Computer Sciences Commons^™

A Survey Of Botnet Detection Techniques By Command And Control Infrastructure, Thomas S. Hyslip, Jason M. Pittman

Journal of Digital Forensics, Security and Law

Botnets have evolved to become one of the most serious threats to the Internet and there is substantial research on both botnets and botnet detection techniques. This survey reviewed the history of botnets and botnet detection techniques. The survey showed traditional botnet detection techniques rely on passive techniques, primarily honeypots, and that honeypots are not effective at detecting peer-to-peer and other decentralized botnets. Furthermore, the detection techniques aimed at decentralized and peer-to-peer botnets focus on detecting communications between the infected bots. Recent research has shown hierarchical clustering of flow data and machine learning are effective techniques for detecting botnet peer-to-peer …

Sparse Coding Based Dense Feature Representation Model For Hyperspectral Image Classification, Ender Oguslu, Guoqing Zhou, Zezhong Zheng, Khan Iftekharuddin, Jiang Li

Electrical & Computer Engineering Faculty Publications

We present a sparse coding based dense feature representation model (a preliminary version of the paper was presented at the SPIE Remote Sensing Conference, Dresden, Germany, 2013) for hyperspectral image (HSI) classification. The proposed method learns a new representation for each pixel in HSI through the following four steps: sub-band construction, dictionary learning, encoding, and feature selection. The new representation usually has a very high dimensionality requiring a large amount of computational resources. We applied the l₁/l_q regularized multiclass logistic regression technique to reduce the size of the new representation. We integrated the method with a linear …

Community Discovery From Social Media By Low-Rank Matrix Recovery, Jinfeng Zhuang, Mei Tao, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang

Research Collection School Of Computing and Information Systems

The pervasive usage and reach of social media have attracted a surge of attention in the multimedia research community. Community discovery from social media has therefore become an important yet challenging issue. However, due to the subjective generating process, the explicitly observed communities (e.g., group-user and user-user relationship) are often noisy and incomplete in nature. This paper presents a novel approach to discovering communities from social media, including the group membership and user friend structure, by exploring a low-rank matrix recovery technique. In particular, we take Flickr as one exemplary social media platform. We first model the observed indicator matrix …

Metadata And Linked Data In Word Sense Disambiguation, Matthew Corsmeier

Library Philosophy and Practice (e-journal)

Word Sense Disambiguation (WSD) can be assisted by taking advantage of the metadata embedded in the various ontologies, lexica, databases, etc… that exist in the Semantic Web. Automated processes that exploit the links already present in the Semantic Web can strengthen parsing of word senses by using user-contributed and semantically-linked data. These processes are only possible because of a commitment to interoperability and the creation of shared standards. This paper will review some of the most heavily used Linguistic Linked Open Data (LLOD) tools and models which show the most promise for using metadata to alleviate problems caused by polysemous …

Judging Dread: A Quantitative Investigation Of Affect, Psychometric Dread And Risk Consequence, Melvyn Griffiths

Theses: Doctorates and Masters

Risk is generally understood as a product of the likelihood and consequence of an event. However, the way in which estimations of consequences are formed is unclear due to the complexities of human perception. In particular, the influence of Affect, defined as positive or negative qualities subjectively assigned to stimuli, may skew risk consequence judgements. Thus a clearer understanding of the role of Affect in risk consequence estimations has significant implications for risk management, risk communication and policy formulation.

In the Psychometric tradition of risk perception, Affect has become almost synonymous with the concept of Dread, despite Dread being measured …

Intensity Based Interrogation Of Optical Fibre Sensors For Industrial Automation And Intrusion Detection Systems, Gary Andrew Allwood

Theses: Doctorates and Masters

In this study, the use of optical fibre sensors for intrusion detection and industrial automation systems has been demonstrated, with a particular focus on low cost, intensity-based, interrogation techniques. The use of optical fibre sensors for intrusion detection systems to secure residential, commercial, and industrial premises against potential security breaches has been extensively reviewed in this thesis. Fibre Bragg grating (FBG) sensing is one form of optical fibre sensing that has been underutilised in applications such as in-ground, in-fence, and window and door monitoring, and addressing that opportunity has been a major goal of this thesis. Both security and industrial …

Employees’ Social Networking Site Use Impact On Job Performance: Evidence From Pakistan, Murad Moqbel, Fizza Aftab

Information Systems Faculty Publications

This paper reinvestigates the impact of social networking site use by employees on job performance by conducting a methodological replication of Moqbel, Nevo, and Kock (2013) using samples (N=139) from Pakistan. In both studies, social networking site use has significant effects on organizational commitment and job satisfaction, and job satisfaction also has a significant impact on job performance and organizational commitment. In comparison with the U.S., we find that social networking site use in Pakistan has no significant impact on job performance through the mediating effect of job satisfaction, yet has a significant effect on organizational commitment and job satisfaction. …

