177 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
Solid Verifiable Credentials
No full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 63-66).Credentials are an integral part of our lives, as they express our capabilities and enable access to restricted services and benefits. In the early 2010s, the Verifiable Claims Working Group of the World Wide Web Consortium (W3C) proposed a specification for what is now the Verifiable Credentials Data Model. This living specification, which is still in development, outlines a cogent framework for the issuance, storage, presentation, and verification of credentials on the Web. Many of the leading Verifiable Credentials projects leverage Distributed Ledger Technology (DLT), potentially compromising Web interoperability and sometimes exposing otherwise personal data. SolidVC is a decentralized Verifiable Credentials platform built with the open protocols of the Web. It is implemented on top of Solid, a Web framework developed at MIT in 2016 that allows decentralized applications to interact with personal user data to provide services in an access controlled environment.by Kayode Yadilichi Ezike.M. Eng.M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc
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
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
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
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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