Digital Commons Network^™

Knowledge Modeling Of Phishing Emails, Courtney Falk

Open Access Dissertations

This dissertation investigates whether or not malicious phishing emails are detected better when a meaningful representation of the email bodies is available. The natural language processing theory of Ontological Semantics Technology is used for its ability to model the knowledge representation present in the email messages. Known good and phishing emails were analyzed and their meaning representations fed into machine learning binary classifiers. Unigram language models of the same emails were used as a baseline for comparing the performance of the meaningful data. The end results show how a binary classifier trained on meaningful data is better at detecting phishing …

Cufa: A More Formal Definition For Digital Forensic Artifacts, Vikram S. Harichandran, Daniel Walnycky, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

The term “artifact” currently does not have a formal definition within the domain of cyber/ digital forensics, resulting in a lack of standardized reporting, linguistic understanding between professionals, and efficiency. In this paper we propose a new definition based on a survey we conducted, literature usage, prior definitions of the word itself, and similarities with archival science. This definition includes required fields that all artifacts must have and encompasses the notion of curation. Thus, we propose using a new term e curated forensic artifact (CuFA) e to address items which have been cleared for entry into a CuFA database (one …

Comparison Of Formulations Of Applied Tasks With Intervals, Fuzzy Sets And Probability Approaches, Boris Kovalerchuk, Vladik Kreinovich

All Faculty Scholarship for the College of the Sciences

The focus of this paper is to clarify the concepts of solutions in linear equations in interval, probabilistic and fuzzy sets setting for real word tasks. There is a fundamental difference between formal definitions of the solutions and physically meaningful concept of solution in applied tasks when equations have uncertain components. For instance, a formal definition of the solution in terms of Moore interval analysis can be completely irrelevant for solving a real world task. We show that formal definitions must follow meaningful concept of the solution in the real world. The paper proposed several formalized definitions of the concept …

Latent Semantic Indexing In The Discovery Of Cyber-Bullying In Online Text, Jacob L. Bigelow

Computer Science Summer Fellows

The rise in the use of social media and particularly the rise of adolescent use has led to a new means of bullying. Cyber-bullying has proven consequential to youth internet users causing a need for a response. In order to effectively stop this problem we need a verified method of detecting cyber-bullying in online text; we aim to find that method. For this project we look at thirteen thousand labeled posts from Formspring and create a bank of words used in the posts. First the posts are cleaned up by taking out punctuation, normalizing emoticons, and removing high and low …

Detection Of Cyberbullying In Sms Messaging, Bryan W. Bradley

Computer Science Summer Fellows

Cyberbullying is a type of bullying that uses technology such as cell phones to harass or malign another person. To detect acts of cyberbullying, we are developing an algorithm that will detect cyberbullying in SMS (text) messages. Over 80,000 text messages have been collected by software installed on cell phones carried by participants in our study. This paper describes the development of the algorithm to detect cyberbullying messages, using the cell phone data collected previously. The algorithm works by first separating the messages into conversations in an automated way. The algorithm then analyzes the conversations and scores the severity and …

A Model For Attention-Driven Judgements In Type Theory With Records, Simon Dobnik, John D. Kelleher

Conference papers

This paper makes three contributions to the discussion on the applicability of Type Theory with Records (TTR) to embodied dialogue agents. First, it highlights the problem of type assignment or judgements in practical implementations which is resource intensive. Second, it presents a judgement control mechanism, which consists of grouping of types into clusters or states by their thematic relations and selection of types following two mechanisms inspired by the Load Theory of selective attention and cognitive control (Lavie et al., 2004), that addresses this problem. Third, it presents a computational framework, based on Bayesian inference, that offers a basis for …

Response To Sbp-Brims Data Challenge: Agent-Based Approach To Human Migration Movement, Lin Junjie, Larry, Kathleen M. Carley

Research Collection School Of Computing and Information Systems

In this work, we attempt to address the social question of international migration, and the resulting shifts in country populations. This is achieved through the development of a country-level agent-based dynamic network model to examine shifts in population given network relations among countries, which inuences overall population change.

