Databases and Information Systems Commons^™

A Design Science Approach To Investigating Decentralized Identity Technology, Janelle Krupicka

Cybersecurity Undergraduate Research Showcase

The internet needs secure forms of identity authentication to function properly, but identity authentication is not a core part of the internet’s architecture. Instead, approaches to identity verification vary, often using centralized stores of identity information that are targets of cyber attacks. Decentralized identity is a secure way to manage identity online that puts users’ identities in their own hands and that has the potential to become a core part of cybersecurity. However, decentralized identity technology is new and continually evolving, which makes implementing this technology in an organizational setting challenging. This paper suggests that, in the future, decentralized identity …

Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman

Electronic Theses and Dissertations

Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …

A New Cache Replacement Policy In Named Data Network Based On Fib Table Information, Mehran Hosseinzadeh, Neda Moghim, Samira Taheri, Nasrin Gholami

VMASC Publications

Named Data Network (NDN) is proposed for the Internet as an information-centric architecture. Content storing in the router’s cache plays a significant role in NDN. When a router’s cache becomes full, a cache replacement policy determines which content should be discarded for the new content storage. This paper proposes a new cache replacement policy called Discard of Fast Retrievable Content (DFRC). In DFRC, the retrieval time of the content is evaluated using the FIB table information, and the content with less retrieval time receives more discard priority. An impact weight is also used to involve both the grade of retrieval …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Ensuring Non-Repudiation In Long-Distance Constrained Devices, Ethan Blum

Honors Theses

Satellite communication is essential for the exploration and study of space. Satellites allow communications with many devices and systems residing in space and on the surface of celestial bodies from ground stations on Earth. However, with the rise of Ground Station as a Service (GsaaS), the ability to efficiently send action commands to distant satellites must ensure non-repudiation such that an attacker is unable to send malicious commands to distant satellites. Distant satellites are also constrained devices and rely on limited power, meaning security on these devices is minimal. Therefore, this study attempted to propose a novel algorithm to allow …

Blockchain Security: Double-Spending Attack And Prevention, William Henry Scott Iii

Electronic Theses and Dissertations

This thesis shows that distributed consensus systems based on proof of work are vulnerable to hashrate-based double-spending attacks due to abuse of majority rule. Through building a private fork of Litecoin and executing a double-spending attack this thesis examines the mechanics and principles behind the attack. This thesis also conducts a survey of preventative measures used to deter double-spending attacks, concluding that a decentralized peer-to-peer network using proof of work is best protected by the addition of an observer system whether internal or external.

Nftdisk: Visual Detection Of Wash Trading In Nft Markets, Xiaolin Wen, Yong Wang, Xuanwu Yue, Feida Zhu, Min Zhu

Research Collection School Of Computing and Information Systems

With the growing popularity of Non-Fungible Tokens (NFT), a new type of digital assets, various fraudulent activities have appeared in NFT markets. Among them, wash trading has become one of the most common frauds in NFT markets, which attempts to mislead investors by creating fake trading volumes. Due to the sophisticated patterns of wash trading, only a subset of them can be detected by automatic algorithms, and manual inspection is usually required. We propose NFTDisk, a novel visualization for investors to identify wash trading activities in NFT markets, where two linked visualization modules are presented: a radial visualization module with …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Integrated Organizational Machine Learning For Aviation Flight Data, Michael J. Pritchard, Paul Thomas, Eric Webb, Jon Martin, Austin Walden

National Training Aircraft Symposium (NTAS)

An increased availability of data and computing power has allowed organizations to apply machine learning techniques to various fleet monitoring activities. Additionally, our ability to acquire aircraft data has increased due to the miniaturization of small form factor computing machines. Aircraft data collection processes contain many data features in the form of multivariate time-series (continuous, discrete, categorical, etc.) which can be used to train machine learning models. Yet, three major challenges still face many flight organizations 1) integration and automation of data collection frameworks, 2) data cleanup and preparation, and 3) embedded machine learning framework. Data cleanup and preparation has …

A Novel Data Lineage Model For Critical Infrastructure And A Solution To A Special Case Of The Temporal Graph Reachability Problem, Ian Moncur

