Computer Engineering Commons^™

Development Of A National Repository Of Digital Forensic Intelligence, Mark Weiser, David P. Biros, Greg Mosier

Annual ADFSL Conference on Digital Forensics, Security and Law

Many people do all of their banking online, we and our children communicate with peers through computer systems, and there are many jobs that require near continuous interaction with computer systems. Criminals, however, are also “connected”, and our online interaction provides them a conduit into our information like never before. Our credit card numbers and other fiscal information are at risk, our children's personal information is exposed to the world, and our professional reputations are on the line.

The discipline of Digital Forensics in law enforcement agencies around the nation and world has grown to match the increased risk and …

Designing A Data Warehouse For Cyber Crimes, Il-Yeol Song, John D. Maguire, Ki Jung Lee, Namyoun Choi, Xiaohua Hu, Peter Chen

Annual ADFSL Conference on Digital Forensics, Security and Law

One of the greatest challenges facing modern society is the rising tide of cyber crimes. These crimes, since they rarely fit the model of conventional crimes, are difficult to investigate, hard to analyze, and difficult to prosecute. Collecting data in a unified framework is a mandatory step that will assist the investigator in sorting through the mountains of data. In this paper, we explore designing a dimensional model for a data warehouse that can be used in analyzing cyber crime data. We also present some interesting queries and the types of cyber crime analyses that can be performed based on …

Patent Reexamination Post Litigation: It's Time To Set The Rules Straight, Tremesha S. Willis

Georgia Journal of Law & Technology

No abstract provided.

Development Of A Wireless Environmental Data Acquisition Prototype Adopting Agile Practices: An Experience Report, Paul Celicourt, Richard Sam, Michael Piasecki

Publications and Research

The traditional software development model commonly named “waterfall” is unable to cope with the increasing functionality and complexity of modern embedded systems. In addition, it is unable to support the ability for businesses to quickly respond to new market opportunities due to changing requirements. As a response, the software development community developed the Agile Methodologies (e.g., extreme Programming, Scrum) which were also adopted by the Embedded System community. However, failures and bad experiences in applying Agile Methodologies to the development of embedded systems have not been reported in the literature. Therefore, this paper contributes a detailed account of our first-time …

Towards A Development Of A Mobile Application Security Invasiveness Index, Sam Espana

KSU Proceedings on Cybersecurity Education, Research and Practice

The economic impact of Mobile IP, the standard that allows IP sessions to be maintained even when switching between different cellular towers or networks, has been staggering in terms of both scale and acceleration (Doherty, 2016). As voice communications transition to all-digital, all-IP networks such as 4G, there will be an increase in risk due to vulnerabilities, malware, and hacks that exist for PC-based systems and applications (Harwood, 2011). According to Gostev (2006), in June, 2004, a well-known Spanish virus collector known as VirusBuster, emailed the first known mobile phone virus to Kaspersky Lab, Moscow. Targeting the Symbian OS, the …

Studying The Effects Of Serpentine Soil On Adapted And Non-Adapted Species Using Arduino Technology, Kiana Saniee, Edward Himelblau, Brian Paavo

STAR Program Research Presentations

Abstract: Serpentine soils are formed from ultramafic rocks and are represent an extreme environment for plants. Serpentine soils are unique in that they carry high concentrations of heavy metals, are nutrient deficient, particularly in calcium, and have poor water retention capabilities. Although these soils constitute harsh conditions for plant growth, there are a number of species that are adapted and even endemic to serpentine soil. Water retention by commercial potting mix was compared with serpentine soil. Also, serpentine adapted and non-adapted species were grown in both soil treatments and physiological data were collected. We used the Arduino electronic platform to …

A Comparison Of X86 Computer Architecture Simulators, Ayaz Akram, Lina Sawalha

Computer Architecture and Systems Research Laboratory (CASRL)

The significance of computer architecture simulators in advancing computer architecture research is widely acknowledged. Computer architects have developed numerous simulators in the past few decades and their number continues to rise. This paper explores different simulation techniques and surveys many simulators. Comparing simulators with each other and validating their correctness has been a challenging task. In this paper, we compare and contrast x86 simulators in terms of flexibility, level of details, user friendliness and simulation models. In addition, we measure the experimental error and compare the speed of four contemporary x86 simulators: gem5, Sniper, Multi2sim and PTLsim. We also discuss …

2016 (Fall) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the fall of 2016.

