120 research outputs found
Machine Learning Approaches to Improve Security and Performance Monitoring of IoT Devices
No full textThe author has granted permission for their work to be available to the general public.In this current era of Internet of Things (IoT), data privacy and security of Internet enabled devices has become a major concern of many users and device manufacturers. Massive amount of data is being generated by these IoT devices and there might be possibilities of user's information being exposed without any privacy protection. The rate of data transfer, size, kind of information transmitted and secure channels used by these IoT devices are of utmost importance and demand more exploratory research. Moreover, the "always on" and "always connected" attributes of IoT devices necessitate working condition as well as performance monitoring. Unexpected downtime and sudden breakdown of IoT devices can be extremely destructive especially for safety-critical systems. Condition monitoring and health state estimation are vital techniques for maintaining high reliability. Effective approach to investigate security and privacy of wide range of IoT devices needs to be developed. Using a proxy server, we investigate the data being transmitted by six representative IoT devices, analyze the data and propose an intelligent approach for proxy connection monitoring. Our results show that user's information and devices' identities were being leaked in our experiments. The applied neural network classifier uses network connection information to effectively detect proxy connections and performs better than Support Vector Machine as well as logistic regression models that were developed. We further propose a robust proxy detection mechanism suit-able for stochastic and deterministic malicious alteration of connection information. The approach is based on Deep Q-Network and Generative Adversarial Network. For condition monitoring, we propose a lightweight model operable on edge device for Remaining Useful Life (RUL) estimation. The model aptly utilizes the time series sensor data and successfully predicts the remaining useful life. Towards a distributed estimator in smart home environment, we also developed a model based on Long Short Term Memory (LSTM) neural network for estimating energy utilization. These research works demonstrate excellent results and contribution to knowledge. Our work addressed two major challenges in IoT, namely security and performance monitoring. The various data driven approaches and methods that we developed can be applied to enhance data security and performance monitoring in IoT. Security mechanisms to detect unsolicited proxy connection, anomalies or cyber attacks have been proposed. Furthermore, our techniques for estimating remaining useful life and energy utilization in smart home environment are effective. Efficient method for distributed learning and use case are also proposed to illustrate its feasibility. These are approaches that can improve reliability, performance monitoring and time-critical data driven computation.Computer Scienc
A Cloud Based Approach for Data Security in IoT
No full textThe number of connected devices grows rapidly each year as more and more enterprises realize its potentials. Despite the benefits, data privacy and security in Internet of Things (IoT) remain a major issue. IoT devices generates massive data but are limited in resources. The proliferation of IoT devices and the increasing network traffic have heightened the attack surface. Moreover, the susceptibility of transmitted data to eavesdropping and man-in-the-middle attacks is a great concern to users and manufacturers. It is not all IoT devices that utilize encryption. IoT traffic from devices that transmit data in plain text will expose sensitive information if intercepted by an adversary. Such a vulnerability can be exploited to facilitate identity theft and implement other devasting cyber-attacks. This paper presents an implementation of a cloud-based security approach for transmitted data in IoT. The design is based on Lambda architecture using Amazon Web Services. The proposed approach effectively processes and analyzes real-time sensor data as well as historical data from a master database on the cloud. It also ensures the security of user’s information. Keywords: Internet of Things, Cloud computing, Data security, Lambda architecture DOI: 10.7176/CEIS/11-2-03 Publication date: February 29th 202
Security Flaws in IoT Devices: Investigation and Defense Mechanisms
No full textThe proliferation of Internet of Things (IoT) devices has led to massive generation of sensor data and increase in attack vectors. Traffic generated by these devices require more exploratory studies in order to determine the effective ways to secure transmitted data and avert exploitation by hackers. IoT devices susceptibility to direct or remote manipulation, secure channel used for message transmission and resilience of the underlying middleware (broker) to exploitation are very important issues that worth consideration. With more data ever being collected than before, the security of user’s information and devices identities are becoming a great concern. In this research work, we evaluate the vulnerabilities inherent in an IoT ecosystem design that was developed using Raspberry Pi, sensors and MQTT protocol. We also developed a real-time anomaly detection in sensor reading to avert dangerous situation and evaluate the effectiveness of our work. Keywords: Internet of Things, Vulnerabilities, Data privacy, Security mechanisms DOI: 10.7176/JIEA/10-1-04 Publication date: January 31st 202
Covid-19 mõju liha tarneahelale Ondo osariigis Nigeerias: liha jaemüüjate vaatenurk
No full textMaster’s thesis
Curriculum in Agri-Food Business ManagementCOVID-19 has affected the global economy, and the effect has affected chiefly the agricultural and food
business. This study aimed to research the impacts of COVID-19 on the supply chain of meat in Ondo
State, Nigeria, through the lens of meat retailers. This study employed a quantitative study approach and
questionnaires. The hypothesis designed for this study was achieved with statistical correlation models
using SPSS Statistical Software. The findings showed that the COVID-19 pandemic has significantly
affected the retailers in Ondo State, Nigeria and the price, supply, and demand of meat in Ondo State.
