Computer Sciences Commons^™

Deleting Collected Digital Evidence By Exploiting A Widely Adopted Hardware Write Blocker, Christopher S. Meffert, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

In this primary work we call for the importance of integrating security testing into the process of testing digital forensic tools. We postulate that digital forensic tools are increasing in features (such as network imaging), becoming networkable, and are being proposed as forensic cloud services. This raises the need for testing the security of these tools, especially since digital evidence integrity is of paramount importance. At the time of conducting this work, little to no published anti-forensic research had focused on attacks against the forensic tools/process.We used the TD3, a popular, validated, touch screen disk duplicator and hardware write blocker …

From Qualitative To Quantitative: Supporting Robot Understanding In Human-Interactive Path Planning, Daqing Yi

Theses and Dissertations

Improvements in robot autonomy are changing human-robot interaction from low-level manipulation to high-level task-based collaboration. When a robot can independently and autonomously executes tasks, a human in a human-robot team acts as a collaborator or task supervisor instead of a tele-operator. When applying this to planning paths for a robot's motion, it is very important that the supervisor's qualitative intent is translated into aquantitative model so that the robot can produce a desirable consequence. In robotic path planning, algorithms can transform a human's qualitative requirement into a robot's quantitative model so that the robot behavior satisfies the human's intent. In …

Comon+: A Cooperative Context Monitoring System For Multi-Device Personal Sensing Environments, Youngki Lee, Seungwoo Kang, Chulhong Min, Younghyun Ju, Inseok Hwang, Junehwa Song

Research Collection School Of Computing and Information Systems

Continuous mobile sensing applications are emerging. Despite their usefulness, their real-world adoption has been slow. Many users are turned away by the drastic battery drain caused by continuous sensing and processing. In this paper, we propose CoMon+, a novel cooperative context monitoring system, which addresses the energy problem through opportunistic cooperation among nearby users. For effective cooperation, we develop a benefit-aware negotiation method to maximize the energy benefit of context sharing. CoMon+ employs heuristics to detect cooperators who are likely to remain in the vicinity for a long period of time, and the negotiation method automatically devises a cooperation plan …

Revocable And Decentralized Attribute-Based Encryption, Hui Cui, Deng, Robert H.

Research Collection School Of Computing and Information Systems

In this paper, we propose a revocable and decentralized attribute-based encryption (ABE) system that splits the task of decryption key generation across multiple attribute authorities (AAs) without requiring any central party such that it achieves attribute revocation by simply stopping updating of the corresponding private key. In our system, a party can easily behave as an AA by creating a public and private key pair without any global communication except the creation for the common system parameters, under which it can periodically issue/update private key components for users that reflect their attributes, and an AA can freely leave the system …

New Developments In Metaheuristics And Their Applications: Selected Extended Contributions From The 10th Metaheuristics International Conference (Mic 2013), Hoong Chuin Lau, Günther R. Raidl, Pascal Van Hentenryck

Research Collection School Of Computing and Information Systems

No abstract provided.

Tafloc: Time-Adaptive And Fine-Grained Device-Free Localization With Little Cost, Liqiong Chang, Jie Xiong, Xiaojiang Chen, Ju Wang, Junhao Hu, Wei Wang

Research Collection School Of Computing and Information Systems

Many emerging applications drive the needs of device-free localization (DfL), in which the target can be localized without any device attached. Because of the ubiquitousness of WiFi infrastructures nowadays, the widely available Received Signal Strength (RSS) information at the WiFi Access points are commonly employed for localization purposes. However, current RSS based DfL systems have one main drawback hindering their real-life applications. That is, the RSS measurements (fingerprints) vary slowly in time even without any change in the environment and frequent updates of RSS at each location lead to a high human labor cost. In this paper, we propose an …

Extending The Network: The Influence Of Offline Friendship On Twitter Network, Young Soo Kim, Kyungsub Stephen Choi, Felicia Natali

Research Collection School Of Computing and Information Systems

Twitter effectively provides a communication platform that allows users to strengthen or augment relationships with their close ones. It is a common scene to see groups of people in continuing group communication from offline to online using tools such as Twitter. Furthermore, it is also possible to meet new friends via online encounter. Under these circumstances, there would be friends who are both offline and online, or only in online. Many of earlier Twitter network studies focused on the network effects’ direction going from online to offline network. This paper explores the opposite direction, going from offline to online network. …

