Computer Sciences Commons^™

Development Of Visualization-Animation Software For Learning Transportation Algorithms, Ivan P. Makohon

Computational Modeling & Simulation Engineering Theses & Dissertations

Recognizing the steady decline in US Science Technology Engineering Mathematics (STEM) interests and enrollments, the National Science Foundation (NSF) and the White House have developed national strategies and provided significant budget resources to STEM education research [1-2] in the past years, with the ultimate goals being to improve both the quality and number of highly trained US educators, student workforce in STEM topics, in today’s highly competitive global markets. With the explosion of the internet’s capability and availability, it is even more critical to effectively train this future USA-STEM work-force and/or to develop effective STEM related teaching tools to reach …

Oversampling Methods For Imbalanced Dataset Classification And Their Application To Gynecological Disorder Diagnosis, Iman Nekooeimehr

USF Tampa Graduate Theses and Dissertations

In many applications, the dataset for classification may be highly imbalanced where most of the instances in the training set may belong to some of the classes (majority classes), while only a few instances are from the other classes (minority classes). Conventional classifiers will strongly favor the majority class and ignore the minority instances. The imbalance problem can occur in both binary data classification and also in ordinal regression. Ordinal regression is a supervised approach for learning the ordinal relationship between classes. Extensive research has been performed for addressing imbalanced datasets for binary classification; however, current methods do not address …

Enforcing Security Policies On Gpu Computing Through The Use Of Aspect-Oriented Programming Techniques, Bader Albassam

USF Tampa Graduate Theses and Dissertations

This thesis presents a new security policy enforcer designed for securing parallel computation on CUDA GPUs. We show how the very features that make a GPGPU desirable have already been utilized in existing exploits, fortifying the need for security protections on a GPGPU. An aspect weaver was designed for CUDA with the goal of utilizing aspect-oriented programming for security policy enforcement. Empirical testing verified the ability of our aspect weaver to enforce various policies. Furthermore, a performance analysis was performed to demonstrate that using this policy enforcer provides no significant performance impact over manual insertion of policy code. Finally, future …

Energy Consumption Prediction With Big Data: Balancing Prediction Accuracy And Computational Resources, Katarina Grolinger, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

In recent years, advances in sensor technologies and expansion of smart meters have resulted in massive growth of energy data sets. These Big Data have created new opportunities for energy prediction, but at the same time, they impose new challenges for traditional technologies. On the other hand, new approaches for handling and processing these Big Data have emerged, such as MapReduce, Spark, Storm, and Oxdata H2O. This paper explores how findings from machine learning with Big Data can benefit energy consumption prediction. An approach based on local learning with support vector regression (SVR) is presented. Although local learning itself is …

Secure Software Engineering Education: Knowledge Area, Curriculum And Resources, Xiaohong Yuan, Li Yang, Bilan Jones, Huiming Yu, Bei-Tseng Chu

Journal of Cybersecurity Education, Research and Practice

This paper reviews current efforts and resources in secure software engineering education, with the goal of providing guidance for educators to make use of these resources in developing secure software engineering curriculum. These resources include Common Body of Knowledge, reference curriculum, sample curriculum materials, hands-on exercises, and resources developed by industry and open source community. The relationship among the Common Body of Knowledge proposed by the Department of Homeland Security, the Software Engineering Institute at Carnegie Mellon University, and ACM/IEEE are discussed. The recent practices on secure software engineering education, including secure software engineering related programs, courses, and course modules …

Metrics, Software Engineering, Small Systems – The Future Of Systems Development, William L. Honig

Computer Science: Faculty Publications and Other Works

In this talk I will introduce the importance of metrics, or measures, and the role they play in the development of high quality computer systems. I will review some key mega trends in computer science over the last three decades and then explain why I believe the trend to small networked systems, along with metrics and software engineering will define the future of high technology computer based systems.

I first learned about metrics at the Bell System where everything was measured. Metrics can be understood easily if you think of them as measures, for example of calories or salt in …

Analysis Of A Parallel Machine Scheduling Problem With Sequence Dependent Setup Times And Job Availability Intervals, Ridvan Gedik, Chase Rainwater, Heather Nachtmann, Edward A. Pohl

Mechanical and Industrial Engineering Faculty Publications

In this study, we propose constraint programming (CP) model and logic-based Benders algorithms in order to make the best decisions for scheduling non-identical jobs with availability intervals and sequence dependent setup times on unrelated parallel machines in a fixed planning horizon. In this problem, each job has a profit, cost and must be assigned to at most one machine in such a way that total profit is maximized. In addition, the total cost has to be less than or equal to a budget level. Computational tests are performed on a real-life case study prepared in collaboration with the U.S. Army …