All the determinants showed a positive coefficient, meaning that an increase in transport cost, storage
cost, and cost quantity of meat available led to a rise in the market price. Among other recommendations,
the study recommended that the government establish local cow farms in the State and provide funds for
the increase in the supply of close substitutes to mitigate the rise in the price of cow meat because of its
growth in demand.COVID-19 on mõjutanud maailma majandust ning see on mõjutanud eelkõige põllumajandus- ja
toiduäri. Selle uuringu eesmärk oli uurida COVID-19 mõju liha tarneahelale Ondo osariigis Nigeerias,
keskendudes liha jaemüüjatele. Selles uuringus kasutati kvantitatiivset uurimismeetodit ja küsimustikke.
Selle uuringu jaoks kavandatud hüpotees saavutati statistiliste korrelatsioonimudelitega, kasutades SPSS
statistilist tarkvara. Tulemused näitasid, et COVID-19 pandeemia on märkimisväärselt mõjutanud
jaemüüjaid Ondo osariigis Nigeerias ning liha hinda, pakkumist ja nõudlust Ondo osariigis. Kõik
määrajad näitasid positiivset koefitsienti, mis tähendab, et transpordikulude, ladustamiskulude ja
saadaoleva liha omahinna suurenemine tõi kaasa turuhinna tõusu. Muude soovituste hulgas soovitati
uuringus valitsusel rajada osariiki kohalikud lehmafarmid ja eraldada raha lähiasendajate pakkumise
suurendamiseks, et leevendada nõudluse kasvust tulenevat lehmaliha hinnatõusu
Hauntings and the Legacies of Colonialism and Slavery in Olumide Popoola's Works
No full textOlumide Popoola is a German Nigerian author whose works vary in genre from short
fiction to poetry and theater. Popoola was raised travelling between Germany and Nigeria with
her German mother and Nigerian father, but, since leaving Germany in 2002, she lives in
London and teaches undergraduate Creative Writing classes at Goldsmiths University of London
(Deutsche Welle). She attended East London University to complete a Master’s Degree in
Writing: Imaginative Practice in 2009; after receiving her Master’s, Popoola stayed at the
University of East London for her PhD which she completed in 2015. Despite having been raised
in Germany, Popoola writes in English, citing the fact that her everyday language is English, so it
“is the sensible choice” (Layne). In an email interview with Dr. Priscilla Layne, she states that
because of the lack of interest in creative writing by Afro-German authors in Germany as she
was beginning of her career, it made more sense for her to begin her career elsewhere;
however, despite writing in English, her earlier works were all published by German publishers.