Content Mining Techniques For Detecting Cyberbullying In Social Media, Shawniece L. Parker, Yen-Hung Hu

Virginia Journal of Science

The use of social media has become an increasingly popular trend, primarily among teenagers. A major problem concerning teens using social media is that they are often unaware of the dangers involved when using these media. They are also more inclined to misuse social media because they are often unaware of the privacy rights associated with their use, or the rights of other users. As a result, cyberbullying cases have steadily risen in recent years, often going undiscovered or not being discovered until serious harm has been caused to the victims. This study aims to create an effective algorithm that …

An Exploration Of Mobile Device Security Artifacts At Institutions Of Higher Education, Amita Goyal Chin, Diania Mcrae, Beth H. Jones, Mark A. Harris

Journal of International Technology and Information Management

The explosive growth and rapid proliferation of smartphones and other mobile

devices that access data over communication networks has necessitated advocating

and implementing security constraints for the purpose of abetting safe computing.

Remote data access using mobile devices is particularly popular among students at

institutions of higher education. To ensure safe harbor for constituents, it is

imperative for colleges and universities to establish, disseminate, and enforce

mobile device security artifacts, where artifacts is defined as policies, procedures,

guidelines or other documented or undocumented protocols. The purpose of this

study is to explore the existence of, specific content of, and the …

Motivations For Social Network Site (Sns) Gaming: A Uses And Gratification & Flow Perspective, Brinda Sampat, Bala Krishnamoorthy

Journal of International Technology and Information Management

The penetration of the internet, smart-phones and tablets has witnessed tremendous increase in the number of people playing online games in the past few years. Social networking site (SNS) games are a subset of digital games. They are platform based, multiplayer and reveal the real identity of the player. These games are hosted on social networks such as Facebook, where in people play with many other players online. The risks associated with social network gaming are addiction, theft, fraud, loneliness, anxiety, aggression, poor academic performance, cognition distortion etc. This study aims to understand the user motivations to continue to play …

The Impact Of Analytics Utilization On Team Performance: Comparisons Within And Across The U.S. Professional Sports Leagues, Lee A. Freeman

Journal of International Technology and Information Management

Business analytics, defined as the use of data to make better, more relevant, evidence-based business decisions, has received a great deal of attention in practitioner circles. Organizations have adopted business analytics in an effort to improve revenue, product placement, and customer satisfaction. Professional sports teams are no different. While analytics has been used for over 30 years, the use of analytics by professional sports teams is a relatively new concept. However, it is unclear whether the teams that have adopted analytics are seeing any results. If not, then perhaps analytics is not the right solution. Analyses across the four, major …

Region-Based Approach For Single Image Super-Resolution, Min Zhang

Electrical & Computer Engineering Theses & Dissertations

Single image super-resolution (SR) is a technique that generates a high- resolution image from a single low-resolution image [1,2,10,11]. Single image super- resolution can be generally classified into two groups: example-based and self-similarity based SR algorithms. The performance of the example-based SR algorithm depends on the similarity between testing data and the database. Usually, a large database is needed for better performance in general. This would result in heavy computational cost. The self-similarity based SR algorithm can generate a high-resolution (HR) image with sharper edges and fewer ringing artifacts if there is sufficient recurrence within or across scales of the …

Support Vector Machines And Artificial Neural Networks: Assessing The Validity Of Using Technical Features For Security Forecasting, James Dipadua

Dissertations

Stock forecasting is an enticing and well-studied problem in both finance and machine learning literature with linear-based models such as ARIMA and ARCH to non-linear Artificial Neural Networks (ANN) and Support Vector Machines (SVM). However, these forecasting techniques also use very different input features, some of which are seen by economists as irrational and theoretically unjustified. In this comparative study using ANNs and SVMs for 12 publicly traded companies, derivative price “technicals” are evaluated against macro- and microeconomic fundamentals to evaluate the efficacy of model performance. Despite the efficient market hypothesis positing the ill-suitability of technicals as model inputs, this …

Data Fusion For Vision-Based Robotic Platform Navigation, Andrés F. Echeverri

Master's Theses (2009 -)

Data fusion has become an active research topic in recent years. Growing computational performance has allowed the use of redundant sensors to measure a single phenomenon. While Bayesian fusion approaches are common in general applications, the computer vision community has largely relegated this approach. Most object following algorithms have gone towards pure machine learning fusion techniques that tend to lack flexibility. Consequently, a more general data fusion scheme is needed. The motivation for this work is to propose methods that allow for the development of simple and cost effective, yet robust visual following robots capable of tracking a general object …

A Data-Centric Analysis On Stem Majoring And Success: Attitude And Readiness, Xin James He, Myron Sheu, Jie Tao

Journal of International Technology and Information Management

This research studies attitude and readiness of STEM majoring and success with

the data from a survey with a total of 501 viable responses, with respect to STEM

(science, technology, engineering, and mathematics) related majors that are

essential and fundamental to skills relevant to big data business analytics.

