Computer Sciences Commons^™

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.

Cancerin: A Computational Pipeline To Infer Cancer-Associated Cerna Interaction Networks, Duc Do, Serdar Bozdag

Mathematics, Statistics and Computer Science Faculty Research and Publications

MicroRNAs (miRNAs) inhibit expression of target genes by binding to their RNA transcripts. It has been recently shown that RNA transcripts targeted by the same miRNA could “compete” for the miRNA molecules and thereby indirectly regulate each other. Experimental evidence has suggested that the aberration of such miRNA-mediated interaction between RNAs—called competing endogenous RNA (ceRNA) interaction—can play important roles in tumorigenesis. Given the difficulty of deciphering context-specific miRNA binding, and the existence of various gene regulatory factors such as DNA methylation and copy number alteration, inferring context-specific ceRNA interactions accurately is a computationally challenging task. Here we propose a computational …

An Ensemble Stacked Convolutional Neural Network Model For Environmental Event Sound Recognition, Shaobo Li, Yong Yao, Jie Hu, Guokai Liu, Xuemei Yao, Jianjun Hu

Faculty Publications

Convolutional neural networks (CNNs) with log-mel audio representation and CNN-based end-to-end learning have both been used for environmental event sound recognition (ESC). However, log-mel features can be complemented by features learned from the raw audio waveform with an effective fusion method. In this paper, we first propose a novel stacked CNN model with multiple convolutional layers of decreasing filter sizes to improve the performance of CNN models with either log-mel feature input or raw waveform input. These two models are then combined using the Dempster–Shafer (DS) evidence theory to build the ensemble DS-CNN model for ESC. Our experiments over three …

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

High-Performance Testbed For Vision-Aided Autonomous Navigation For Quadrotor Uavs In Cluttered Environments, Shakeeb Ahmad

Electrical and Computer Engineering ETDs

This thesis presents the development of an aerial robotic testbed based on Robot Operating System (ROS). The purpose of this high-performance testbed is to develop a system capable of performing robust navigation tasks using vision tools such as a stereo camera. While ensuring the computation of robot odometery, the system is also capable of sensing the environment using the same stereo camera. Hence, all the navigation tasks are performed using a stereo camera and an inertial measurement unit (IMU) as the main sensor suite. ROS is used as a framework for software integration due to its capabilities to provide efficient …

Information Foraging Through The Analysis Of Semantic Network Topology, Phillip J. Dibona

Theses and Dissertations

Information seekers are posed with multiple challenges in gathering an unbiased and comprehensive body of information. The costs of analyzing documents often drive searches toward a small subset of documents. Additionally, modern search tools may reinforce the confirmation bias of users by providing only those documents that closely match their search query. The end result is a decision or hypothesis that is ill-considered and substantiated by potentially biased information. Information seekers need an information foraging tool that can help them explore the document corpus to find relevant topics and text snippets, while finding the hidden information that may be buried …

Compact Hardware Implementation Of A Sha-3 Core For Wireless Body Sensor Networks, Yi Yang, Debiao He, Neeraj Kumar, Sherali Zeadally

Information Science Faculty Publications

One of the most important Internet of Things applications is the wireless body sensor network (WBSN), which can provide universal health care, disease prevention, and control. Due to large deployments of small scale smart sensors in WBSNs, security, and privacy guarantees (e.g., security and safety-critical data, sensitive private information) are becoming a challenging issue because these sensor nodes communicate using an open channel, i.e., Internet. We implement data integrity (to resist against malicious tampering) using the secure hash algorithm 3 (SHA-3) when smart sensors in WBSNs communicate with each other using the Internet. Due to the limited resources (i.e., storage, …

Epa-Rimm-V: Efficient Rootkit Detection For Virtualized Environments, Tejaswini Ajay Vibhute

Dissertations and Theses

The use of virtualized environments continues to grow for efficient utilization of the available compute resources. Hypervisors virtualize the underlying hardware resources and allow multiple Operating Systems to run simultaneously on the same infrastructure. Since the hypervisor is installed at a higher privilege level than the Operating Systems in the software stack it is vulnerable to rootkits that can modify the environment to gain control, crash the system and even steal sensitive information. Thus, runtime integrity measurement of the hypervisor is essential. The currently proposed solutions achieve the goal by relying either partially or entirely on the features of the …