Prosense, Johnny Favazza Ii, Casey Glasgow, Matt Epperson

Computer Engineering

This project aims to gather advanced data sets from MEMS sensors and GPS and deliver it to the user, who can capitalize on the data. The once negligible half-degree difference of your board barreling down a wave can be recorded from a gyro and exploited for the perfect turn. The exact speed dreaded by longboarders where speed wobbles turn into a road rash can be analysed and consequently avoided. Ascertaining the summit of your flight using combined GPS sensors from the ski ramp allows for the correct timing of tricks. When it comes to pursuing excellence in professional sports, amateur …

Musictrakr, Benjamin Lin

Computer Engineering

MusicTrackr is an IoT device that musicians attach to their instruments. The device has a start and stop button that allows users to record their playing sessions. Each recorded session is sent wirelessly to a cloud database. An accompanying website displays all of the recorded sessions, organized by date. After picking a specific date, the user can view graphs showing total practice time and average session length as well play back any recordings during that date. In addition, the user may add comments to any specific date or recording. Lastly, the user may tag a specific date with a color …

What Time Is It? Deep Learning Approaches For Circadian Rhythms, Forest Agostinelli, Nicholas Ceglia, Babak Shahbaba, Paolo Sassone-Corsi, Pierre Baldi

Faculty Publications

Motivation: Circadian rhythms date back to the origins of life, are found in virtually every species and every cell, and play fundamental roles in functions ranging from metabolism to cognition. Modern high-throughput technologies allow the measurement of concentrations of transcripts, metabolites and other species along the circadian cycle creating novel computational challenges and opportunities, including the problems of inferring whether a given species oscillate in circadian fashion or not, and inferring the time at which a set of measurements was taken.

Results: We first curate several large synthetic and biological time series datasets containing labels for both periodic and aperiodic …

Experimental Building Demonstration Model With Viscous Fluid Dampers, Blake Thomas Reeve, Brianna Jean Kufa, Aden Malek Stepanians, Sophie Carmion Ratkovich

Architectural Engineering

The Architectural Engineering major places a heavy emphasis on structural dynamics and the role of wind and seismic loading in building analysis and design. Buildings of high importance that are critical to community function, such as hospitals, often utilize supplemental damping devices like supplemental viscous fluid dampers or base isolators to reduce the overall demands on the structural system. The design and analysis of these dampers are typically not taught at the undergraduate level, and is frequently performed by mechanical engineers, in lieu of structural engineers.

To better understand and research building behavior with supplemental damping devices, our multi-disciplinary team …

Dual Formulations For Optimizing Dec-Pomdp Controllers, Akshat Kumar, Hala Mostafa, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Decentralized POMDP is an expressive model for multi-agent planning. Finite-state controllers (FSCs)---often used to represent policies for infinite-horizon problems---offer a compact, simple-to-execute policy representation. We exploit novel connections between optimizing decentralized FSCs and the dual linear program for MDPs. Consequently, we describe a dual mixed integer linear program (MIP) for optimizing deterministic FSCs. We exploit the Dec-POMDP structure to devise a compact MIP and formulate constraints that result in policies executable in partially-observable decentralized settings. We show analytically that the dual formulation can also be exploited within the expectation maximization (EM) framework to optimize stochastic FSCs. The resulting EM algorithm …

Demo: Ta$Ker: Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Thivya Kandappu, Randy Tandriansyah, Archan Misra

Research Collection School Of Computing and Information Systems

We design and develop TA$Ker, a real-world mobile crowd- sourcing platform to empirically study the worker responses to various task recommendation and selection strategies.

Poster: Improving Communication And Communicability With Smarter Use Of Text-Based Messages On Mobile And Wearable Devices, Kenny T. W. Choo

Research Collection School Of Computing and Information Systems

While smartphones have undoubtedly afforded many modern conveniences such as emails, instant messaging or web search, the notifications from smartphones conversely impact our lives through a deluge of information, or stress arising from expectations that we should turn our immediate attention to them (e.g., work emails). In my latest research, we find that the glanceability of smartwatches may provide an opportunity to reduce the perceived disruption from mobile notifications. Text is a common medium for communication in smart devices, the application of natural language processing on text, together with the physical affordances of smartwatches, present exciting opportunities for research to …

Rapid Android Parser For Investigating Dex Files (Rapid), Xiaolu Zhang, Frank Breitinger, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

Android malware is a well-known challenging problem and many researchers/vendors/practitioners have tried to address this issue through application analysis techniques. In order to analyze Android applications, tools decompress APK files and extract relevant data from the Dalvik EXecutable (DEX) files. To acquire the data, investigators either use decompiled intermediate code generated by existing tools, e.g., Baksmali or Dex2jar or write their own parsers/dissemblers. Thus, they either need additional time because of decompiling the application into an intermediate representation and then parsing text files, or they reinvent the wheel by implementing their own parsers. In this article, we present Rapid Android …

