Computer Sciences Commons^™

Beyond The Classroom - What Students Need To Know, Will Alexander

KSU Proceedings on Cybersecurity Education, Research and Practice

No abstract provided.

A New Framework For Securing, Extracting And Analyzing Big Forensic Data, Hitesh Sachdev, Hayden Wimmer, Lei Chen, Carl Rebman

Journal of Digital Forensics, Security and Law

Finding new methods to investigate criminal activities, behaviors, and responsibilities has always been a challenge for forensic research. Advances in big data, technology, and increased capabilities of smartphones has contributed to the demand for modern techniques of examination. Smartphones are ubiquitous, transformative, and have become a goldmine for forensics research. Given the right tools and research methods investigating agencies can help crack almost any illegal activity using smartphones. This paper focuses on conducting forensic analysis in exposing a terrorist or criminal network and introduces a new Big Forensic Data Framework model where different technologies of Hadoop and EnCase software are …

Disruptive Technology: Can The Banking Industry Harness Disruption For Competitive Edge?, Edgar Low

MITB Thought Leadership Series

Disruptive innovation was identified as a phenomenon more than two decades ago by prominent Harvard scholar Clayton Christensen. So you may wonder why established industries are only now waking up to the prospect of digital transformation - the banking industry in particular.

Management Of It (Ksu), Rebecca Rutherfoord, Dawn Tatum, Susan Vandeven, Richard Halstead-Nussloch, James Rutherfoord, Zhigang Li

Computer Science and Information Technology Grants Collections

This Grants Collection for Management of IT was created under a Round Eleven ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report

I4s: Capturing Shopper’S In-Store Interactions, Sougata Sen, Archan Misra, Vigneshwaran Subbaraju, Karan Grover, Meeralakshmi Radhakrishnan, Rajesh K. Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

In this paper, we present I4S, a system that identifies item interactions of customers in a retail store through sensor data fusion from smartwatches, smartphones and distributed BLE beacons. To identify these interactions, I4S builds a gesture-triggered pipeline that (a) detects the occurrence of “item picks”, and (b) performs fine-grained localization of such pickup gestures. By analyzing data collected from 31 shoppers visiting a mid-sized stationary store, we show that we can identify person-independent picking gestures with a precision of over 88%, and identify the rack from where the pick occurred with 91%+ precision (for popular racks).

Research Innovation And Institutional Growth: Digital Humanities, Usm, And The University Of Maine System, Janet M. Billson, Katherine Bessey

Research Innovation and Institutional Growth

No abstract provided.

Minutes & Seconds: The Scientists, Patrick Aievoli

Zea E-Books Collection

Minutes & Seconds, is a captivating intelligible read for those who strive to understand where the “what if” moment has gone. Succeeding his other captivating books, Aievoli’s deep introspective lens dials his readers in to awaken the proverbial sleeping giant inside of our consciousness. He designs an insightful exciting romp through the surreal landscape of our society and illustrates how various pioneers have lead us to a crossroads. I’m truly impressed with Aievoli’s perspicacious comprehension of where digital has taken us through the hands of these select individuals. --Sequoyah Wharton

In creating Minutes & Seconds, Aievoli has assembled an interesting …

Breaking Down The Barriers To Operator Workload Estimation: Advancing Algorithmic Handling Of Temporal Non-Stationarity And Cross-Participant Differences For Eeg Analysis Using Deep Learning, Ryan G. Hefron

Theses and Dissertations

This research focuses on two barriers to using EEG data for workload assessment: day-to-day variability, and cross- participant applicability. Several signal processing techniques and deep learning approaches are evaluated in multi-task environments. These methods account for temporal, spatial, and frequential data dependencies. Variance of frequency- domain power distributions for cross-day workload classification is statistically significant. Skewness and kurtosis are not significant in an environment absent workload transitions, but are salient with transitions present. LSTMs improve day- to-day feature stationarity, decreasing error by 59% compared to previous best results. A multi-path convolutional recurrent model using bi-directional, residual recurrent layers significantly increases …

A Strategic Value Appropriation Path For Cloud Computing, Abhishek Kathuria, Arti Mann, Jiban Khuntia, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

Cloud-based information management is one of the leading competitive differentiation strategies for firms. With the increasing criticality of information management in value creation and process support, establishing an integrated capability with cloud computing is vital for organizational success in the changing landscape of business competition. These issues have received scant attention, however. We draw on the resource-based view, dynamic capability hierarchy concepts, and the perspective of operand and operant resources to suggest a cloud value appropriation model for firms. We argue that, to appropriate business value from cloud computing, the firm needs to effectively deploy cloud computing and leverage cloud …