Survey Results On Adults And Cybersecurity Education, Frank Breitinger, Joseph Ricci, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

Cyberattacks and identity theft are common problems nowadays where researchers often say that humans are the weakest link in the security chain. Therefore, this survey focused on analyzing the interest for adults for ‘cyber threat education seminars’, e.g., how to project themselves and their loved ones. Specifically, we asked questions to understand a possible audience, willingness for paying / time commitment, or fields of interest as well as background and previous training experience. The survey was conducted in late 2016 and taken by 233 participants. The results show that many are worried about cyber threats and about their children exploring …

Securing Zigbee Commercial Communications Using Constellation Based Distinct Native Attribute Fingerprinting, Christopher M. Rondeau, J. Addison Betances, Michael A. Temple

Faculty Publications

This work provides development of Constellation Based DNA (CB-DNA) Fingerprinting for use in systems employing quadrature modulations and includes network protection demonstrations for ZigBee offset quadrature phase shift keying modulation. Results are based on 120 unique networks comprised of seven authorized ZigBee RZSUBSTICK devices, with three additional like-model devices serving as unauthorized rogue devices. Authorized network device fingerprints are used to train a Multiple Discriminant Analysis (MDA) classifier and Rogue Rejection Rate (RRR) estimated for 2520 attacks involving rogue devices presenting themselves as authorized devices. With MDA training thresholds set to achieve a True Verification Rate (TVR) of TVR = …

Mixed Logical And Probabilistic Reasoning In The Game Of Clue, Todd W. Neller, Ziqian Luo

Computer Science Faculty Publications

Neller and Ziqian Luo ’18 presented a means of mixed logical and probabilistic reasoning with knowledge in the popular deductive mystery game Clue. Using at-least constraints, we more efficiently represented and reasoned about cardinality constraints on Clue card deal knowledge, and then employed a WalkSAT-based solution sampling algorithm with a tabu search metaheuristic in order to estimate the probabilities of unknown card places.

Adaptive Virtual Impedance Droop Control Based On Consensus Control Of Reactive Current, Zhilin Lu, Qing Wei, Yiyi Zhang, Junhui Zhao, Emad Manla

Electrical & Computer Engineering and Computer Science Faculty Publications

It is difficult to achieve accurate distribution of reactive power based on conventional droop control due to the line impedance mismatch in an islanded microgrid. An adaptive virtual impendence method based on consensus control of reactive current is proposed in this paper. A distributed control structure without the central controller has been established. In this structure, each distributed generation unit (DG) is an independent agent, one-way communication is used between the adjacent DGs, and the reactive power sharing is equivalent to a problem of reactive power current consensus. It has been proven that the system is asymptotically stable under the …

Moving Target Defense For Securing Scada Communications, Vahid Heydari

College of Science & Mathematics Departmental Research

In this paper, we introduce a framework for building a secure and private peer to peer communication used in supervisory control and data acquisition networks with a novel Mobile IPv6-based moving target defense strategy. Our approach aids in combating remote cyber-attacks against peer hosts by thwarting any potential attacks at their reconnaissance stage. The IP address of each host is randomly changed at a certain interval creating a moving target to make it difficult for an attacker to find the host. At the same time, the peer host is updated through the use of the binding update procedure (standard Mobile …

Challenging The Estrangela / Serto Divide: Why The Standard Model Of Syriac Scripts Just Doesn't Work, Kristina Bush, Michael Philip Penn, R. Jordan Crouser, Nicholas Howe, Shuangxia Wu

Computer Science: Faculty Publications

As part of a larger digital paleography project, our team has assembled a database of tens of thousands of individual Syriac letters and letter data from 96% of extant early Syriac manuscripts that have a secure composition date. Long term, such data can help scholars develop more accurate ways to classify Syriac scripts. In the present article we use this data to illustrate just how frequently the most common way of categorizing Syriac scripts as either Estrangela or Serto does not accurately convey the ways early scribes actually wrote. In addition to challenging this “Standard Model” of Syriac scripts, the …