Her first published work, this is not about sadnesss (2010), was written originally as her
Master’s Thesis in Creative Writing and was edited by Sharon Otoo, a prominent Afro-German
writer. Her second published work is a short play entitled Also by Mail (2013) and was also
edited by Otoo. The last work that will be discussed in this thesis is a collection of poetry
published in an anthology of works by people of color in Germany and their experiences
entitled Arriving in the Future (2014). Popoola’s more recent work are two novels: Breach was
co-written with Annie Holmes and published by a British press, and When We Speak of Nothing
(2017) was published by a Nigerian press.Bachelor of Art
Molecular interaction and inhibitory activity of dandelion’s compounds on nucleoprotein: A therapeutic intervention in lassa fever
No full textLassa fever (LF) is an acute and sometimes fatal viral hemorrhagic fever caused by the Lassa virus (LASV). It is a major public health challenge and endemic exclusively in West Africa. Despite the large toll of human morbidity and mortality, no vaccine or effective drugs are available to treat this disease. Therefore, there is an urgent need for the development of novel and effective treatments and therapeutics. LASV nucleoprotein plays a vital role in several aspects of the viral life cycle. Therefore, an effective inhibitor of LASV nucleoprotein will potentially control the replication of LASV. To evaluate the inhibitory effect of Dandelion phyto-compounds on LASV nucleoprotein, Glide-SP, and – XP docking was performed for hit identification. The hit compounds were further subjected to Induced Fit Docking (IFD) followed by Prime MM-GBSA calculation and ADME studies. Dandelion phyto-compounds, carfentrazone, luteolin, caffeic acid, and riboflavin recorded better binding affinity than the reference drug, ribavirin, and interacted with key amino acids residues. ADME studies also showed that our hit compounds are drug-like. This study showed that phyto-compounds of dandelion could be a better and effective therapeutics in LF treatment
Determinants of training needs of youths in broiler chicken production in Osun State, Nigeria and implications for extension workers
No full textSaabunud / Received 10.10.2019 ; Aktsepteeritud / Accepted 17.12.2019 ; Avaldatud veebis / Published online 25.12.2019 ; Vastutav autor / Corresponding author: Mary Oluwaseun Olumide-Oyaniyi e-mail: [email protected] study identified the factors influencing the training needs of youth in broiler chicken production and drew implications for extension workers in Osun State, Nigeria. Data were collected from 221 youth farmers through a purposive sampling procedure and a snowball sampling technique. The data were analyzed using descriptive statistics, correlation, regression and factor analytical techniques. Findings reveal that 43.4% of the respondents were between the ages of 26 and 30 years, 26.7% were between the ages of 31 and 35 years, 19.0% were above 36 years of age while 10.9% of the respondents were less than 25 years of age. Majority (60.2%) of the respondents were males while others 39.8% were females. In addition, 40.7% of the respondents had at least three years of broiler chicken production experience, 34.8% had four to six years of experience, 17.6% had seven to nine years of experience and the remaining 6.8% had more than 10 years of broiler chicken production experience. In addition, vast Majority 86.0% of the respondents raise below 200 birds at the time of this research, 8.1% raise between 201 and 300 birds, 5.0% raised above 401 birds while the remaining 0.9% of the respondents raised between 301 and 400 birds. Furthermore, majority (60.2%) of the respondents have not received any training in poultry farming in the past one year while 39.8% of respondents received training between two to five times in the past one year. In addition, respondents were highly in need of training in five standard practices involved in broiler chicken production, which are: growing management / daily routine management, poultry housing, marketing of birds, litter management and equipment. Two groups of factors; income factors (33.2%) and training related factors (21.0%) that were isolated contributed 54.2% to the training needs of youth in broiler chicken production in Osun State, Nigeria
Nigerian Journal of Banking and Financial Issues (NJBFI): CAPITAL STRUCTURE, CORPORATE GOVERNANCE AND COST EFFICIENCY IN SELECTED LISTED INSURANCE FIRMS IN NIGERIA
No full textThe study examined the capital structure\u27s effect on the listed insurance organizations as well as the cost effectiveness of a sample of Nigerian insurance firms that were publicly traded. Additionally, it assessed the impact of corporate governance on the selected listed insurance institutions in Nigeria while taking cost effectiveness and capital structure into consideration. Between 2005 and 2020, the post-consolidation period and the time the nation was impacted by the infamous corona virus that shook the entire world, they were with the intention of providing information on the interactions between capital structure, corporate governance, and cost efficiency in a number of Nigerian insurance organizations. This study\u27s goal is to investigate the capital structure, corporate governance, and cost effectiveness of a sample of Nigeria\u27s listed insurance institutions. The study used a descriptive survey design and secondary data from 10 listed insurance firms in Nigeria. Stochastic Frontier Analysis (SFA) was used to test the data. Business governance factors including board size (t= 2.285, p < 0.05) and board expertise (t=-2.311, p< 0.05) have a substantial impact on the capital structure. The results also showed that variables that worked as mediators between corporate governance and cost effectiveness, such as board size (t=-2.807, p < 0.05), board independence, and board composition, were both statistically significant at the 5% level. The findings of the investigation showed a strong correlation between capital structure, corporate governance, and cost effectiveness
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