Talent Flow Analytics In Online Professional Network, Richard J. Oentaryo, Ee-Peng Lim, Xavier Jayaraj Siddarth Ashok, Philips Kokoh Prasetyo

Research Collection School Of Computing and Information Systems

Analyzing job hopping behavior is important for understanding job preference and career progression of working individuals. When analyzed at the workforce population level, job hop analysis helps to gain insights of talent flow among different jobs and organizations. Traditionally, surveys are conducted on job seekers and employers to study job hop behavior. Beyond surveys, job hop behavior can also be studied in a highly scalable and timely manner using a data-driven approach in response to fast-changing job landscape. Fortunately, the advent of online professional networks (OPNs) has made it possible to perform a large-scale analysis of talent flow. In this …

Blockchain Based Efficient And Robust Fair Payment For Outsourcing Services In Cloud Computing, Yinghui Zhang, Robert H. Deng, Ximeng Liu, Dong Zheng

Research Collection School Of Computing and Information Systems

As an attractive business model of cloud computing, outsourcing services usually involve online payment and security issues. The mutual distrust between users and outsourcing service providers may severely impede the wide adoption of cloud computing. Nevertheless, most existing payment solutions only consider a specific type of outsourcing service and rely on a trusted third-party to realize fairness. In this paper, in order to realize secure and fair payment of outsourcing services in general without relying on any third-party, trusted or not, we introduce BCPay, a blockchain based fair payment framework for outsourcing services in cloud computing. We first present the …

Cognitive Antecedents Of Family Business Bias In Investment Decisions: A Commentary On 'Risky Decisions And The Family Firm Bias: An Experimental Study Based On Prospect Theory, H. Fang, Keng Siau, E. Memili, J. Dou

Research Collection School Of Computing and Information Systems

Lude and Prügl explored “family business bias,” a cognitive tendency where the family nature of a firm can often reduce investors’ perceived risk in investments. As a result, investors would display lower risk-avoidance in the gain domain and reinforced risk-seeking in the loss domain. We expanded the authors’ work by introducing four cognitive factors (anchoring, representativeness, stereotype heuristic, and information availability) that can explain the underlying mechanisms behind the prevalence of “family business bias” and other cognitive misperceptions surrounding family businesses when it comes to investment decisions.

Trajectory-Driven Influential Billboard Placement, Ping Zhang, Zhifeng Bao, Yuchen Li, Guoliang Li, Yipeng Zhang, Zhiyong Peng

Research Collection School Of Computing and Information Systems

In this paper we propose and study the problem of trajectory-driven influential billboard placement: given a set of billboards U (each with a location and a cost), a database of trajectories T and a budget L, find a set of billboards within the budget to influence the largest number of trajectories. One core challenge is to identify and reduce the overlap of the influence from different billboards to the same trajectories, while keeping the budget constraint into consideration. We show that this problem is NP-hard and present an enumeration based algorithm with (1−1/e) approximation ratio. However, the enumeration should be …

Transaction Cost Optimization For Online Portfolio Selection, Bin Li, Jialei Wang, Dingjiang Huang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

To improve existing online portfolio selection strategies in the case of non-zero transaction costs, we propose a novel framework named Transaction Cost Optimization (TCO). The TCO framework incorporates the L1 norm of the difference between two consecutive allocations together with the principles of maximizing expected log return. We further solve the formulation via convex optimization, and obtain two closed-form portfolio update formulas, which follow the same principle as Proportional Portfolio Rebalancing (PPR) in industry. We empirically evaluate the proposed framework using four commonly used data-sets. Although these data-sets do not consider delisted firms and are thus subject to survival bias, …

Why Accountants Should Embrace Machine Learning?, Benjamin Huan Zhou Lee, Gary Pan, Poh Sun Seow

Research Collection School Of Accountancy

AI and ML are enabling tools that take the tedious gruntwork out of accounting, freeing up professionals to provide valuable insights - as well as professional scepticism - which are sought-after services no machine can replicate.