Major Challenges And Solutions For Utilizing Big Data In The Maritime Industry, Sadaharu Koga

World Maritime University Dissertations

The dissertation is a study of big data for the use in the maritime industry. Today’s society is information-intensive. The term “big data” is becoming more common. In fact, some maritime companies and institutions have already been trying to utilize big data for enhancing maritime safety and environmental protection. In order to promote this trend, the dissertation tries to identify common and important challenges for the whole maritime industry in terms of the utilization of big data and propose corresponding solutions. First, by reviewing the definitions of big data, three major features are identified. Big data takes electronic form, is …

An Empirical Study Of Semantic Similarity In Wordnet And Word2vec, Abram Handler

LSU New Orleans Theses and Dissertations

This thesis performs an empirical analysis of Word2Vec by comparing its output to WordNet, a well-known, human-curated lexical database. It finds that Word2Vec tends to uncover more of certain types of semantic relations than others -- with Word2Vec returning more hypernyms, synonomyns and hyponyms than hyponyms or holonyms. It also shows the probability that neighbors separated by a given cosine distance in Word2Vec are semantically related in WordNet. This result both adds to our understanding of the still-unknown Word2Vec and helps to benchmark new semantic tools built from word vectors.

Data Preparation For Social Network Mining And Analysis, Yazhe Wang

Dissertations and Theses Collection (Open Access)

This dissertation studies the problem of preparing good-quality social network data for data analysis and mining. Modern online social networks such as Twitter, Facebook, and LinkedIn have rapidly grown in popularity. The consequent availability of a wealth of social network data provides an unprecedented opportunity for data analysis and mining researchers to determine useful and actionable information in a wide variety of fields such as social sciences, marketing, management, and security. However, raw social network data are vast, noisy, distributed, and sensitive in nature, which challenge data mining and analysis tasks in storage, efficiency, accuracy, etc. Many mining algorithms cannot …

Anomaly Detection Through Enhanced Sentiment Analysis On Social Media Data, Zhaoxia Wang, Victor Joo, Chuan Tong, Xin Xin, Hoong Chor Chin

Research Collection School Of Computing and Information Systems

Anomaly detection in sentiment analysis refers to detecting abnormal opinions, sentiment patterns or special temporal aspects of such patterns in a collection of data. The anomalies detected may be due to sudden sentiment changes hidden in large amounts of text. If these anomalies are undetected or poorly managed, the consequences may be severe, e.g. A business whose customers reveal negative sentiments and will no longer support the establishment. Social media platforms, such as Twitter, provide a vast source of information, which includes user feedback, opinion and information on most issues. Many organizations also leverage social media platforms to publish information …

Extracting Interest Tags From Twitter User Biographies, Ying Ding, Jing Jiang

Research Collection School Of Computing and Information Systems

Twitter, one of the most popular social media platforms, has been studied from different angles. One of the important sources of information in Twitter is users’ biographies, which are short self-introductions written by users in free form. Biographies often describe users’ background and interests. However, to the best of our knowledge, there has not been much work trying to extract information from Twitter biographies. In this work, we study how to extract information revealing users’ personal interests from Twitter biographies. A sequential labeling model is trained with automatically constructed labeled data. The popular patterns expressing user interests are extracted and …

Is The Smartphone Smart In Kathmandu?, Seth Bird

Independent Study Project (ISP) Collection

This is the extensive study of the smartphone in the developing country of Nepal, specifically the Kathmandu valley. Throughout my research I conducted various interviews with businesses, Tibetan refugees, and Nepali millennials (18yrs-33yrs) with the goal of identifying how the smartphone is used and understood. I chose the Kathmandu valley as my main area of research because the usage of smartphones in rural Nepal is extremely limited, and the valley represents the economic hub where progressive thinking flourishes. As a main objective I sought to understand how, if at all, the smartphone is used differently between Nepal and America. All …

Issues Of Social Data Analytics With A New Method For Sentiment Analysis Of Social Media Data, Zhaoxia Wang, Victor J. C. Tong, David Chan

Research Collection School of Social Sciences

Social media data consists of feedback, critiques and other comments that are posted online by internet users. Collectively, these comments may reflect sentiments that are sometimes not captured in traditional data collection methods such as administering a survey questionnaire. Thus, social media data offers a rich source of information, which can be adequately analyzed and understood. In this paper, we survey the extant research literature on sentiment analysis and discuss various limitations of the existing analytical methods. A major limitation in the large majority of existing research is the exclusive focus on social media data in the English language. There …

High-Resolution Digital 3d Models Of Algar Do Penico Chamber: Limitations, Challenges, And Potential, Ivo Silvestre M.Sc., José I. Rodrigues Phd, Mauro Figueiredo Phd, Cristina Veiga-Pires Phd

International Journal of Speleology

The study of karst and its geomorphological structures is important for understanding the relationships between hydrology and climate over geological time. In that context, we conducted a terrestrial laser-scan survey to map geomorphological structures in the karst cave of Algar do Penico in southern Portugal. The point cloud data set obtained was used to generate 3D meshes with different levels of detail, allowing the limitations of mapping capabilities to be explored.