Recruiting and keeping students in STEM areas have attracted a large body of

attention in pedagogical studies. An effective way of achieving such a goal is to

show them how rewarding and self-fulfilling STEM careers can be toward

perspective students. One example of the abundance of STEM careers is the rapid

growth …

Prediction And Recommendations On The It Leaners' Learning Path As A Collective Intelligence Using A Data Mining Technique, Seong-Yong Hong, Juyun Cho, Yonghyun Hwang

Journal of International Technology and Information Management

With the recent advances in computer technology along with pervasive internet accesses, data analytics is getting more attention than ever before. In addition, research areas on data analysis are diverging and integrating lots of different fields such as a business and social sector. Especially, recent researches focus on the data analysis for a better intelligent decision making and prediction system. This paper analyzes data collected from current IT learners who have already studied various IT subjects to find the IT learners’ learning patterns. The most popular learning patterns are identified through an association rule data mining using an arules package …

Computer Software Release: Open Photo Roster, Szymon Machajewski

Open Teaching Tools

Learning student names in a classroom course is important to creating an inclusive learning environment. Some Learning Management Systems, like Blackboard Learn, provide tools for student images, but such tools are insufficient. This software project creates a consistent and reliable way of identifying students for the needs of proctored exams as well as for learning student names.

Violating Of Individual Privacy: Moroccan Perceptions Of The Ban Of Voip Services, Tyler Delhees

Independent Study Project (ISP) Collection

On January 6, 2016, the Moroccan telecommunications regulatory agency, the ANRT, announced a ban onVoice Over Internet Protocol(VoIP) calling services such as Skype, WhatsApp, and Viber. The ban triggered sweeping opposition among the Moroccan public, opening discussion of digital rights, censorship, and Internet governance. Considering liberal democratic rights in the 2011 Moroccan Constitution and a history of censorship, this study analyzes the official justification of the ANRT alongside additional explanations involving business interests and the security services. The purpose of this study is to gauge the perceptions of Moroccans on the decision of the ANRT and provide a holistic explanation. …

Repmatch: Robust Feature Matching And Pose For Reconstructing Modern Cities, Wen-Yan Lin, Siying Liu, Minh N. Do, Ping Tan, Jiangbo Lu

Research Collection School Of Computing and Information Systems

A perennial problem in recovering 3-D models from images is repeated structures common in modern cities. The problem can be traced to the feature matcher which needs to match less distinctive features (permitting wide-baselines and avoiding broken sequences), while simultaneously avoiding incorrect matching of ambiguous repeated features. To meet this need, we develop RepMatch, an epipolar guided (assumes predominately camera motion) feature matcher that accommodates both wide-baselines and repeated structures. RepMatch is based on using RANSAC to guide the training of match consistency curves for differentiating true and false matches. By considering the set of all nearest-neighbor matches, RepMatch can …

Special Issue On Cyberharassment Investigation: Advances And Trends, Joanne Bryce, Virginia N. L. Franqueira, Andrew Marrington

Journal of Digital Forensics, Security and Law

Empirical and anecdotal evidence indicates that cyberharassment is more prevalent as the use of social media becomes increasingly widespread, making geography and physical proximity irrelevant. Cyberharassment can take different forms (e.g., cyberbullying, cyberstalking, cybertrolling), and be motivated by the objectives of inflicting distress, exercising control, impersonation, and defamation. Little is currently known about the modus operandi of offenders and their psychological characteristics. Investigation of these behaviours is particularly challenging because it involves digital evidence distributed across the devices of both alleged offenders and victims, as well as online service providers, sometimes over an extended period of time. This special issue …

The Impact Of Low Self-Control On Online Harassment: Interaction With Opportunity., Hyunin Baek, Michael M. Losavio, George E. Higgins

Journal of Digital Forensics, Security and Law

Developing Internet technology has increased the rates of youth online harassment. This study examines online harassment from adolescents with low self-control and the moderating effect of opportunity. The data used in this study were collected by the Korea Institute of Criminology in 2009. The total sample size was 1,091. The results indicated that low self-control, opportunity, and gender have a significant influence on online harassment. However, these results differed according to gender; for males, low self-control significantly impacted online harassment; for females, however, only low self-control significantly impacted online harassment. Furthermore, the interaction between low self-control and opportunity did not …

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

A Legal Examination Of Revenge Pornography And Cyber-Harassment, Thomas Lonardo, Tricia Martland, Doug White

Journal of Digital Forensics, Security and Law

This paper examines the current state of the statutes in the United States as they relate to cyber-harassment in the context of "revenge porn". Revenge porn refers to websites which cater to those wishing to exploit, harass, or otherwise antagonize their ex partners using pornographic images and videos which were obtained during their relationships. The paper provide examples and illustrations as well as a summary of current statute in the United States. The paper additionally explores some of the various legal remedies available to victims of revenge pornography.