Detecting Communities Using Coordination Games: A Short Paper, Radhika Arava, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Communities typically capture homophily as people of the same community share many common features. This paper is motivated by the problem of community detection in social networks, as it can help improve our understanding of the network topology. Given the selfish nature of humans to align with like-minded people, we employ game theoretic models and algorithms to detect communities in this paper. Specifically, we employ coordination games to represent interactions between individuals in a social network. We provide a novel and scalable two phased algorithm NashOverlap to compute an accurate overlapping community structure in the given network. We evaluate our …

Fine-Grained Appliance Usage And Energy Monitoring Through Mobile And Power-Line Sensing, Nirmalya Roy, Nilavra Pathak, Archan Misra

Research Collection School Of Computing and Information Systems

To promote energy-efficient operations in residential and office buildings, non-intrusive load monitoring (NILM) techniques have been proposed to infer the fine-grained power consumption and usage patterns of appliances from power-line measurement data. Fine-grained monitoring of everyday appliances (such as toasters and coffee makers) can not only promote energy-efficient building operations, but also provide unique insights into the context and activities of individuals. Current building-level NILM techniques are unable to identify the consumption characteristics of relatively low-load appliances, whereas smart-plug based solutions incur significant deployment and maintenance costs. In this paper, we investigate an intermediate architecture, where smart circuit breakers provide …

Singapore In Motion: Insights On Public Transport Service Level Through Farecard And Mobile Data Analytics, Hasan Poonawala, Vinay Kolar, Sebastien Blandin, Laura Wynter, Sambit Sahu

Research Collection School Of Computing and Information Systems

Given the changing dynamics of mobility patterns and rapid growth of cities, transport agencies seek to respond more rapidly to needs of the public with the goal of offering an effective and competitive public transport system. A more data-centric approach for transport planning is part of the evolution of this process. In particular, the vast penetration of mobile phones provides an opportunity to monitor and derive insights on transport usage. Real time and historical analyses of such data can give a detailed understanding of mobility patterns of people and also suggest improvements to current transit systems. On its own, however, …

Understanding Patient Portal Use Intentions: Enablers And Inhibitors Of It Use, M. Moqbel, Fiona Fui-Hoon Nah, V. Bartelt, R. O’Dell

Research Collection School Of Computing and Information Systems

This research explores factors that influence patient’s intentions to use a hospital’s patient portal. Specifically, we investigate patient portal use intentions using two different perspectives: enablers of IT use (patient need for healthcare empowerment and healthcare professional encouragement) and inhibitors of IT use (privacy and security concerns). Drawing on theories of privacy calculus and protection motivation, we propose a research model to assess the relationships between the enablers and inhibitors of IT use as well as their effects on patient portal adoption. We will administer a survey questionnaire to existing patients of a major hospital in the Midwest and employ …

Design And Evaluation Of Advanced Collusion Attacks On Collaborative Intrusion Detection Networks In Practice, Weizhi Meng, Xiapu Luo, Wenjuan Li, Yan Li

Research Collection School Of Computing and Information Systems

To encourage collaboration among single intrusion detection systems (IDSs), collaborative intrusion detection networks (CIDNs) have been developed that enable different IDS nodes to communicate information with each other. This distributed network infrastructure aims to improve the detection performance of a single IDS, but may suffer from various insider attacks like collusion attacks, where several malicious nodes can collaborate to perform adversary actions. To defend against insider threats, challenge-based trust mechanisms have been proposed in the literature and proven to be robust against collusion attacks. However, we identify that such mechanisms depend heavily on an assumption of malicious nodes, which is …

The Jvmcsp Runtime And Code Generator For Processj In Java, Cabel Dhoj Shrestha

UNLV Theses, Dissertations, Professional Papers, and Capstones

The modern day advancements in multi-core technologies require programmers to use the right tools and languages to fully harness their potentials. On that front, our endeavor lies in developing a new multipro- cessing programming language. Concurrent or parallel programs can be hard to get right because of locks, monitors, mutexes, etc. One solution is using a CSP based process-oriented language. Process-oriented programming alleviates many of the problems found in thread and lock programming by proper encapsu- lation of data, explicit synchronous message passing, and the ability to verify code to be free of deadlocks and livelocks by using tools like …