Strategic Planning For Setting Up Base Stations In Emergency Medical Systems, Supriyo Ghosh, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Emergency Medical Systems (EMSs) are an important component of public health-care services. Improving infrastructure for EMS and specifically the construction of base stations at the ”right” locations to reduce response times is the main focus of this paper. This is a computationally challenging task because of the: (a) exponentially large action space arising from having to consider combinations of potential base locations, which themselves can be significant; and (b) direct impact on the performance of the ambulance allocation problem, where we decide allocation of ambulances to bases. We present an incremental greedy approach to discover the placement of bases that …

Poster: Air Quality Friendly Route Recommendation System, Savina Singla, Divya Bansal, Archan Misra

Research Collection School Of Computing and Information Systems

To model the overall personal inhalation of hazardous gases through the air (both indoor and outdoor) by an individual, provide air quality friendly route recommendations, thus raising the overall quality of urban movement and living healthy life.

Designing And Comparing Multiple Portfolios Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir

Research Collection School Of Computing and Information Systems

Algorithm portfolios seek to determine an effective set of algorithms that can be used within an algorithm selection framework to solve problems. A limited number of these portfolio studies focus on generating different versions of a target algorithm using different parameter configurations. In this paper, we employ a Design of Experiments (DOE) approach to determine a promising range of values for each parameter of an algorithm. These ranges are further processed to determine a portfolio of parameter configurations, which would be used within two online Algorithm Selection approaches for solving different instances of a given combinatorial optimization problem effectively. We …

Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Evolutionary Algorithm is a well-known meta-heuristics paradigm capable of providing high-quality solutions to computationally hard problems. As with the other meta-heuristics, its performance is often attributed to appropriate design choices such as the choice of crossover operators and some other parameters. In this chapter, we propose a continuous state Markov Decision Process model to select crossover operators based on the states during evolutionary search. We propose to find the operator selection policy efficiently using a self-organizing neural network, which is trained offline using randomly selected training samples. The trained neural network is then verified on test instances not used for …

Sim Card Forensics: Digital Evidence, Nada Ibrahim, Nuha Al Naqbi, Farkhund Iqbal, Omar Alfandi

Annual ADFSL Conference on Digital Forensics, Security and Law

With the rapid evolution of the smartphone industry, mobile device forensics has become essential in cybercrime investigation. Currently, evidence forensically-retrieved from a mobile device is in the form of call logs, contacts, and SMSs; a mobile forensic investigator should also be aware of the vast amount of user data and network information that are stored in the mobile SIM card such as ICCID, IMSI, and ADN. The aim of this study is to test various forensic tools to effectively gather critical evidence stored on the SIM card. In the first set of experiments, we compare the selected forensic tools in …

Assessing The Gap: Measure The Impact Of Phishing On An Organization, Brad Wardman

Annual ADFSL Conference on Digital Forensics, Security and Law

Phishing has become one of the most recognized words associated with cybercrime. As more organizations are being targeted by phishing campaigns, there are more options within the industry to deter such attacks. However, there is little research into how much damage these campaigns are causing organizations. This paper will show how financial organizations can be impacted by phishing and present a method for accurately quantifying resultant monetary losses. The methodology presented in this paper can be adapted to other organizations in order to quantify phishing losses across industries.

Keywords: phishing, cybercrime, economics

Wban Security Management In Healthcare Enterprise Environments, Karina Bahena, Manghui Tu

Annual ADFSL Conference on Digital Forensics, Security and Law

As healthcare data are pushed online, consumers have raised big concerns on the breach of their personal information. Law and regulations have placed businesses and public organizations under obligations to take actions to prevent such data breaches. Various vulnerabilities have been identified in healthcare enterprise environments, in which the Wireless Body Area Networks (WBAN) remains to be a major vulnerability, which can be easily taken advantage of by determined adversaries. Thus, vulnerabilities of WBAN systems and the effective countermeasure mechanisms to secure WBAN are urgently needed. In this research, first, the architecture of WBAN system has been explored, and the …

Forensics Analysis Of Privacy Of Portable Web Browsers, Ahmad Ghafarian

Annual ADFSL Conference on Digital Forensics, Security and Law

Web browser vendors offer a portable web browser option which is considered as one of the features that provides user privacy. Portable web browser is a browser that can be launched from a USB flash drive without the need for its installation on the host machine. Most popular web browsers have portable versions of their browsers as well. Portable web browsing poses a great challenge to computer forensic investigators who try to reconstruct the past browsing history, in case of any computer incidence. This research examines various sources in the host machine such as physical memory, temporary, recent, event files, …

Reverse Engineering A Nit That Unmasks Tor Users, Matthew Miller, Joshua Stroschein, Ashley Podhradsky

