Computer Sciences Commons^™

Masthead

Journal of Digital Forensics, Security and Law

No abstract provided.

Back Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

Front Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

Predicting Flavonoid Ugt Regioselectivity With Graphical Residue Models And Machine Learning., Arthur Rhydon Jackson

Electronic Theses and Dissertations

Machine learning is applied to a challenging and biologically significant protein classification problem: the prediction of flavonoid UGT acceptor regioselectivity from primary protein sequence. Novel indices characterizing graphical models of protein residues are introduced. The indices are compared with existing amino acid indices and found to cluster residues appropriately. A variety of models employing the indices are then investigated by examining their performance when analyzed using nearest neighbor, support vector machine, and Bayesian neural network classifiers. Improvements over nearest neighbor classifications relying on standard alignment similarity scores are reported.

Hybrid Matching And Risk Assessment Of The Misspelled Names Hmra, Cihan Varol

Theses and Dissertations

Companies acquire personal information from phone, World Wide Web, or email in order to sell or send an advertisement about their product. However, when this information is acquired, moved, copied or edited, the data may loose its quality. Often, the use of data administrators or a tool that has limited capabilities to correct the mistyped information can cause many problems. Moreover, most of the correction techniques are particularly implemented for the words used in daily conversations. Since personal names have different characteristics compared to general text, firstly, we proposed a hybrid matching algorithm (PNRS) which employs phonetic encoding, string matching …

Real Time Network Monitoring And Reporting System, Ricky Lee Massengale Sr.

Theses and Dissertations

With the ability of modern system developers to develop intelligent programs that allows machines to learn, modify and evolve themselves, current trends of reactionary methods to detect and eradicate malicious software code from infected machines is proving to be too costly. Addressing malicious software after an attack is the current methodology and should be a fallback approach. A modern approach should be to perpetually monitor the "enterprise network backbone" traffic and broadcast alerts while taking protective and pre-emptive measures, in the event that the traffic falls out of the bounds of pre-described norms. This work demonstrates that a synergy approach …

Realizing The Technical Advantages Of Star Transformation, Karen L. Darling

Regis University Student Publications (comprehensive collection)

Data warehousing and business intelligence go hand in hand, each gives the other purpose for development, maintenance and improvement. Both have evolved over a few decades and build upon initial development. Management initiatives further drive the need and complexity of business intelligence, while in turn expanding the end user community so that business change, results and strategy are affected at the business unit level. The literature, including a recent business intelligence user survey, demonstrates that query performance is the most significant issue encountered. Oracle's data warehouse 10g.2 is examined with improvements to query optimization via "best practice" through Star Transformation. …

An Investigation Into Rewriting A Security Policy For Loreto College, Paul M. Mwai

Regis University Student Publications (comprehensive collection)

Computers as well as the networking environments in which they operate have evolved into highly sophisticated and complex systems. The intricacy of these systems and especially the relationship between them forms the greatest area of vulnerabilities for organizations. (Whitman and Mattord, 2004) Information needs to be transmitted to and from the organization, and thus may be vulnerable within certain stages along the communications line. If at any stage of the process, the information is compromised, it could have a negative impact on the entire organization. Protective measures such as disaster recover plans, encryption/ decryption, and information system security controls, can …

Optimal Cryptographic Hardness Of Learning Monotone Functions, Dana Dachman-Soled, Homin K. Lee, Tal Malkin, Rocco A. Servedio, Andrew Wan, Hoeteck Wee

Publications and Research

Over the years a range of positive algorithmic results have been obtained for learning various classes of monotone Boolean functions from uniformly distributed random examples. Prior to our work, however, the only negative result for learning monotone functions in this model has been an information-theoretic lower bound showing that certain super-polynomial-size monotone circuits cannot be learned to accuracy 1/2+w(log n/ p n) (Blum, Burch, and Langford, FOCS’98). This is in contrast with the situation for nonmonotone functions, where a wide range of cryptographic hardness results establish that various “simple” classes of polynomial-size circuits are not learnable by polynomial-time algorithms.

In …

Scalable Multi-Core Model Checking Fairness Enhanced Systems, Yang Liu, Jun Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

Rapid development in hardware industry has brought the prevalence of multi-core systems with shared-memory, which enabled the speedup of various tasks by using parallel algorithms. The Linear Temporal Logic (LTL) model checking problem is one of the difficult problems to be parallelized or scaled up to multi-core. In this work, we propose an on-the-fly parallel model checking algorithm based on the Tarjan’s strongly connected components (SCC) detection algorithm. The approach can be applied to general LTL model checking or with different fairness assumptions. Further, it is orthogonal to state space reduction techniques like partial order reduction. We enhance our PAT …

Labrat™: Miniature Robot For Students, Researchers, And Hobbyists, Paul Robinette, Ryan Meuth, Ryanne Dolan, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

LabRat™ is an autonomous, self-contained mobile robot kit with batteries, motors, two bumper whisker sensors, and three infrared proximity sensors that double as channels for "Rat-to-Rat" communication. the vehicle determines its position with an optical sensor that detects movement in both lateral directions. the LabRat™ design is completely open source, including software examples and libraries. LabRat™ is designed to fit inside the body of a computer mouse and has applications in the classroom, the lab and the home. the device has been successfully used in an undergraduate robotics class. © 2009 IEEE.

Research In Semantic Web And Information Retrieval: Trust, Sensors, And Search, Krishnaprasad Thirunarayan

Kno.e.sis Publications

No abstract provided.

