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Analysis of System Performance Metrics Towards the Detection of Cryptojacking in IOT Devices
Get PDFThis single-case mechanism study examined the effects of cryptojacking on Internet of Things (IoT) device performance metrics. Cryptojacking is a cyber-threat that involves stealing the computational resources of devices belonging to others to generate cryptocurrencies. The resources primarily include the processing cycles of devices and the additional electricity needed to power this additional load. The literature surveyed showed that cryptojacking has been gaining in popularity and is now one of the top cyberthreats. Cryptocurrencies offer anyone more freedom and anonymity than dealing with traditional financial institutions which make them especially attractive to cybercriminals. Other reasons for the increasing popularity of cryptojacking include a large number of vulnerable devices, the low cost to implement, minimal to no expertise required, and the low risk of getting caught or prosecuted. Internet connected devices are becoming increasingly popular and commonplace. Many of these devices also are inherently insecure and make great targets of threat actors. Although many of these devices are low powered, the sheer number of available devices make up for the lack of processing power. Future research could expand on this study by incorporating machine learning, virtualization, live cryptojacking malware samples, or a combination of those items
Analyzing the Effectiveness of Legal Regulations and Social Consequences for Securing Data
Get PDFThere is a wide range of concerns and challenges related to stored data security – which range from privacy and management to operations readiness, These challenges span from financial to personal and public impact. With an abundance of regulations for the enforcement of data security and emerging requirements proposed every year, organizations cannot avoid the legal or social implications of inadequate data protection. Today, public spotlight and awareness are challenging organizations to enhance how data is protected more than at any other time. For this reason, organizations have made significant efforts to improve security.
When looking at precautions or changes, the factors considered are costs associated with such action, a potential consequence of not acting, impact on users, the effort required, and the scope. For this reason, leaders need to make the hard decisions of which risks they can live with and which need to be reduced because it is unrealistic to think that data security can be guaranteed. However, it is essential to have physical, administrative, and technical controls to mitigate data risks. Data protection regulations define requirements, create procedures to identify the associated risks, determine the extent of the impact, and identify what precautions should be taken.
This dissertation defined seven areas for consideration related to stored data security. The research facilitated developing a measurement tool to gather and analyze the knowledge and opinions of working professionals within the United States. The study was performed from July to October 2020, which resulted in a quantitative data sample used to analyze the effectiveness of legal regulations and social consequences for securing data
Understanding the Public Sentiment and Discourse on COVID-19 Vaccine
Get PDFThe novel Coronavirus disease has negatively impacted human lives in various aspects leading to the global health crisis and economic fallout. The availability of vaccines in the U.S. is a relief. However, many people are not in favor of the COVID-19 vaccine. The study aimed to identify the emotions and themes of discourse related to the COVID-19 vaccine posted on Twitter. Sentiment analysis and topic modeling techniques were employed to discover the sentiment and prevalent themes. The findings suggest that overall, the public has positive opinions towards the vaccine. Those people that show positive opinions appreciate the efforts of leadership, medical experts, and pharmaceutical companies in developing the COVID-19 vaccine. They are feeling hopeful and relieved as the vaccines are/will be available. There are also people that hold negative attitudes towards the vaccines because of disbelief in the government and concerns about the efficacy and adverse reactions caused by the vaccines
Explainable Artificial Intelligence in the Medical Domain: A Systematic Review
Get PDFThe applications of Artificial Intelligence (AI) and Machine Learning (ML) techniques in different medical fields is rapidly growing. AI holds great promise in terms of beneficial, accurate and effective preventive and curative interventions. At the same time, there is also concerns regarding potential risks, harm and trust issues arising from the opacity of some AI algorithms because of their un-explainability. Overall, how can the decisions from these AI-based systems be trusted if the decision-making logic cannot be properly explained? Explainable Artificial Intelligence (XAI) tries to shed light to these questions. We study the recent development on this topic within the medical domain. The objective of this study is to provide a systematic review of the methods and techniques of explainable AI within the medical domain as observed within the literature while identifying future research opportunities
Video Games: Do They Affect Adolescent and Teen Behaviors?
Get PDFThe purpose of this survey was to show that video games can be used to vent frustrations and create friendships. To investigate this, a survey was conducted on students enrolled in the Esports program at Dakota State University. The findings of the survey showed that video games were indeed being used as a way to vent frustrations and relieve built-up stress. Only 1.9% of those surveyed believed that video games do not help vent their frustrations. The study also showed that most of the students surveyed started playing video games at a young age. Fifty-eight percent of the students played educational games when they were younger, meaning that they used video games as a learning aid for math, reading, grammar, and more. A majority of the students preferred to keep the moral high ground in adventure and story-based games. This study also showed that 63.5% of the students use video games to socialize with friends they have already made in real life, with another 7.7% of the students stating that they have met most of their friends online
Towards Identity Relationship Management For Internet of Things
Get PDFIdentity and Access Management (IAM) is in the core of any information systems. Traditional IAM systems manage users, applications, and devices within organizational boundaries, and utilize static intelligence for authentication and access control. Identity federation has helped a lot to deal with boundary limitation, but still limited to static intelligence – users, applications and devices must be under known boundaries. However, today’s IAM requirements are much more complex. Boundaries between enterprise and consumer space, on premises and cloud, personal devices and organization owned devices, and home, work and public places are fading away. These challenges get more complicated for Internet of Things (IoTs) due to their diverse use and portability nature. IoTs are being used in consumer space, healthcare, manufacturing, retails, entertainment, transportation, public sector, and many other places. Identity Relationship Management (IRM) can help in solving some of these challenges as it uses a more natural way of access management - a relationship-based access control methodology. IRM can perform identity and relationship management beyond home and organizational boundaries and can simplify authorization and authentication using dynamic intelligence based on relationship.