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper is a case study of a forensic investigation of a Network Investigative Technique (NIT) used by the FBI to deanonymize users of a The Onion Router (Tor) Hidden Service. The forensic investigators were hired by the defense to determine how the NIT worked. The defendant was ac- cused of using a browser to access illegal information. The authors analyzed the source code, binary files and logs that were used by the NIT. The analysis was used to validate that the NIT collected only necessary and legally authorized information. This paper outlines the publicly available case details, how the …

Malware In The Mobile Device Android Environment, Diana Hintea, Robert Bird, Andrew Walker

Annual ADFSL Conference on Digital Forensics, Security and Law

exploit smartphone operating systems has exponentially expanded. Android has become the main target to exploit due to having the largest install base amongst the smartphone operating systems and owing to the open access nature in which application installations are permitted. Many Android users are unaware of the risks associated with a malware infection and to what level current malware scanners protect them. This paper tests how efficient the currently available malware scanners are. To achieve this, ten representative Android security products were selected and tested against a set of 5,560 known and categorized Android malware samples. The tests were carried …

Forensic Analysis Of Smartphone Applications For Privacy Leakage, Diana Hintea, Chrysanthi Taramonli, Robert Bird, Rezhna Yusuf

Annual ADFSL Conference on Digital Forensics, Security and Law

Smartphone and tablets are personal devices that have diffused to near universal ubiquity in recent years. As Smartphone users become more privacy-aware and -conscious, research is needed to understand how “leakage” of private information (personally identifiable information – PII) occurs. This study explores how leakage studies in Droid devices should be adapted to Apple iOS devices. The OWASP Zed Attack Proxy (ZAP) is examined for 50 apps in various categories. This study confirms that: (1) most apps transmit unencrypted sensitive PII, (2) SSL is used by some recipient websites, but without corresponding app compliance with SSL, and (3) most apps …

Inferring Previously Uninstalled Applications From Residual Partial Artifacts, Jim Jones, Tahir Khan, Kathryn Laskey, Alex Nelson, Mary Laamanen, Douglas White

Annual ADFSL Conference on Digital Forensics, Security and Law

In this paper, we present an approach and experimental results to suggest the past presence of an application after the application has been uninstalled and the system has remained in use. Current techniques rely on the recovery of intact artifacts and traces, e.g., whole files, Windows Registry entries, or log file entries, while our approach requires no intact artifact recovery and leverages trace evidence in the form of residual partial files. In the case of recently uninstalled applications or an instrumented infrastructure, artifacts and traces may be intact and complete. In most cases, however, digital artifacts and traces are al- …

One-Time Pad Encryption Steganography System, Michael J. Pelosi, Gary Kessler, Michael Scott S. Brown

Annual ADFSL Conference on Digital Forensics, Security and Law

In this paper we introduce and describe a novel approach to adaptive image steganography which is combined with One-Time Pad encryption, and demonstrate the software which implements this methodology. Testing using the state-of-the-art steganalysis software tool StegExpose concludes the image hiding is reliably secure and undetectable using reasonably-sized message payloads (≤25% message bits per image pixel; bpp). Payload image file format outputs from the software include PNG, BMP, JP2, JXR, J2K, TIFF, and WEBP. A variety of file output formats is empirically important as most steganalysis programs will only accept PNG, BMP, and possibly JPG, as the file inputs.

Keywords: …

Applying Grounded Theory Methods To Digital Forensics Research, Ahmed Almarzooqi, Andrew Jones, Richard Howley

Annual ADFSL Conference on Digital Forensics, Security and Law

Deciding on a suitable research methodology is challenging for researchers. In this paper, grounded theory is presented as a systematic and comprehensive qualitative methodology in the emergent field of digital forensics research. This paper applies grounded theory in a digital forensics research project undertaken to study how organisations build and manage digital forensics capabilities. This paper gives a step-by-step guideline to explain the procedures and techniques of using grounded theory in digital forensics research. The paper gives a detailed explanation of how the three grounded theory coding methods (open, axial, and selective coding) can be used in digital forensics research. …

Covert6: A Tool To Corroborate The Existence Of Ipv6 Covert Channels, Raymond A. Hansen, Lourdes Gino, Dominic Savio

Annual ADFSL Conference on Digital Forensics, Security and Law

Covert channels are any communication channel that can be exploited to transfer information in a manner that violates the system’s security policy. Research in the field has shown that, like many communication channels, IPv4 and the TCP/IP protocol suite have been susceptible to covert channels, which could be exploited to leak data or be used for anonymous communications. With the introduction of IPv6, researchers are acutely aware that many vulnerabilities of IPv4 have been remediated in IPv6. However, a proof of concept covert channel system was demonstrated in 2006. A decade later, IPv6 and its related protocols have undergone major …