Graduate Theses and Dissertations

Rapid and accurate damage assessment is crucial to minimize downtime in critical infrastructure. Dependency on modern technology requires fast and consistent techniques to prevent damage from spreading while also minimizing the impact of damage on system users. One technique to assist in assessment is data lineage, which involves tracing a history of dependencies for data items. The goal of this thesis is to present one novel model and an algorithm that uses data lineage with the goal of being fast and accurate. In function this model operates as a directed graph, with the vertices being data items and edges representing …

Crest Or Trough? How Research Libraries Used Emerging Technologies To Survive The Pandemic, So Far, Scout Calvert

UNL Libraries: Faculty Publications

Introduction

In the first months of the COVID-19 pandemic, it was impossible to tell if we were at the crest of a wave of new transmissions, or a trough of a much larger wave, still yet to peak. As of this writing, as colleges and universities prepare for mostly in-person fall 2021 semesters, case counts in the United States are increasing again after a decline that coincided with easier access to the COVID vaccine. Plans for a return to campus made with confidence this spring may be in doubt, as we climb the curve of what is already the second …

Signal Processing And Data Analysis For Real-Time Intermodal Freight Classification Through A Multimodal Sensor System., Enrique J. Sanchez Headley

Graduate Theses and Dissertations

Identifying freight patterns in transit is a common need among commercial and municipal entities. For example, the allocation of resources among Departments of Transportation is often predicated on an understanding of freight patterns along major highways. There exist multiple sensor systems to detect and count vehicles at areas of interest. Many of these sensors are limited in their ability to detect more specific features of vehicles in traffic or are unable to perform well in adverse weather conditions. Despite this limitation, to date there is little comparative analysis among Laser Imaging and Detection and Ranging (LIDAR) sensors for freight detection …

Privacy-Preserving Cloud-Assisted Data Analytics, Wei Bao

Graduate Theses and Dissertations

Nowadays industries are collecting a massive and exponentially growing amount of data that can be utilized to extract useful insights for improving various aspects of our life. Data analytics (e.g., via the use of machine learning) has been extensively applied to make important decisions in various real world applications. However, it is challenging for resource-limited clients to analyze their data in an efficient way when its scale is large. Additionally, the data resources are increasingly distributed among different owners. Nonetheless, users' data may contain private information that needs to be protected.

Cloud computing has become more and more popular in …

Securing Fog Federation From Behavior Of Rogue Nodes, Mohammed Saleh H. Alshehri

Graduate Theses and Dissertations

As the technological revolution advanced information security evolved with an increased need for confidential data protection on the internet. Individuals and organizations typically prefer outsourcing their confidential data to the cloud for processing and storage. As promising as the cloud computing paradigm is, it creates challenges; everything from data security to time latency issues with data computation and delivery to end-users. In response to these challenges CISCO introduced the fog computing paradigm in 2012. The intent was to overcome issues such as time latency and communication overhead and to bring computing and storage resources close to the ground and the …

Lecture 11: The Road To Exascale And Legacy Software For Dense Linear Algebra, Jack Dongarra

Mathematical Sciences Spring Lecture Series

In this talk, we will look at the current state of high performance computing and look at the next stage of extreme computing. With extreme computing, there will be fundamental changes in the character of floating point arithmetic and data movement. In this talk, we will look at how extreme-scale computing has caused algorithm and software developers to change their way of thinking on implementing and program-specific applications.

Learning Adl Daily Routines With Spatiotemporal Neural Networks, Shan Gao, Ah-Hwee Tan, Rossi Setchi

Research Collection School Of Computing and Information Systems

The activities of daily living (ADLs) refer to the activities performed by individuals on a daily basis and are the indicators of a person’s habits, lifestyle, and wellbeing. Learning an individual’s ADL daily routines has significant value in the healthcare domain. Specifically, ADL recognition and inter-ADL pattern learning problems have been studied extensively in the past couple of decades. However, discovering the patterns performed in a day and clustering them into ADL daily routines has been a relatively unexplored research area. In this paper, a self-organizing neural network model, called the Spatiotemporal ADL Adaptive Resonance Theory (STADLART), is proposed for …

Deepmag+ : Sniffing Mobile Apps In Magnetic Field Through Deep Learning, Rui Ning, Cong Wang, Chunsheng Xin, Jiang Li, Hongyi Wu