Using A Virtual Computing Laboratory To Foster Collaborative Learning For Information Security And Information Technology Education, Abdullah Konak, Michael R. Bartolacci

Journal of Cybersecurity Education, Research and Practice

Virtual computer laboratories have been an excellent technological solution to the problem of providing students with hands-on experimentation in information technology fields such as information security in a cost effective and secure manner. A virtual computer laboratory was utilized in this work as a collaborative environment for student learning with the goal of measuring its effect on student learning and attitudes toward laboratory assignments. Experiments were carried out utilizing specially-designed computer-based laboratory activities that included student assessments and surveys upon their completion. The experiments involved both small groups and individual students completing their respective laboratory activities and subsequent assessments/surveys. …

Data-Driven Synthesis And Evaluation Of Syntactic Facial Expressions In American Sign Language Animation, Hernisa Kacorri

Dissertations, Theses, and Capstone Projects

Technology to automatically synthesize linguistically accurate and natural-looking animations of American Sign Language (ASL) would make it easier to add ASL content to websites and media, thereby increasing information accessibility for many people who are deaf and have low English literacy skills. State-of-art sign language animation tools focus mostly on accuracy of manual signs rather than on the facial expressions. We are investigating the synthesis of syntactic ASL facial expressions, which are grammatically required and essential to the meaning of sentences. In this thesis, we propose to: (1) explore the methodological aspects of evaluating sign language animations with facial expressions, …

Skewer: Sentiment Knowledge Extraction With Entity Recognition, Christopher James Wu

Master's Theses

The California state legislature introduces approximately 5,000 new bills each legislative session. While the legislative hearings are recorded on video, the recordings are not easily accessible to the public. The lack of official transcripts or summaries also increases the effort required to gain meaningful insight from those recordings. Therefore, the news media and the general population are largely oblivious to what transpires during legislative sessions.

Digital Democracy, a project started by the Cal Poly Institute for Advanced Technology and Public Policy, is an online platform created to bring transparency to the California legislature. It features a searchable database of state …

Categorizing Blog Spam, Brandon Bevans

Master's Theses

The internet has matured into the focal point of our era. Its ecosystem is vast, complex, and in many regards unaccounted for. One of the most prevalent aspects of the internet is spam. Similar to the rest of the internet, spam has evolved from simply meaning ‘unwanted emails’ to a blanket term that encompasses any unsolicited or illegitimate content that appears in the wide range of media that exists on the internet.

Many forms of spam permeate the internet, and spam architects continue to develop tools and methods to avoid detection. On the other side, cyber security engineers continue to …

Qcri At Semeval-2016 Task 4: Probabilistic Methods For Binary And Ordinal Quantification, Giovanni Da San Martino, Wei Gao, Fabrizio Sebastiani

Research Collection School Of Computing and Information Systems

. (2016). n. In , pages 58—63, San Diego, California, USA. Association for Computational Linguistics. (1st place in sub-task E of Sentiment Analysis in Twitter)

Automated Identification Of High Impact Bug Reports Leveraging Imbalanced Learning Strategies, Xinli Yang, David Lo, Qiao Huang, Xin Xia, Jianling Sun

Research Collection School Of Computing and Information Systems

In practice, some bugs have more impact than others and thus deserve more immediate attention. Due to tight schedule and limited human resource, developers may not have enough time to inspect all bugs. Thus, they often concentrate on bugs that are highly impactful. In the literature, high impact bugs are used to refer to the bugs which appear in unexpected time or locations and bring more unexpected effects, or break pre-existing functionalities and destroy the user experience. Unfortunately, identifying high impact bugs from the thousands of bug reports in a bug tracking system is not an easy feat. Thus, an …

Learning Natural Language Inference With Lstm, Shuohang Wang, Jing Jiang

Research Collection School Of Computing and Information Systems

Natural language inference (NLI) is a fundamentally important task in natural language processing that has many applications. The recently released Stanford Natural Language Inference (SNLI) corpus has made it possible to develop and evaluate learning-centered methods such as deep neural networks for natural language inference (NLI). In this paper, we propose a special long short-term memory (LSTM) architecture for NLI. Our model builds on top of a recently proposed neural attention model for NLI but is based on a significantly different idea. Instead of deriving sentence embeddings for the premise and the hypothesis to be used for classification, our solution …

Using Perceptually Grounded Semantic Models To Autonomously Convey Meaning Through Visual Art, Derrall L. Heath

Theses and Dissertations

Developing advanced semantic models is important in building computational systems that can not only understand language but also convey ideas and concepts to others. Semantic models can allow a creative image-producing-agent to autonomously produce artifacts that communicate an intended meaning. This notion of communicating meaning through art is often considered a necessary part of eliciting an aesthetic experience in the viewer and can thus enhance the (perceived) creativity of the agent. Computational creativity, a subfield of artificial intelligence, deals with designing computational systems and algorithms that either automatically create original and functional products, or that augment the ability of humans …

User Behavior Mining In Microblogging, Tuan Anh Hoang

Dissertations and Theses Collection (Open Access)

This dissertation addresses the modeling of factors concerning microblogging users' content and behavior. We focus on two sets of factors. The first set includes behavioral factors of users and content items driving content propagation in microblogging. The second set consists of latent topics and communities of users as the users are engaged in content generation and behavior adoptions. These two sets of factors are extremely important in many applications, e.g., network monitoring and recommender systems. In the first part of this dissertation, we identify user virality, user susceptibility, and content virality as three behavioral factors that affect users' behaviors in …