Dynamic Machine Level Resource Allocation To Improve Tasking Performance Across Multiple Processes, Richard Walter Thatcher

Boise State University Theses and Dissertations

Across the landscape of computing, parallelism within applications is increasingly important in order to track advances in hardware capability and meet critical performance metrics. However, writing parallel applications is difficult to do in a scalable way, which has led to the creation of tasking libraries and language extensions like OpenMP, Intel Threading Building Blocks, Qthreads, and more. These tools abstract parallel execution by expressing it in terms of work units (tasks) rather than specific hardware details. This abstraction enables scaling and allows programmers to write software solutions that can leverage whatever level of parallelism is available.However, the typical task scheduler …

Unfolding Convex Polyhedra Via Radially Monotone Cut Trees, Joseph O'Rourke

Computer Science: Faculty Publications

A notion of "radially monotone" cut paths is introduced as an effective choice for finding a non-overlapping edge-unfolding of a convex polyhedron. These paths have the property that the two sides of the cut avoid overlap locally as the cut is infinitesimally opened by the curvature at the vertices along the path. It is shown that a class of planar, triangulated convex domains always have a radially monotone spanning forest, a forest that can be found by an essentially greedy algorithm. This algorithm can be mimicked in 3D and applied to polyhedra inscribed in a sphere. Although the algorithm does …

Use Of Clustering Techniques For Protein Domain Analysis, Eric Rodene

School of Computing: Dissertations, Theses, and Student Research

Next-generation sequencing has allowed many new protein sequences to be identified. However, this expansion of sequence data limits the ability to determine the structure and function of most of these newly-identified proteins. Inferring the function and relationships between proteins is possible with traditional alignment-based phylogeny. However, this requires at least one shared subsequence. Without such a subsequence, no meaningful alignments between the protein sequences are possible. The entire protein set (or proteome) of an organism contains many unrelated proteins. At this level, the necessary similarity does not occur. Therefore, an alternative method of understanding relationships within diverse sets of proteins …

Color Image Segmentation Using The Bee Algorithm In The Markovian Framework, Vehbi Dragaj

Master of Science in Computer Science Theses

This thesis presents color image segmentation as a vital step of image analysis in computer vision. A survey of the Markov Random Field (MRF) with four different implementation methods for its parameter estimation is provided. In addition, a survey of swarm intelligence and a number of swarm based algorithms are presented. The MRF model is used for color image segmentation in the framework. This thesis introduces a new image segmentation implementation that uses the bee algorithm as an optimization tool in the Markovian framework. The experiments show that the new proposed method performs faster than the existing implementation methods with …

Perceived Effectiveness Of E-Learning For Technology Instruction In Public Library Staff Development Programs: A Survey Based On The Technology Acceptance Model, Julia Huprich

Master of Science in Information Technology Theses

The purpose of this research study was to determine the perceived effectiveness of e-learning for staff members in public libraries. In addition, the effects of user demographics - including a user’s age and gender - were analyzed to determine if these factors impacted the perceived effectiveness of e-learning as a training delivery model.

Davis’s Technology Acceptance Model (1989) was used to develop a questionnaire related to the perceived effectiveness and value of e-learning, and a survey of public library staff members across the United States was conducted. Results of the survey showed the impact that previous e-learning experience and the …

Towards Understanding And Developing Virtual Environments To Increase Accessibilities For People With Visual Impairments, Miao Dong

Master of Science in Computer Science Theses

The primary goal of this research is to investigate the possibilities of utilizing audio feedback to support effective Human-Computer Interaction Virtual Environments (VEs) without visual feedback for people with Visual Impairments. Efforts have been made to apply virtual reality (VR) technology for training and educational applications for diverse population groups, such as children and stroke patients. Those applications had already shown effects of increasing motivations, providing safer training environments and more training opportunities. However, they are all based on visual feedback. With the head related transfer functions (HRTFs), it is possible to design and develop considerably safer, but diversified training …

Artificial Intelligence And Amikacin Exposures Predictive Of Outcomes In Multidrug-Resistant Tuberculosis Patients, Chawangwa Modongo, Jotam G. Pasipanodya, Shashikant Srivastava, Nicola Zetola, Scott Williams, Giorgio Sirugo, Tawanda Gumbo