Electrical & Computer Engineering Faculty Publications

This paper reports a new side-channel attack to smartphones using the unrestricted magnetic sensor data. We demonstrate that attackers can effectively infer the Apps being used on a smartphone with an accuracy of over 80%, through training a deep Convolutional Neural Networks (CNN). Various signal processing strategies have been studied for feature extractions, including a tempogram based scheme. Moreover, by further exploiting the unrestricted motion sensor to cluster magnetometer data, the sniffing accuracy can increase to as high as 98%. To mitigate such attacks, we propose a noise injection scheme that can effectively reduce the App sniffing accuracy to only …

Iomt Malware Detection Approaches: Analysis And Research Challenges, Mohammad Wazid, Ashok Kumar Das, Joel J.P.C. Rodrigues, Sachin Shetty, Youngho Park

VMASC Publications

The advancement in Information and Communications Technology (ICT) has changed the entire paradigm of computing. Because of such advancement, we have new types of computing and communication environments, for example, Internet of Things (IoT) that is a collection of smart IoT devices. The Internet of Medical Things (IoMT) is a specific type of IoT communication environment which deals with communication through the smart healthcare (medical) devices. Though IoT communication environment facilitates and supports our day-to-day activities, but at the same time it has also certain drawbacks as it suffers from several security and privacy issues, such as replay, man-in-the-middle, impersonation, …

Extracting Social Network From Literary Prose, Tarana Tasmin Bipasha

Graduate Theses and Dissertations

This thesis develops an approach to extract social networks from literary prose, namely, Jane Austen’s published novels from eighteenth- and nineteenth- century. Dialogue interaction plays a key role while we derive the networks, thus our technique relies upon our ability to determine when two characters are in conversation. Our process involves encoding plain literary text into the Text Encoding Initiative’s (TEI) XML format, character name identification, conversation and co-occurrence detection, and social network construction. Previous work in social network construction for literature have focused on drama, specifically manually TEI-encoded Shakespearean plays in which character interactions are much easier to track …

Identifying Regional Trends In Avatar Customization, Peter Mawhorter, Sercan Sengun, Haewoon Kwak, D. Fox Harrell

Research Collection School Of Computing and Information Systems

Since virtual identities such as social media profiles and avatars have become a common venue for self-expression, it has become important to consider the ways in which existing systems embed the values of their designers. In order to design virtual identity systems that reflect the needs and preferences of diverse users, understanding how the virtual identity construction differs between groups is important. This paper presents a new methodology that leverages deep learning and differential clustering for comparative analysis of profile images, with a case study of almost 100 000 avatars from a large online community using a popular avatar creation …

Reputation-Aware Trajectory-Based Data Mining In The Internet Of Things (Iot), Samia Tasnim

FIU Electronic Theses and Dissertations

Internet of Things (IoT) is a critically important technology for the acquisition of spatiotemporally dense data in diverse applications, ranging from environmental monitoring to surveillance systems. Such data helps us improve our transportation systems, monitor our air quality and the spread of diseases, respond to natural disasters, and a bevy of other applications. However, IoT sensor data is error-prone due to a number of reasons: sensors may be deployed in hazardous environments, may deplete their energy resources, have mechanical faults, or maybe become the targets of malicious attacks by adversaries. While previous research has attempted to improve the quality of …

Community Discovery In Heterogeneous Social Networks, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch

Research Collection School Of Computing and Information Systems

Discovering social communities of web users through clustering analysis of heterogeneous link associations has drawn much attention. However, existing approaches typically require the number of clusters a priori, do not address the weighting problem for fusing heterogeneous types of links, and have a heavy computational cost. This chapter studies the commonly used social links of users and explores the feasibility of the proposed heterogeneous data co-clustering algorithm GHF-ART, as introduced in Sect. 3.6, for discovering user communities in social networks. Contrary to the existing algorithms proposed for this task, GHF-ART performs real-time matching of patterns and one-pass learning, which guarantees …

Applications Of Fog Computing In Video Streaming, Kyle Smith

Computer Science and Computer Engineering Undergraduate Honors Theses

The purpose of this paper is to show the viability of fog computing in the area of video streaming in vehicles. With the rise of autonomous vehicles, there needs to be a viable entertainment option for users. The cloud fails to address these options due to latency problems experienced during high internet traffic. To improve video streaming speeds, fog computing seems to be the best option. Fog computing brings the cloud closer to the user through the use of intermediary devices known as fog nodes. It does not attempt to replace the cloud but improve the cloud by allowing faster …

The Global Disinformation Order: 2019 Global Inventory Of Organised Social Media Manipulation, Samantha Bradshaw, Philip N. Howard

Copyright, Fair Use, Scholarly Communication, etc.