Esg And Corporate Financial Performance: Empirical Evidence From China's Listed Power Generation Companies, Changhong Zhao, Yu Guo, Jiahai Yuan, Mengya Wu, Daiyu Li, Yiou Zhou, Jiangang Kang

Research Collection School Of Computing and Information Systems

Nowadays, listed companies around the world are shifting from short-term goals of maximizing profits to long-term sustainable environmental, social, and governance (ESG) goals. People have come to realize that ESG has become an important source of the corporate risk and may affect the company's financial performance and profitability. Recent research shows that good ESG performance could improve the financial performance in some countries. Yet, the question of how does ESG affect financial performance has not been thoroughly discussed and studied in China. In this article, we study China's listed power generation groups to explore the relationship between ESG performance and …

Customer Level Predictive Modeling For Accounts Receivable To Reduce Intervention Actions, Michelle L. F. Cheong, Wen Shi

Research Collection School Of Computing and Information Systems

One of the main costs associated with Accounts receivable (AR) collection is related to the intervention actions taken to remind customers to pay their outstanding invoices. Apart from the cost, intervention actions may lead to poor customer satisfaction, which is undesirable in a competitive industry. In this paper, we studied the payment behavior of invoices for customers of a logistics company, and used predictive modeling to predict if a customer will pay the outstanding invoices with high probability, in an attempt to reduce intervention actions taken, thus reducing cost and improving customer relationship. We defined a pureness measure to classify …

Cryptovisor: A Cryptocurrency Advisor Tool, Matthew Baldree, Paul Widhalm, Brandon Hill, Matteo Ortisi

SMU Data Science Review

In this paper, we present a tool that provides trading recommendations for cryptocurrency using a stochastic gradient boost classifier trained from a model labeled by technical indicators. The cryptocurrency market is volatile due to its infancy and limited size making it difficult for investors to know when to enter, exit, or stay in the market. Therefore, a tool is needed to provide investment recommendations for investors. We developed such a tool to support one cryptocurrency, Bitcoin, based on its historical price and volume data to recommend a trading decision for today or past days. This tool is 95.50% accurate with …

Experiential Learning Builds Cybersecurity Self-Efficacy In K-12 Students, Abdullah Konak

Journal of Cybersecurity Education, Research and Practice

In recent years, there have been increased efforts to recruit talented K-12 students into cybersecurity fields. These efforts led to many K-12 extracurricular programs organized by higher education institutions. In this paper, we first introduce a weeklong K-12 program focusing on critical thinking, problem-solving, and igniting interest in information security through hands-on activities performed in a state-of-the-art virtual computer laboratory. Then, we present an inquiry-based approach to design hands-on activities to achieve these goals. We claim that hands-on activities designed based on this inquiry-based framework improve K-12 students’ self-efficacy in cybersecurity as well as their problem-solving skills. The evaluation of …

Student Misconceptions About Cybersecurity Concepts: Analysis Of Think-Aloud Interviews, Julia D. Thompson, Geoffrey L. Herman, Travis Scheponik, Linda Oliva, Alan Sherman, Ennis Golaszewski, Dhananjay Phatak, Kostantinos Patsourakos

Journal of Cybersecurity Education, Research and Practice

We conducted an observational study to document student misconceptions about cybersecurity using thematic analysis of 25 think-aloud interviews. By understanding patterns in student misconceptions, we provide a basis for developing rigorous evidence-based recommendations for improving teaching and assessment methods in cybersecurity and inform future research. This study is the first to explore student cognition and reasoning about cybersecurity. We interviewed students from three diverse institutions. During these interviews, students grappled with security scenarios designed to probe their understanding of cybersecurity, especially adversarial thinking. We analyzed student statements using a structured qualitative method, novice-led paired thematic analysis, to document patterns in …

"Think Before You Click. Post. Type." Lessons Learned From Our University Cyber Security Awareness Campaign, Rachael L. Innocenzi, Kaylee Brown, Peggy Liggit, Samir Tout, Andrea Tanner, Theodore Coutilish, Rocky J. Jenkins

Journal of Cybersecurity Education, Research and Practice

This article discusses the lessons learned after implementing a successful university-wide cyber security campaign. The Cyber Security Awareness Committee (CyberSAC), a group comprised of diverse units across campus, collaborated together on resources, talent, people, equipment, technology, and assessment practices to meet strategic goals for cyber safety and education. The project involves assessing student learning and behavior changes after participating in a Cyber Security Password Awareness event that was run as a year-long campaign targeting undergraduate students. The results have implications for planning and implementing university-wide initiatives in the field of cyber security, and more broadly, higher education at large.

