayode Boniface Alese, Chukwuemeka Christian Ugwu","doi":"10.1109/CYBERNIGERIA51635.2021.9428795","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428795","url":null,"abstract":"Automated Teller Machine (ATM) is a major tool for electronic banking (e-Banking). It enables the availability of banking services anytime and anywhere. Presently, most ATMs communicate only with the banking system networks for security monitoring and enforcements. This paper presents a customer-aware surveillance system for all attempted ATM banking activities. Employing a graphical modeling tool (Unified Modeling Language), the design integrates an additional input, through an inbuilt IP Camera that stealthily captures the ATM user facial image, which is automatically transmitted to the mobile device of the bank account owner, through some dedicated artificial intelligent agents, for remote certification, which either authorizes the transaction appropriately or signals a security-violation alert to the banking security system. Thus, online and real-time monitoring of ATM banking transactions is enabled, reporting suspected unusual attempts to account owner and bank security unit. Hence, customer-level visibility of ATM banking security, through remote certification of a proxy ATM user, is made possible.","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"40 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":"125765274","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

Conceptual Modelling of Criticality of Critical Infrastructure Nth Order Dependency Effect Using Neural Networks 基于神经网络的关键基础设施n阶依赖效应临界性概念建模

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428861

U. Mbanaso, J. Makinde

{"title":"Conceptual Modelling of Criticality of Critical Infrastructure Nth Order Dependency Effect Using Neural Networks","authors":"U. Mbanaso, J. Makinde","doi":"10.1109/CYBERNIGERIA51635.2021.9428861","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428861","url":null,"abstract":"This paper presents conceptual modelling of the criticality of critical infrastructure (CI) nth order dependency effect using neural networks. Incidentally, critical infrastructures are usually not stand-alone, they are mostly interconnected in some way thereby creating a complex network of infrastructures that depend on each other. The relationships between these infrastructures can be either unidirectional or bidirectional with possible cascading or escalating effect. Moreover, the dependency relationships can take an nth order, meaning that a failure or disruption in one infrastructure can cascade to nth interconnected infrastructure. The nth-order dependency and criticality problems depict a sequential characteristic, which can result in chronological cyber effects. Consequently, quantifying the criticality of infrastructure demands that the impact of its failure or disruption on other interconnected infrastructures be measured effectively. To understand the complex relational behaviour of nth order relationships between infrastructures, we model the behaviour of nth order dependency using Neural Network (NN) to analyse the degree of dependency and criticality of the dependent infrastructure. The outcome, which is to quantify the Criticality Index Factor (CIF) of a particular infrastructure as a measure of its risk factor can facilitate a collective response in the event of failure or disruption. Using our novel NN approach, a comparative view of CIFs of infrastructures or organisations can provide an efficient mechanism for Critical Information Infrastructure Protection and resilience (CIIPR) in a more coordinated and harmonised way nationally. Our model demonstrates the capability to measure and establish the degree of dependency (or interdependency) and criticality of CIs as a criterion for a proactive CIIPR.","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"98 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":"134627133","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

Critical Requirements for Sustainable Deployment of IoT Systems in Nigeria 在尼日利亚可持续部署物联网系统的关键要求

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428821

G. Chukwudebe, R. Ogu, Jenny Ebitonere Fawei

{"title":"Critical Requirements for Sustainable Deployment of IoT Systems in Nigeria","authors":"G. Chukwudebe, R. Ogu, Jenny Ebitonere Fawei","doi":"10.1109/CYBERNIGERIA51635.2021.9428821","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428821","url":null,"abstract":"The Internet of Things is finding innovative and interesting applications. Currently, it is being applied in transportation, healthcare delivery, agriculture, security surveillance, smart manufacturing. It has resulted to the development of smart cities, manufacturing, grid etc. The IoT nodes may collect sensitive personal information or become surface for cyberattacks, hence suitable policies and regulations need to be enacted at the global and national levels to ensure benefit realization and safe use. This paper reviewed already established IoT standards and best practices by notable organizations such as the Body of European Regulators for Electronic Communications, the GSM Association, the Institute of Electrical and Electronic Engineers, International Telecommunication Union, International Standards Organization, European Telecommunication Standards Institute etc. The regulation of IoT applications and systems is more challenging than existing ICT because of the complexity of numerous interactions involved in any Internet of Things ecosystem. The IoT regulatory efforts so far in USA, India and European Union were examined although standardization efforts are still ongoing. From the study, the critical requirements for a sustainable deployment of IoT systems; government support, appropriate spectrum allocation, connectivity, adaptability, security, privacy and trust were identified. A robust IoT Policy and Regulatory framework for Nigeria was proposed and a multi-sectoral collaboration was recommended for full development and implementation of the policy and regulatory framework.","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"59 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":"116449467","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