Executive Summary

Over the past three years, we have monitored the global organization of social media manipulation by governments and political parties. Our 2019 report analyses the trends of computational propaganda and the evolving tools, capacities, strategies, and resources.

1. Evidence of organized social media manipulation campaigns which have taken place in 70 countries, up from 48 countries in 2018 and 28 countries in 2017. In each country, there is at least one political party or government agency using social media to shape public attitudes domestically.

2.Social media has become co-opted by many authoritarian regimes. In 26 countries, computational propaganda …

Deep Unsupervised Pixelization, Chu Han, Qiang Wen, Shengfeng He, Qianshu Zhu, Yinjie Tan, Guoqiang Han, Tien-Tsin Wong

Research Collection School Of Computing and Information Systems

In this paper, we present a novel unsupervised learning method for pixelization. Due to the difficulty in creating pixel art, preparing the paired training data for supervised learning is impractical. Instead, we propose an unsupervised learning framework to circumvent such difficulty. We leverage the dual nature of the pixelization and depixelization, and model these two tasks in the same network in a bi-directional manner with the input itself as training supervision. These two tasks are modeled as a cascaded network which consists of three stages for different purposes. GridNet transfers the input image into multi-scale grid-structured images with different aliasing …

User-Centric Privacy Preservation In Mobile And Location-Aware Applications, Mingming Guo

FIU Electronic Theses and Dissertations

The mobile and wireless community has brought a significant growth of location-aware devices including smart phones, connected vehicles and IoT devices. The combination of location-aware sensing, data processing and wireless communication in these devices leads to the rapid development of mobile and location-aware applications. Meanwhile, user privacy is becoming an indispensable concern. These mobile and location-aware applications, which collect data from mobile sensors carried by users or vehicles, return valuable data collection services (e.g., health condition monitoring, traffic monitoring, and natural disaster forecasting) in real time. The sequential spatial-temporal data queries sent by users provide their location trajectory information. The …

Keep It Simple, Keep It Safe - Research On The Impacts Of Increasing Complexity Of Modern Enterprise Applications, Shawn Ware, David Phillips

UNO Student Research and Creative Activity Fair

As the Cybersecurity program within UNO continues to adapt to the ever-changing world of information systems and information security, the Cybersecurity Capstone has recently become an active, community-involvement project, where real-world organizations can receive valuable, useful research and information from students on their way towards a degree. This presentation encompasses two such projects from the Cybersecurity Capstone, looking at how modern, more complex systems can often increase system vulnerability.

Cyber Security And Risk Society: Estonian Discourse On Cyber Risk And Security Strategy, Lauren Kook

Copyright, Fair Use, Scholarly Communication, etc.

The main aim of this thesis is to call for a new analysis of cyber security which departs from the traditional security theory. I argue that the cyber domain is inherently different in nature, in that it is lacking in traditional boundaries and is reflexive in nature. Policy-makers are aware of these characteristics, and in turn this awareness changes the way that national cyber security strategy is handled and understood. These changes cannot be adequately understood through traditional understanding of security, as they often are, without missing significant details. Rather, examining these changes through the lens of Ulrich Beck’s risk …

Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang

Department of Computer Science Faculty Scholarship and Creative Works

As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …

Lightweight Data Aggregation Scheme Against Internal Attackers In Smart Grid Using Elliptic Curve Cryptography, Debiao He, Sherali Zeadally, Huaqun Wang, Qin Liu

Information Science Faculty Publications

Recent advances of Internet and microelectronics technologies have led to the concept of smart grid which has been a widespread concern for industry, governments, and academia. The openness of communications in the smart grid environment makes the system vulnerable to different types of attacks. The implementation of secure communication and the protection of consumers’ privacy have become challenging issues. The data aggregation scheme is an important technique for preserving consumers’ privacy because it can stop the leakage of a specific consumer’s data. To satisfy the security requirements of practical applications, a lot of data aggregation schemes were presented over the …