In this research, we studied the needs of IRM for the Internet of Things. We explored four fundamental questions in IRM: what relationships need to be supported in IRM, how relationships can be supported in IRM, how relationship can be used for access control, and finally what infrastructure is required to support IRM. Since relationship is globally spread out and perimeter-less in nature, we designed the IRM service with a global scalable, modular, and borderless architecture. Instead of building something from scratch, we slightly modified the UMA 2.0 protocol built on top of OAuth 2.0 to make the relationship-based access control feature easily pluggable with existing IAM frameworks. We implemented a proof-of-concept to demonstrate and analyze the results of this research. This dissertation serves as the foundation for future research and development in IRM domain
Isolation and Characterization of Pythium spp. from South Dakota soils under commerical alfalfa production
Get PDFAlfalfa is a significant crop in South Dakota that provides many different benefits for its growers. South Dakota plants the most acres of alfalfa in the United States. It is used as a protein protein-rich feed for livestock, a cover crop that protects against soil erosion, and a natural fertilizer because of its ability to fix nitrogen in the soil. However, alfalfa seedlings are susceptible to many diseases. Pythium root and seed rot is one disease known to have devastating effects on alfalfa field establishment and yield. Pythium species are oomycete pathogens that inhabit the soil and remain present and pathogenic as oospores. Pythium diseases of alfalfa cause reduced root systems, plant size, length, and growth rate. Pythium management is centered on fungicidal seed treatments. There have been recent reports of Pythium spp. infecting alfalfa across the world in places like Sudan and China, but current research in South Dakota is needed. In our research, we isolated Pythium spp. from Lake County South Dakota soils under commercial alfalfa production. We also characterized these isolates with a DNA sequencing analysis and evaluated the isolates for fungicide sensitivity. This summer, we will conduct a statewide Pythium disease survey and assess the collected isolates for fungicide sensitivity and pathogenicity towards various commercial lines of alfalfa. This research will provide growers with the information necessary to Make educated decisions in order to increase yields and maximize their profits.https://scholar.dsu.edu/erposters/1010/thumbnail.jp
Block the Root Takeover: Validating Devices Using Blockchain Protocol
Get PDFThis study addresses a vulnerability in the trust-based STP protocol that allows malicious users to target an Ethernet LAN with an STP Root-Takeover Attack. This subject is relevant because an STP Root-Takeover attack is a gateway to unauthorized control over the entire network stack of a personal or enterprise network. This study aims to address this problem with a potentially trustless research solution called the STP DApp. The STP DApp is the combination of a kernel /net modification called stpverify and a Hyperledger Fabric blockchain framework in a NodeJS runtime environment in userland. The STP DApp works as an Intrusion Detection System (IPS) by intercepting Ethernet traffic and blocking forged Ethernet frames sent by STP Root-Takeover attackers. This study’s research methodology is a quantitative pre-experimental design that provides conclusive results through empirical data and analysis using experimental control groups. In this study, data collection was based on active RAM utilization and CPU Usage during a performance evaluation of the STP DApp. It blocks an STP Root-Takeover Attack launched by the Yersinia attack tool installed on a virtual machine with the Kali operating system. The research solution is a test blockchain framework using Hyperledger Fabric. It is made up of an experimental test network made up of nodes on a host virtual machine and is used to validate Ethernet frames extracted from stpverify
End-to-End Latency Prediction of Microservices Workflow on Kubernetes: A Comparative Evaluation of Machine Learning Models and Resource Metrics
Get PDFAphanomyces root rot of alfalfa disease survey in Eastern South Dakota establishes widespread pathogen distribution
Get PDFAphanomyces euteiches causes Aphanomyces root rot (ARR) and damping-off in alfalfa (Medicago sativa), along with root rotting in many other legumes. According to the United States Department of Agriculture 2020 Crop Production Summary, South Dakota plants the most acres of alfalfa in the United States but is the sixth highest state in production. Identification of A. euteiches has been confirmed in several states surrounding South Dakota providing the need for detection in state since ARR management centers on planting resistant alfalfa cultivars.https://scholar.dsu.edu/erposters/1006/thumbnail.jp