Automatic Multimodal Assessment Of Neonatal Pain, Ghada Zamzmi

USF Tampa Graduate Theses and Dissertations

For several decades, pediatricians used to believe that neonates do not feel pain. The American Academy of Pediatrics (AAP) recognized neonates' sense of pain in 1987. Since then, there have been many studies reporting a strong association between repeated pain exposure (under-treatment) and alterations in brain structure and function. This association has led to the increased use of anesthetic medications. However, recent studies found that the excessive use of analgesic medications (over-treatment) can cause many side effects. The current standard for assessing neonatal pain is discontinuous and suffers from inter-observer variations, which can lead to over- or under-treatment. Therefore, it …

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 …

Machine Learning Methods For Network Intrusion Detection And Intrusion Prevention Systems, Zheni Svetoslavova Stefanova

USF Tampa Graduate Theses and Dissertations

Given the continuing advancement of networking applications and our increased dependence upon software-based systems, there is a pressing need to develop improved security techniques for defending modern information technology (IT) systems from malicious cyber-attacks. Indeed, anyone can be impacted by such activities, including individuals, corporations, and governments. Furthermore, the sustained expansion of the network user base and its associated set of applications is also introducing additional vulnerabilities which can lead to criminal breaches and loss of critical data. As a result, the broader cybersecurity problem area has emerged as a significant concern, with many solution strategies being proposed for both …

A Comparison Of Nano-Patterns Vs. Software Metrics In Vulnerability Prediction, Kazi Zakia Sultana, Byron J. Williams, Amiangshu Bosu

Department of Computer Science Faculty Scholarship and Creative Works

Context: Software security is an imperative aspect of software quality. Early detection of vulnerable code during development can better ensure the security of the codebase and minimize testing efforts. Although traditional software metrics are used for early detection of vulnerabilities, they do not clearly address the granularity level of the issue to precisely pinpoint vulnerabilities. The goal of this study is to employ method-level traceable patterns (nano-patterns) in vulnerability prediction and empirically compare their performance with traditional software metrics. The concept of nano-patterns is similar to design patterns, but these constructs can be automatically recognized and extracted from source code. …

Pragmatics And Semantics To Connect Specific Local Laws With Public Reactions, Manish Puri, Aparna S. Varde, Boxiang Dong

Department of Computer Science Faculty Scholarship and Creative Works

This paper proposes an approach called TOLCS (Tweet Ordinance Linkage by Commonsense and Semantics) which helps connect specific ordinances or local laws to pertinent tweets expressing public reactions on them. TOLCS incorporates pragmatic aspects by commonsense knowledge, and semantic aspects by domain knowledge along with text similarity methods. It uses a blocking mechanism to reduce sample space for efficiently processing big data on ordinances and tweets.

Predicting River Stage Using Recurrent Neural Networks, Eric Rohli

LSU Master's Theses

River stage prediction is an important problem in the water transportation industry. Accurate river stage predictions provide crucial information to barge and tow boat operators, port terminal captains, and lock management officials. Shallow river levels caused by prolonged drought impact the loading capacity of barges and tow boats. High river levels caused by excessive rainfall or snowmelt allow for greater tow capacities but make downstream transportation and lock management risky. Current academic river height prediction systems utilize either time series statistical analysis or machine learning algorithms to forecast future river heights, but systems that combine these two areas often limit …

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.