A Review on Machine Learning Techniques for Image Based Spam Emails Detection 基于图像的垃圾邮件检测机器学习技术综述

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428826

M. Abdullahi, A. Mohammed, S. Bashir, Opeyemi O. Abisoye

{"title":"A Review on Machine Learning Techniques for Image Based Spam Emails Detection","authors":"M. Abdullahi, A. Mohammed, S. Bashir, Opeyemi O. Abisoye","doi":"10.1109/CYBERNIGERIA51635.2021.9428826","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428826","url":null,"abstract":"Sending and receiving e-mails have continued to take the lead being the easiest and fastest way of e-communication despite the presence of other forms of e-communication such as social networking. The rise in online transactions through email has globally contributed to the increasing rate of spam emails relatively which has been a major problem in the field of computing. In this note, there are many machine learning techniques available for detecting these unwanted spams. In spite of the significant progress made in the figures of literature reviewed, there is no machine learning method that has achieve 100% accuracy. Each algorithm only utilizes limited features and properties for classification. Therefore, identifying the best algorithm is an important task as their strengths need to be weighed against their limitations. In this paper we explored different machine learning techniques relevant to the spam detection and discussed the contributions provided by researchers for controlling the spamming problem using machine learning classifiers by conducting a comparative study of the selected machine learning algorithms such as: Naive Bayes, Clustering techniques, Random Forest, Decision Tree and Support Vector Machine (SVM).","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"1 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":"130841046","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

[Copyright notice] (版权)

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/cybernigeria51635.2021.9428858

引用次数: 0

Impact of Pixel Scaling on Classification Accuracy of Dermatological Skin Disease Detection 像素缩放对皮肤病检测分类精度的影响

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428813

Afiz Adeniyi Adeyemo, S. Bashir, A. Mohammed, Opeyemi O. Abisoye

{"title":"Impact of Pixel Scaling on Classification Accuracy of Dermatological Skin Disease Detection","authors":"Afiz Adeniyi Adeyemo, S. Bashir, A. Mohammed, Opeyemi O. Abisoye","doi":"10.1109/CYBERNIGERIA51635.2021.9428813","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428813","url":null,"abstract":"Images are made up of many features on which the performance of the system used in processing them depends. Image pixel values are one of such important features which are often not considered. This study investigates the importance of image preprocessing using some calculated statistics on the pixels of skin images in classifying images using HAM10000 dataset. Image pixel values make a great impact on the classification performance of Convolutional Neural Network (CNN) based image classifiers. In this study, the ‘original pixel values’ of the skin images are used to train three carefully designed CNN architectures. The designed architectures are further trained with some calculated statistical values using ‘global centering’, ‘local centering’, ‘dividing pixel values by the mean’ and ‘root of the division’ techniques of data normalization. The results obtained have shown that, out of the five different forms of values used in training the architectures, the CNNs trained with the original (unscaled) image pixel values perform below those trained with calculated statistics that are computed on the image pixel values.","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":"126409480","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 Active Power Control Technique for Interference Mitigation in 5G Uplink Macro-Femto Cellular Network 5G上行宏femto蜂窝网络中增强有源功率控制技术的干扰抑制

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428852

Katfun Philemon Dawar, Usman Abraham Usman, Bala Alhaji Salihu

{"title":"An Enhanced Active Power Control Technique for Interference Mitigation in 5G Uplink Macro-Femto Cellular Network","authors":"Katfun Philemon Dawar, Usman Abraham Usman, Bala Alhaji Salihu","doi":"10.1109/CYBERNIGERIA51635.2021.9428852","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428852","url":null,"abstract":"Macro-femto heterogeneous network (HetNet) comes with tremendous inter and intra cell interference problems. This paper considered fifth generation (5G) non-stand-alone (NSA) architecture. An enhanced active power control technique (EAPC) is proposed to mitigate interference in uplink macro-femto HetNet. The MATLAB simulation result obtained in terms of average power consumption of macrocell user equipment (MUE) and femtocell user equipment (HUE) using EAPC technique stood at 6.7 dBm and 7.5 dBm respectively, as against that of active power control (APC), fixed power control (FPC) and power control 1 (PC1); which stood at 10.9 dBm, 23.0 dBm, 14.8 dBm for MUE and 11.1 dBm, 23.0 dBm, 14.8 dBm for HUE respectively. It indicates that HUE and MUE using EAPC technique had low average power consumption when benchmark. 5G NSA macrocell base station (en-gNB), 60% cumulative distributive function (CDF) of throughput based on EAPC, APC, PC1 and FPC techniques had 36.2 Mbps, 15.0 Mbps, 24.0 Mbps and 12.5 Mbps throughput respectively. And that of femtocell base station (Hen-gNB) according to EAPC, APC, PC1 and FPC was 25.0 Mbps, 23.0 Mbps, 10.0 Mbps and 18.6 Mbps throughout, respectively. This implies that EAPC has better Hen-gNB and en-gNB throughput when benchmarked with other related techniques. Hence, the proposed EAPC technique improves 5G network performance in terms of better throughput and conserving limited user equipment (UE) energy.","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"71 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":"132959457","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