Dartmouth Scholarship

Aminoglycosides such as amikacin continue to be part of the backbone of treatment of multidrug-resistant tuberculosis (MDR- TB). We measured amikacin concentrations in 28 MDR-TB patients in Botswana receiving amikacin therapy together with oral levofloxacin, ethionamide, cycloserine, and pyrazinamide and calculated areas under the concentration-time curves from 0 to 24 h (AUC0 –24). The patients were followed monthly for sputum culture conversion based on liquid cultures. The median duration of amikacin therapy was 184 (range, 28 to 866) days, at a median dose of 17.30 (range 11.11 to 19.23) mg/kg. Only 11 (39%) pa- tients had sputum culture conversion during …

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 …

Super-Intelligence Challenges And Lossless Visual Representation Of High-Dimensional Data, Boris Kovalerchuk

All Faculty Scholarship for the College of the Sciences

Fundamental challenges and goals of the cognitive algorithms are moving super-intelligent machines and super-intelligent humans from dreams to reality. This paper is devoted to a technical way to reach some specific aspects of super-intelligence that are beyond the current human cognitive abilities. Specifically the proposed technique is to overcome inabilities to analyze a large amount of abstract numeric high-dimensional data and finding complex patterns in these data with a naked eye. Discovering patterns in multidimensional data using visual means is a long-standing problem in multiple fields and Data Science and Modeling in general. The major challenge is that we cannot …

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 …

Ciliate Codon Translator Program Manual, Quentin D. Altemose

Mathematics Summer Fellows

Understanding the evolutionary history of organisms allows us to better comprehend selective pressures and their effects on larger populations. In our study, we focused on analyzing the DNA of ciliate groups, which are single celled protozoans characterized by the presence of cilia on their outer membrane. We utilized the DNA of the organisms to analyze the changes in population genotype over time. We tested existing evolutionary models (designed to represent natural genetic variation over time in populations) against our data to identify the model with the best fit and likelihood. From the DNA and the evolutionary model with the highest …

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 …

Quantum Key Distribution: Boon Or Bust, Logan O. Mailloux, Douglas D. Hodson, Michael R. Grimaila, Colin V. Mclaughlin, Gerald B. Baumgartner

Faculty Publications

Quantum Key Distribution (QKD) is an emerging cybersecurity technology which provides the means for two geographically separated parties to grow “unconditionally secure” symmetric cryptographic keying material. Unlike traditional key distribution techniques, the security of QKD rests on the laws of quantum mechanics and not computational complexity. This unique aspect of QKD is due to the fact that any unauthorized eavesdropping on the key distribution channel necessarily introduces detectable errors (Gisin, Ribordy, Tittel, & Zbinden, 2002). This attribute makes QKD desirable for high-security environments such as banking, government, and military applications. However, QKD is a nascent technology where implementation non-idealities can …

Hyper-Heuristics, Daniel R. Tauritz, John Woodward

Computer Science Faculty Research & Creative Works

No abstract provided.

Bic-Lsu: Big Data Research Integration With Cyberinfrastructure For Lsu, Chui Hui Chiu, Nathan Lewis, Dipak Kumar Singh, Arghya Kusum Das, Mohammad M. Jalazai, Richard Platania, Sayan Goswami, Kisung Lee, Seung Jong Park

Computer Science Faculty Research & Creative Works

In recent years, big data analysis has been widely applied to many research fields including biology, physics, transportation, and material science. Even though the demands for big data migration and big data analysis are dramatically increasing in campus IT infrastructures, there are several technical challenges that need to be addressed. First of all, frequent big data transmission between storage systems in different research groups imposes heavy burdens on a regular campus network. Second, the current campus IT infrastructure is not designed to fully utilize the hardware capacity for big data migration and analysis. Last but not the least, running big …

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 …

Efficient Algorithms And Applications In Topological Data Analysis, Junyi Tu

USF Tampa Graduate Theses and Dissertations

Topological Data Analysis (TDA) is a new and fast growing research field developed over last two decades. TDA finds many applications in computer vision, computer graphics, scientific visualization, molecular biology, and material science, to name a few. In this dissertation, we make algorithmic and application contributions to three data structures in TDA: contour trees, Reeb graphs, and Mapper. From the algorithmic perspective, we design a parallel algorithm for contour tree construction and implement it in OpenCL. We also design and implement critical point pairing algorithms to compute persistence diagrams directly from contour trees, Reeb graphs, and Mapper. In terms of …