Lightweight Multilingual Software Analysis, Damian Lyons, Anne Marie Bogar, David Baird

Faculty Publications

Developer preferences, language capabilities and the persistence of older languages contribute to the trend that large software codebases are often multilingual – that is, written in more than one computer language. While developers can leverage monolingual software development tools to build software components, companies are faced with the problem of managing the resultant large, multilingual codebases to address issues with security, efficiency, and quality metrics. The key challenge is to address the opaque nature of the language interoperability interface: one language calling procedures in a second (which may call a third, or even back to the first), resulting in a …

Improving K-Nn Search And Subspace Clustering Based On Local Intrinsic Dimensionality, Arwa M. Wali

Dissertations

In several novel applications such as multimedia and recommender systems, data is often represented as object feature vectors in high-dimensional spaces. The high-dimensional data is always a challenge for state-of-the-art algorithms, because of the so-called "curse of dimensionality". As the dimensionality increases, the discriminative ability of similarity measures diminishes to the point where many data analysis algorithms, such as similarity search and clustering, that depend on them lose their effectiveness. One way to handle this challenge is by selecting the most important features, which is essential for providing compact object representations as well as improving the overall search and clustering …

Applications Of Big Knowledge Summarization, Ling Zheng

Dissertations

Advanced technologies have resulted in the generation of large amounts of data ("Big Data"). The Big Knowledge derived from Big Data could be beyond humans' ability of comprehension, which will limit the effective and innovative use of Big Knowledge repository. Biomedical ontologies, which play important roles in biomedical information systems, constitute one kind of Big Knowledge repository. Biomedical ontologies typically consist of domain knowledge assertions expressed by the semantic connections between tens of thousands of concepts. Without some high-level visual representation of Big Knowledge in biomedical ontologies, humans cannot grasp the "big picture" of those ontologies. Such Big Knowledge orientation …

Novel Image Descriptors And Learning Methods For Image Classification Applications, Ajit Puthenputhussery

Dissertations

Image classification is an active and rapidly expanding research area in computer vision and machine learning due to its broad applications. With the advent of big data, the need for robust image descriptors and learning methods to process a large number of images for different kinds of visual applications has greatly increased. Towards that end, this dissertation focuses on exploring new image descriptors and learning methods by incorporating important visual aspects and enhancing the feature representation in the discriminative space for advancing image classification.

First, an innovative sparse representation model using the complete marginal Fisher analysis (CMFA-SR) framework is proposed …

Theoretical Studies Of Photoinduced Dynamics And Topological States In Materials With Strong Electron-Lattice Couplings, Linghua Zhu

Dissertations

First, we study the nonequilibrium dynamics of photoinduced phase transitions in charge ordered (CO) systems with a strong electron-lattice interaction and analyze the interplay between electrons, periodic lattice distortions, and a phonon thermal reservoir. Simulations based on a tight-binding Hamiltonian and Boltzmann equations reveal partially decoupled oscillations of the electronic order parameter and the periodic lattice distortion during CO melting, which becomes more energy efficient with lower photon energy. The cooling rate of the electron system correlates with the CO gap dynamics, responsible for an order of magnitude decrease of the cooling rate upon the gap reopening. The work also …

Why Stem?, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Is the idea of combining science, technology, engineering, and mathematics into a single STEM complex a fashionable tendency, as some educator think - or is there a deep reason behind this combination? In this paper, we show that the latest developments in Theory of Computation make such a union necessary and desirable.

Summation Of Divergent Infinite Series: How Natural Are The Current Tricks, Mourat Tchoshanov, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Infinities are usually an interesting topic for students, especially when they lead to what seems like paradoxes, when we have two different seemingly correct answers to the same question. One of such cases is summation of divergent infinite sums: on the one hand, the sum is clearly infinite, on the other hand, reasonable ideas lead to a finite value for this same sum. A usual way to come up with a finite sum for a divergent infinite series is to find a 1-parametric family of series that includes the given series for a specific value p = p0 of the …

Composing A Cross-Platform Development Environment Using Maven, Terry J. Speicher, Yoonsik Cheon

Departmental Technical Reports (CS)

It is challenging to develop a cross-platform application, that is, an application that runs on multiple platforms. It requires not only code reuse but also an individual building or compilation for each platform, possibly with different development tools. In this paper, we show a simple approach for creating a cross-platform application using Maven, a build tool. We configure a cross-platform development environment by composing a set of platform-specific tools or integrated development environments (IDE's). The key idea of our approach is to use Maven to immediately propagate changes made using one platform tool, or IDE, to other platforms. For this, …