A Distributed Denial of Service Attack Detection System using Long Short Term Memory with Singular Value Decomposition 基于奇异值分解的长短期记忆分布式拒绝服务攻击检测系统

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428870

Chukwuemeka Christian Ugwu, O. Obe, Olugbemiga Solomon Popoọla, A. O. Adetunmbi

{"title":"A Distributed Denial of Service Attack Detection System using Long Short Term Memory with Singular Value Decomposition","authors":"Chukwuemeka Christian Ugwu, O. Obe, Olugbemiga Solomon Popoọla, A. O. Adetunmbi","doi":"10.1109/CYBERNIGERIA51635.2021.9428870","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428870","url":null,"abstract":"The increase in online activity during the COVID 19 pandemic has generated a surge in network traffic capable of expanding the scope of DDoS attacks. Cyber criminals can now afford to launch massive DDoS attacks capable of degrading the performances of conventional machine learning based IDS models. Hence, there is an urgent need for an effective DDoS attack detective model with the capacity to handle large magnitude of DDoS attack traffic. This study proposes a deep learning based DDoS attack detection system using Long Short Term Memory (LSTM). The proposed model was evaluated on UNSW-NB15 and NSL-KDD intrusion datasets, whereby twenty-three (23) and twenty (20) attack features were extracted from UNSW-NB15 and NSL-KDD, respectively using Singular Value Decomposition (SVD). The results from the proposed model show significant improvement when compared with results from some conventional machine learning techniques such as Naïve Bayes (NB), Decision Tree (DT), and Support Vector Machine (SVM) with accuracies of 94.28% and 90.59% on both datasets, respectively. Furthermore, comparative analysis of LSTM with other deep learning results reported in literature justified the choice of LSTM among its deep learning peers in detecting DDoS attacks over a network.","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"9 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":"134220421","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: 9

Artificial Intelligence Autonomous Unmanned Aerial Vehicle (UAV) System for Remote Sensing in Security Surveillance 用于安全监控的人工智能自主无人机(UAV)遥感系统

2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) Pub Date : 2021-02-23 DOI: 10.1109/CYBERNIGERIA51635.2021.9428862

U. O. Matthew, J. S. Kazaure, Amaonwu Onyebuchi, Ogobuchi Okey Daniel, I. H. Muhammed, Nwamaka U. Okafor

{"title":"Artificial Intelligence Autonomous Unmanned Aerial Vehicle (UAV) System for Remote Sensing in Security Surveillance","authors":"U. O. Matthew, J. S. Kazaure, Amaonwu Onyebuchi, Ogobuchi Okey Daniel, I. H. Muhammed, Nwamaka U. Okafor","doi":"10.1109/CYBERNIGERIA51635.2021.9428862","DOIUrl":"https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428862","url":null,"abstract":"Adapting artificial intelligence autonomous systems required a policy specification, policy enforcement and policy management on the key prioritized functions based on the inherent policy enforcement and self-definitive programmed knowledge by an autonomous system. In the current research, attempt was made to model an autonomous unmanned aerial vehicle (UAV) system to be able to detect humans within the thickest forest region amidst the escalating tension of bokoharam and bandits abductions within the Nigeria geographic space. The autonomous artificial intelligence UAVs was designed using laser-range detectors for location evaluation and pathway finding with very accurate precision. While the UAVs hovers in the neighborhood, it establishes an individualized 3-D map of its surrounding. The central objective of this study is to explore the scientific opportunities available for artificial intelligence unmanned aerial vehicle (Drones) modeled with machine learning (convolution neural network) on Internet of Things $(mathbf{IoTs})$ framework and adapt it to revolutionize the mission on environmental & remote sensing, security surveillance, rescue and search mission. The paper established that Nigeria security forces could adopt artificial intelligence UAV to extradite terrorists within the Lake Chad Basin where bokoharam insurgency and banditry are prevalent. The paper further highlight that UAV could be very instrumental in search and rescue mission by the security forces.","PeriodicalId":208301,"journal":{"name":"2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA)","volume":"57 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":"132399523","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: 7