In addition to cave mapping, the study focuses on 3D-mesh analysis, including the development of two algorithms for determination of stalactite extremities and contour lines, and on the interactive …

Tools For Managing The Past Web, Michele C. Weigle, Michael L. Nelson, Yasmin Alnoamany, Ahmed Alsum, Justin Brunelle, Mat Kelly, Hany Salaheldeen

Computer Science Presentations

PDF of a powerpoint presentation from the Archive-It Partners Meeting in Montgomery, Alabama, November 18, 2014. Also available on Slideshare.

Anonymized Video Analysis Methods And Systems, Marjorie Skubic, James M. Keller, Fang Wang, Derek T. Anderson, Erik Stone, Robert H. Luke Iii, Tanvi Banerjee, Marilyn J. Rantz

Kno.e.sis Publications

Methods and systems for anonymized video analysis are described. In one embodiment, a first silhouette image of a person in a living unit may be accessed. The first silhouette image may be based on a first video signal recorded by a first video camera. A second silhouette image of the person in the living unit may be accessed. The second silhouette image may be of a different view of the person than the first silhouette image. The second silhouette image may be based on a second video signal recorded by a second video camera. A three-dimensional model of the person …

Protecting Web Servers From Web Robot Traffic, Derek Doran

Kno.e.sis Publications

No abstract provided.

Preserving Central Ohio’S History: A Study Of Why It Must Be A Consultant To The Business, Gregory J. Syferd

Learning Showcase 2014

Columbus Metropolitan Library (CML) introduced digital images as part of its website nearly 10 years ago. The initial collection featured local artists, historical photographs, and newspaper articles. Since 2012, the collection has continued to grow to include nearly a dozen distinct repositories and hundreds of thousands of unique records. Furthermore, CML has created partnerships with local organizations to preserve Columbus’ unique and rich history.

In 2015, CML looks to further scale its digital collections. Through a grant, which provided specialized large format and a book scanner, CML will share historical photos and artifacts, many of which are generously provided by …

Serving Military Families: Perceptions Of Educational Counseling In A Virtual Environment, Taryn Stevenson

CCAC Theses and Dissertations

The advances in communication technology over the past 20 years have significant implications for the delivery of psycho-educational therapeutic services to populations that have been historically underserved due to remote locations lacking trained providers. One such population is military families, who also suffer from a negative stigma of asking for outside help or education for personal growth. This population also faces increasing mental health needs due to military deployment in Operation Iraqi Freedom (OIF) and Operation Enduring Freedom (OEF). These operations have increased the number of returning service members who have been physically and mentally injured. The effect that these …

Triad-Based Role Discovery For Large Social Systems, Derek Doran

Kno.e.sis Publications

The social role of a participant in a social system conceptualizes the circumstances under which she chooses to interact with others, making their discovery and analysis important for theoretical and practical purposes. In this paper, we propose a methodology to detect such roles by utilizing the conditional triad censuses of ego-networks. These censuses are a promising tool for social role extraction because they capture the degree to which basic social forces push upon a user to interact with others in a system. Clusters of triad censuses, inferred from network samples that preserve local structural properties, define the social roles. The …

Discovering Perceptions In Online Social Media: A Probabilistic Approach, Derek Doran, Swapna S. Gokhale, Aldo Dagnino

Kno.e.sis Publications

People across the world habitually turn to online social media to share their experiences, thoughts, ideas, and opinions as they go about their daily lives. These posts collectively contain a wealth of insights into how masses perceive their surroundings. Therefore, extracting people’s perceptions from social media posts can provide valuable information about pertinent issues such as public transportation, emergency conditions, and even reactions to political actions or other activities. This paper proposes a novel approach to extract such perceptions from a corpus of social media posts originating from a given broad geographical region. The approach divides the broad region into …

Online Information Searching For Cardiovascular Diseases: An Analysis Of Mayo Clinic Search Query Logs, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak

Kno.e.sis Publications

Since the early 2000’s, Internet usage for health information searching has increased significantly. Studying search queries can help us to understand users “information need” and how do they formulate search queries (“expression of information need”). Although cardiovascular diseases (CVD) affect a large percentage of the population, few studies have investigated how and what users search for CVD. We address this knowledge gap in the community by analyzing a large corpus of 10 million CVD related search queries from MayoClinic.com. Using UMLS MetaMap and UMLS semantic types/concepts, we developed a rule-based approach to categorize the queries into 14 health categories. We …

An Analysis Of Mayo Clinic Search Query Logs For Cardiovascular Diseases, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak

Kno.e.sis Publications

Increasingly, individuals are taking active participation in learning and managing their health by leveraging online resources. Understanding online health information searching behavior can help us to study what health topics users search for and how search queries are formulated. In this work, we analyzed 10 million cardiovascular diseases (CVD) related search queries from MayoClinic.com. We performed semantic analysis on the queries using UMLS MetaMap and analyzed structural and textual properties as well as linguistic characteristics of the queries.

A Game-Theoretic Analysis Of The Nuclear Non-Proliferation Treaty, Peter Revesz

School of Computing: Conference and Workshop Papers

Although nuclear non-proliferation is an almost universal human desire, in practice, the negotiated treaties appear unable to prevent the steady growth of the number of states that have nuclear weapons. We propose a computational model for understanding the complex issues behind nuclear arms negotiations, the motivations of various states to enter a nuclear weapons program and the ways to diffuse crisis situations.

On Joint Modeling Of Topical Communities And Personal Interest In Microblogs, Tuan-Anh Hoang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we propose the Topical Communities and Personal Interest (TCPI) model for simultaneously modeling topics, topical communities, and users’ topical interests in microblogging data. TCPI considers different topical communities while differentiating users’ personal topical interests from those of topical communities, and learning the dependence of each user on the affiliated communities to generate content. This makes TCPI different from existing models that either do not consider the existence of multiple topical communities, or do not differentiate between personal and community’s topical interests. Our experiments on two Twitter datasets show that TCPI can effectively mine the representative topics for …

Historical Traffic-Tolerant Paths In Road Networks, Pui Hang Li, Man Lung Yiu, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Historical traffic information is valuable for transportation analysis and planning, as well as for route search services. In view of these applications, we propose the k traffic-tolerant paths problem (TTP) on road networks, which takes a source-destination pair and historical traffic information as input, and returns k paths that minimize the aggregate (historical) travel time. Unlike the shortest path problem, the TTP problem has a combinatorial search space that renders the optimal solution expensive to compute. We propose an exact algorithm and a heuristic algorithm for this problem. Experiments on real traffic data demonstrate the effectiveness of TTP paths and …

The Evolution Of Research On Multimedia Travel Guide Search And Recommender Systems, Junge Shen, Zhiyong Cheng, Jialie Shen, Tao Mei, Xinbo Gao

Research Collection School Of Computing and Information Systems

The importance of multimedia travel guide search and recommender systems has led to a substantial amount of research spanning different computer science and information system disciplines in recent years. The five core research streams we identify here incorporate a few multimedia computing and information retrieval problems that relate to the alternative perspectives of algorithm design for optimizing search/recommendation quality and different methodological paradigms to assess system performance at large scale. They include (1) query analysis, (2) diversification based on different criteria, (3) ranking and reranking, (4) personalization and (5) evaluation. Based on a comprehensive discussion and analysis of these streams, …

Improving The Efficacy Of Web-Based Educational Outreach In Ecology, Gregory R. Goldsmith, Andrew D. Fulton, Colin D. Witherill, Javier F. Espeleta

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Scientists are increasingly engaging the web to provide formal and informal science education opportunities. Despite the prolific growth of web-based resources, systematic evaluation and assessment of their efficacy remains limited. We used clickstream analytics, a widely available method for tracking website visitors and their behavior, to evaluate 60,000 visits over three years to an educational website focused on ecology. Visits originating from search engine queries were a small proportion of the traffic, suggesting the need to actively promote websites to drive visitation. However, the number of visits referred to the website per social media post varied depending on the social …

A Causal Model To Predict Organizational Knowledge Sharing Via Information And Communication Technologies, Simon Cleveland

CCAC Theses and Dissertations

Knowledge management literature identifies numerous barriers that inhibit employees' knowledge seeking and knowledge contributing practices via information and communication technologies (ICTs). Presently, there is a significant gap in the literature that explains what factors promote common knowledge sharing barriers. To bridge this gap, this study examined two research questions: 1) What are the potential factors that contribute to the commonly accepted barriers to knowledge sharing?, and 2) How do these factors impact employees' use of ICTs for knowledge seeking and knowledge contributing? Literature review of 103 knowledge management articles identified three major barriers to knowledge sharing practices (lack of time, …