Voice Hacking: Using Smartphones To Spread Ransomware To Traditional Pcs, Bryson R. Payne, Leonardo I. Mazuran, Tamirat Abegaz

Journal of Cybersecurity Education, Research and Practice

This paper presents a voice hacking proof of concept that demonstrates the ability to deploy a sequence of hacks, triggered by speaking a smartphone command, to launch ransomware and other destructive attacks against vulnerable Windows computers on any wireless network the phone connects to after the voice command is issued. Specifically, a spoken, broadcast, or pre-recorded voice command directs vulnerable Android smartphones or tablets to a malicious download page that compromises the Android device and uses it as a proxy to run software designed to scan the Android device’s local area network for Windows computers vulnerable to the EternalBlue exploit, …

A Case Study In The Implementation Of A Human-Centric Higher Education Cybersecurity Program, John W. Coffey, Melanie Haveard, Geissler Golding

Journal of Cybersecurity Education, Research and Practice

This article contains a description of the implementation of a comprehensive cyber security program at a regional comprehensive university. The program was designed to create an effective cyber security management infrastructure and to train end users and other categories of security management personnel in data protection and cyber security. This work addresses the impetus for the program, the rather extensive planning and development that went into the program, its implementation, and insights gleaned from the experience. The paper concludes with a summary of the strengths and weaknesses of the initiative.

From The Editors, Michael E. Whitman, Herbert J. Mattord, Carole L. Hollingsworth

Journal of Cybersecurity Education, Research and Practice

Welcome to the Spring 2018 issue of the Journal of Cybersecurity Education, Research, and Practice (JCERP). On behalf of the editorial team, we thank you for taking the time to read this issue and strongly encourage you to submit an article for consideration in an upcoming edition.

Feeling Ai

SIGNED: The Magazine of The Hong Kong Design Institute

We all develop emotional connections to the devices we use; the smartphone that is a constant companion or the office printer that is a constant source of frustration. Soon, these machines might be able to respond in kind

Analytics For Novel Consumer Insights (A Three Essay Dissertation), Utkarsh Shrivastava

USF Tampa Graduate Theses and Dissertations

Both literature and practice have investigated how the vast amount of ever increasing customer information can inform marketing strategy and decision making. However, the customer data is often susceptible to modeling bias and misleading findings due to various factors including sample selection and unobservable variables. The available analytics toolkit has continued to develop but in the age of nearly perfect information, the customer decision making has also evolved. The dissertation addresses some of the challenges in deriving valid and useful consumer insights from customer data in the digital age. The first study addresses the limitations of traditional customer purchase measures …

App-Titude Test: Reviewing Productivity-Boosting And Anxiety-Busting Apps, Nurin Nazifa Binte Mohd Yusoff

Social Space

Self-improvement apps have been on the market for a while, but judging from the general lack of reviews, not many have been put to the test. For this edition ofThe Short List, I downloaded five mobile applicationsclaiming to enhance productivity and lower anxiety levels, and tried them out over the course of a few weeks. Am I now more productive and relaxed? Maybe.But were they app-solutely essential? Read on to find out.

Is Information Systems Misuse Always Bad? A New Perspective On Is Misuse In Hospitals Under The Context Of Disasters, Dheyaaldin Alsalman

Masters Theses & Doctoral Dissertations

Although the extant literature has investigated how individuals engage in inappropriate behaviors based on the rational choice theory (RCT) (e.g., computer misconduct), the neutralization theory (e.g., IS security policies violation), and workarounds under normal situations, it has given little consideration to how individuals are involved in misuse of information systems with a good intention under the context of disasters. To fill this research gap, we propose a selfless misuse model, which offers a theoretical explanation for the concept of individuals’ selfless misuse intention under uncertainty caused by disasters. In this study, we show why employees make decisions to misuse the …

Hybrid Recommender For Online Petitions With Social Network And Psycholinguistic Features, Ahmed Elnoshokaty

Masters Theses & Doctoral Dissertations

The online petition has become one of the most important channels of civic participation. Most of the state-of-the-art online platforms, however, tend to use simple indicators (such as popularity) to rank petitions, hence creating a situation where the most popular petitions dominate the rank and attract most people’s attention. For the petitions which focus on specific issues, they are often in a disadvantageous position on the list. For example, a petition for local environment problem may not be seen by many people who are really concerned with it, simply because it takes multiple pages to reach it. Therefore, the simple …

Supervision In The Workplace (Clayton), Sheryne Southard, Christie Burton, Bryan Labrecque, Xueyu Cheng, Elnora Farmer

Computer Science and Information Technology Grants Collections

This Grants Collection for Supervision in the Workplace was created under a Round Ten ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report