The History Of Chinese Cybersecurity: Current Effects On Chinese Society Economy, And Foreign Relations, Vaughn C. Rogers

Seton Hall University Dissertations and Theses (ETDs)

Chinese cybersecurity has become an infamous topic in the field of cybersecurity today, causing a great deal of controversy. The controversy stems from whether or not censorship is hindering Chinese economy, society, and relationships with other countries. The White Papers (中国政府白皮书), the Constitution of the People’s Republic of China (中华人民共和国宪法), and The Internet in China (中国互联网状况) all suggest that there is a free flow of Internet both within and without China that promotes peaceful socioeconomic development which the Chinese government seeks to promote. But is China sacrificing lucrative business prospects to secure …

Automatically Characterizing Product And Process Incentives In Collective Intelligence, Allen Brockhurst Lavoie

McKelvey School of Engineering Graduate Student Theses & Dissertations

Social media facilitate interaction and information dissemination among an unprecedented number of participants. Why do users contribute, and why do they contribute to a specific venue? Does the information they receive cover all relevant points of view, or is it biased? The substantial and increasing importance of online communication makes these questions more pressing, but also puts answers within reach of automated methods. I investigate scalable algorithms for understanding two classes of incentives which arise in collective intelligence processes. Product incentives exist when contributors have a stake in the information delivered to other users. I investigate product-relevant user behavior changes, …

Improving Electroencephalography-Based Imagined Speech Recognition With A Simultaneous Video Data Stream, Sarah J. Stolze

Computer Science and Computer Engineering Undergraduate Honors Theses

Electroencephalography (EEG) devices offer a non-invasive mechanism for implementing imagined speech recognition, the process of estimating words or commands that a person expresses only in thought. However, existing methods can only achieve limited predictive accuracy with very small vocabularies; and therefore are not yet sufficient to enable fluid communication between humans and machines. This project proposes a new method for improving the ability of a classifying algorithm to recognize imagined speech recognition, by collecting and analyzing a large dataset of simultaneous EEG and video data streams. The results from this project suggest confirmation that complementing high-dimensional EEG data with similarly …

Cest: City Event Summarization Using Twitter, Deepa Mallela

Computer Science Graduate Projects and Theses

Twitter, with 288 million active users, has become the most popular platform for continuous real-time discussions. This leads to huge amounts of information related to the real-world, which has attracted researchers from both academia and industry. Event detection on Twitter has gained attention as one of the most popular domains of interest within the research community. Unfortunately, existing event detection methodologies have yet to fully explore Twitter metadata and instead rely solely on identifying events based on prior information or focus on events that belong to specific categories. Given the heavy volume of tweets that discuss events, summarization techniques can …

Augmenting Api Documentation With Insights From Stack Overflow, Christoph Treude, Martin P. Robillard

Research Collection School Of Computing and Information Systems

Software developers need access to different kinds of information which is often dispersed among different documentation sources, such as API documentation or Stack Overflow. We present an approach to automatically augment API documentation with “insight sentences” from Stack Overflow— sentences that are related to a particular API type and that provide insight not contained in the API documentation of that type. Based on a development set of 1,574 sentences, we compare the performance of two state-of-the-art summarization techniques as well as a pattern-based approach for insight sentence extraction. We then present SISE, a novel machine learning based approach that uses …

On Unravelling Opinions Of Issue Specific-Silent Users In Social Media, Wei Gong, Ee-Peng Lim, Feida Zhu, Pei Hua Cher

Research Collection School Of Computing and Information Systems

Social media has become a popular platform for people toshare opinions. Among the social media mining researchprojects that study user opinions and issues, most focus onanalyzing posted and shared content. They could run into thedanger of non-representative findings as the opinions of userswho do not post content are overlooked, which often happensin today’s marketing, recommendation, and social sensing research.For a more complete and representative profiling ofuser opinions on various topical issues, we need to investigatethe opinions of the users even when they stay silent onthese issues. We call these users the issue specific-silent users(i-silent users). To study them and their …

Principles Of Anti-Discriminatory Design, D. E. Wittkower

Philosophy Faculty Publications

Technical design can produce exclusionary and even discriminatory effects for users. A lack of discriminatory intent is insufficient to avoid discriminatory design, since implicit assumptions about users rarely include all relevant user demographics, and in some cases, designing for all relevant users is actually impossible. To minimize discriminatory effects of technical design, an actively anti-discriminatory design perspective must be adopted. This article provides examples of discriminatory user exclusion, then defining exclusionary design in terms of disaffordances and dysaffordances. Once these definitions are in place, principles of anti-discriminatory design are advanced, drawing upon a method of phenomenological variation employed in the …