Differentiating Cyberbullies And Internet Trolls By Personality Characteristics And Self-Esteem, Lauren A. Zezulka, Kathryn C. Seigfried-Spellar

Journal of Digital Forensics, Security and Law

Cyberbullying and internet trolling are both forms of online aggression or cyberharassment; however, research has yet to assess the prevalence of these behaviors in relationship to one another. In addition, the current study was the first to investigate whether individual differences and self-esteem discerned between self-reported cyberbullies and/or internet trolls (i.e., Never engaged in either, Cyberbully-only, Troll-only, Both Cyberbully and Troll). Of 308 respondents solicited from Mechanical Turk, 70 engaged in cyberbullying behaviors, 20 engaged in only trolling behaviors, 129 self-reported both behaviors, and 89 self-reported neither behavior. Results yielded low self-esteem, low conscientiousness, and low internal moral values for …

Toward Online Linguistic Surveillance Of Threatening Messages, Brian H. Spitzberg, Jean Mark Gawron

Journal of Digital Forensics, Security and Law

Threats are communicative acts, but it is not always obvious what they communicate or when they communicate imminent credible and serious risk. This paper proposes a research- and theory-based set of over 20 potential linguistic risk indicators that may discriminate credible from non-credible threats within online threat message corpora. Two prongs are proposed: (1) Using expert and layperson ratings to validate subjective scales in relation to annotated known risk messages, and (2) Using the resulting annotated corpora for automated machine learning with computational linguistic analyses to classify non-threats, false threats, and credible threats. Rating scales are proposed, existing threat corpora …

After The Avalanche: The Post-Snowden Intelligence Politics Between The United States, The United Kingdom, And Germany, Jobel Kyle P. Vecino

Claremont-UC Undergraduate Research Conference on the European Union

The revelations of PRISM and XKeyscore by ex-National Security Agency (NSA) analyst Edward Snowden resulted in arguably the largest intelligence leak so far in the 21^st century. The leak revealed that the NSA was working with the British Government Communications Headquarters (GCHQ) on surveillance and data collection of individuals throughout Europe. Similarly, the NSA also colluded with the German Federal Intelligence Service (BND) on similar data collection and surveillance activities. Whereas the British government reacted relatively benignly to the revelations despite cries of government abuse, the German government reacted negatively to the revelations, eventually opening a rift between Washington …

Activist: A New Framework For Dataset Labelling, Jack O'Neill, Sarah Jane Delany, Brian Mac Namee

Conference papers

Acquiring labels for large datasets can be a costly and time-consuming process. This has motivated the development of the semi-supervised learning problem domain, which makes use of unlabelled data — in conjunction with a small amount of labelled data — to infer the correct labels of a partially labelled dataset. Active Learning is one of the most successful approaches to semi-supervised learning, and has been shown to reduce the cost and time taken to produce a fully labelled dataset. In this paper we present Activist; a free, online, state-of-the-art platform which leverages active learning techniques to improve the efficiency of …

Empirical Comparative Analysis Of 1-Of-K Coding And K-Prototypes In Categorical Clustering, Fei Wang, Hector Franco, John Pugh, Robert J. Ross

Conference papers

Clustering is a fundamental machine learning application, which partitions data into homogeneous groups. K-means and its variants are the most widely used class of clustering algorithms today. However, the original k-means algorithm can only be applied to numeric data. For categorical data, the data has to be converted into numeric data through 1-of-K coding which itself causes many problems. K-prototypes, another clustering algorithm that originates from the k-means algorithm, can handle categorical data by adopting a different notion of distance. In this paper, we systematically compare these two methods through an experimental analysis. Our analysis shows that K-prototypes is more …

Landmark Detection With Surprise Saliency Using Convolutional Neural Networks, Feng Tang, Damian Lyons, Daniel Leeds

Faculty Publications

Abstract—Landmarks can be used as reference to enable people or robots to localize themselves or to navigate in their environment. Automatic definition and extraction of appropriate landmarks from the environment has proven to be a challenging task when pre-defined landmarks are not present. We propose a novel computational model of automatic landmark detection from a single image without any pre-defined landmark database. The hypothesis is that if an object looks abnormal due to its atypical scene context (what we call surprise saliency), it then may be considered as a good landmark because it is unique and easy to spot by …