Domain-Specific Cross-Language Relevant Question Retrieval, Bowen Xu, Zhenchang Xing, Xin Xia, David Lo, Qingye Wang, Shanping Li

Research Collection School Of Computing and Information Systems

In software development process, developers often seek solutions to the technical problems they encounter by searching relevant questions on Q&A sites. When developers fail to find solutions on Q&A sites in their native language (e.g., Chinese), they could translate their query and search on the Q&A sites in another language (e.g., English). However, developers who are non-native English speakers often are not comfortable to ask or search questions in English, as they do not know the proper translation of the Chinese technical words into the English technical words. Furthermore, the process of manually formulating cross-language queries and determining the weight …

Temporal Kernel Descriptors For Learning With Time-Sensitive Patterns, Doyen Sahoo, Abhishek Sharma, Hoi, Steven C. H., Peilin Zhao

Research Collection School Of Computing and Information Systems

Detecting temporal patterns is one of the most prevalent challenges while mining data. Often, timestamps or information about when certain instances or events occurred can provide us with critical information to recognize temporal patterns. Unfortunately, most existing techniques are not able to fully extract useful temporal information based on the time (especially at different resolutions of time). They miss out on 3 crucial factors: (i) they do not distinguish between timestamp features (which have cyclical or periodic properties) and ordinary features; (ii) they are not able to detect patterns exhibited at different resolutions of time (e.g. different patterns at the …

#Greysanatomy Vs. #Yankees: Demographics And Hashtag Use On Twitter, Jisun An, Ingmar Weber

Research Collection School Of Computing and Information Systems

Demographics, in particular, gender, age, and race, are a key predictor of human behavior. Despite the significant effect that demographics plays, most scientific studies using online social media do not consider this factor, mainly due to the lack of such information. In this work, we use state-of-the-art face analysis software to infer gender, age, and race from profile images of 350K Twitter users from New York. For the period from November 1, 2014 to October 31, 2015, we study which hashtags are used by different demographic groups. Though we find considerable overlap for the most popular hashtags, there are also …

Identification Of Small Endogenous Viral Elements Within Host Genomes, Edward C. Davis Jr.

Boise State University Theses and Dissertations

A parallel string matching software architecture has been developed (incorporating several algorithms) to identify small genetic sequences in large genomes. Endogenous viral elements (EVEs) are sequences originating in the genomes of viruses that have become integrated into the chromosomes of sperm or egg cells of infected hosts, and passed to subsequent generations. EVEs have been identified in all seven classes of viruses and in the species of all kingdoms of life. Viruses from groups V and VI are considered in this thesis, including HIV and Ebola, within host genomes ranging from bacteria to humans. This database of small endogenous viral …

A Comparative Approach To Question Answering Systems, Josue Balandrano Coronel

Theses and Dissertations

In this paper I will analyze three different algorithms and approaches to implement Question Answering Systems (QA-Systems). I will analyze the efficiency, strengths, and weaknesses of multiple algorithms by explaining them in detail and comparing them with each other. The overarching aim of this thesis is to explore ideas that can be used to create a truly open context QA-System. Open context QA-Systems remain an open problem.

The various algorithms and approaches presented in this work will be focused on complex questions. Complex questions are usually verbose and the context of the question is equally important to answer the query …

Are You Charlie Or Ahmed? Cultural Pluralism In Charlie Hebdo Response On Twitter, Jisun An, Haewoon Kwak, Yelena Mejova, Sonia Alonso Saenz De Oger, Braulio Gomez Fortes

Research Collection School Of Computing and Information Systems

We study the response to the Charlie Hebdo shootings of January 7, 2015 on Twitter across the globe. We ask whether the stances on the issue of freedom of speech can be modeled using established sociological theories, including Huntington’s culturalist Clash of Civilizations, and those taking into consideration social context, including Density and Interdependence theories. We find support for Huntington’s culturalist explanation, in that the established traditions and norms of one’s “civilization” predetermine some of one’s opinion. However, at an individual level, we also find social context to play a significant role, with non-Arabs living in Arab countries using #JeSuisAhmed …

Sentiments In Sustainability Data Collection : Understanding User Sentiment In Collaborative, Social Tagging Environmental Sciences Platforms, Nikita Sanjay Panchariya

Theses, Dissertations and Culminating Projects

Many scientists throughout the world are exploring how the data can be analyzed and used for sustainability purposes. With these investigations there is significant need to collect and explore the data with mobile collaborative tools to enable real time interactions among the interested users and the researchers. The principle objective of this study is to explore an application of sentiment analysis on the collected heterogeneous data in the form of text, images, and location details that were collected using the Geotagger application and observe and infer users’ reactions and opinions of the geographical data they collect about.