Large-Scale Distributed Coalition Formation, Daniel R. Karrels

Theses and Dissertations

The CyberCraft project is an effort to construct a large scale Distributed Multi-Agent System (DMAS) to provide autonomous Cyberspace defense and mission assurance for the DoD. It employs a small but flexible agent structure that is dynamically reconfigurable to accommodate new tasks and policies. This document describes research into developing protocols and algorithms to ensure continued mission execution in a system of one million or more agents, focusing on protocols for coalition formation and Command and Control. It begins by building large-scale routing algorithms for a Hierarchical Peer to Peer structured overlay network, called Resource-Clustered Chord (RC-Chord). RC-Chord introduces the …

Interactive Football Summarization, Brandon B. Moon

Theses and Dissertations

Football fans do not have the time to watch every game in its entirety and need an effective solution that summarizes them the story of the game. Human-generated summaries are often too short, requiring time and resources to create. We utilize the advantages of Interactive TV to create an automatic football summarization service that is cohesive, provides context, covers the necessary plays, and is concise. First, we construct a degree of interest function that ranks each play based on detailed, play-by-play game events as well as viewing statistics collected from an interactive viewing environment. This allows us to select the …

Bisecting Document Clustering Using Model-Based Methods, Aaron Samuel Davis

Theses and Dissertations

We all have access to large collections of digital text documents, which are useful only if we can make sense of them all and distill important information from them. Good document clustering algorithms that organize such information automatically in meaningful ways can make a difference in how effective we are at using that information. In this paper we use model-based document clustering algorithms as a base for bisecting methods in order to identify increasingly cohesive clusters from larger, more diverse clusters. We specifically use the EM algorithm and Gibbs Sampling on a mixture of multinomials as the base clustering algorithms …

Identifying Interesting Instances For Probabilistic Skylines, Yinian Qi, Mikhail J. Atallah

Department of Computer Science Technical Reports

No abstract provided.

Noninvasive Estimation Of Pulmonary Artery Pressure Using Heart Sound Analysis, Aaron W. Dennis

Theses and Dissertations

Right-heart catheterization is the most accurate method for estimating pulmonary artery pressure (PAP). Because it is an invasive procedure it is expensive, exposes patients to the risk of infection, and is not suited for long-term monitoring situations. Medical researchers have shown that PAP influences the characteristics of heart sounds. This suggests that heart sound analysis is a potential noninvasive solution to the PAP estimation problem. This thesis describes the development of a prototype system, called PAPEr, which estimates PAP noninvasively using heart sound analysis. PAPEr uses patient data with machine learning algorithms to build models of how PAP affects heart …

Fused Visible And Infrared Video For Use In Wilderness Search And Rescue, Dennis Eggett, Michael A. Goodrich, Bryan S. Morse, Nathan Rasmussen

Faculty Publications

Mini Unmanned Aerial Vehicles (mUAVs) have the potential to assist Wilderness Search and Rescue groups by providing a bird’s eye view of the search area. This paper proposes a method for augmenting visible-spectrum searching with infrared sensing in order to make use of thermal search clues. It details a method for combining the color and heat information from these two modalities into a single fused display to reduce needed screen space for remote field use. To align the video frames for fusion, a method for simultaneously pre-calibrating the intrinsic and extrinsic parameters of the cameras and their mount using a …

Development And Implementation Of High-Throughput Snpgenotyping In Barley, Serdar Bozdag, Timothy J. Close, Prasanna R. Bhat, Stefano Lonardi, Yonghui Wu, Nils Rostoks, Luke Ramsay, Arnis Druka, Nils Stein, Jan T. Svensson, Steve Wanamaker, Mikeal L. Roose, Matthew J. Moscou, Shiaoman Chao, Rajeev K. Varshney, Peter Szucs, Kazuhiro Sato, Patrick M. Hayes, David E. Matthews, Andris Kleinhofs, Gary J. Muehlbauer, Joseph Deyoung, David F. Marshall, Kavitha Madishetty, Raymond D. Fenton, Pascal Condamine, Andreas Graner, Robbie Waugh

Mathematics, Statistics and Computer Science Faculty Research and Publications

Background

High density genetic maps of plants have, nearly without exception, made use of marker datasets containing missing or questionable genotype calls derived from a variety of genic and non-genic or anonymous markers, and been presented as a single linear order of genetic loci for each linkage group. The consequences of missing or erroneous data include falsely separated markers, expansion of cM distances and incorrect marker order. These imperfections are amplified in consensus maps and problematic when fine resolution is critical including comparative genome analyses and map-based cloning. Here we provide a new paradigm, a high-density consensus genetic map of …

Biological Sequence Simulation For Testing Complex Evolutionary Hypotheses: Indel-Seq-Gen Version 2.0, Cory L. Strope

School of Computing: Dissertations, Theses, and Student Research

Reconstructing the evolutionary history of biological sequences will provide a better understanding of mechanisms of sequence divergence and functional evolution. Long-term sequence evolution includes not only substitutions of residues but also more dynamic changes such as insertion, deletion, and long-range rearrangements. Such dynamic changes make reconstructing sequence evolution history difficult and affect the accuracy of molecular evolutionary methods, such as multiple sequence alignments (MSAs) and phylogenetic methods. In order to test the accuracy of these methods, benchmark datasets are required. However, currently available benchmark datasets have limitations in their sizes and evolutionary histories of the included sequences are unknown. These …

Warning Based Browser Extension To Protect User Data Against Phishing Attacks, Sree Rama Konduri

Theses and Dissertations

There are currently many anti-phishing tools to combat against the phishing and web scams. Many of which are browser extensions that warn users when they are using suspected phishing websites. But most of the users are ignoring the warnings of the phishing site and providing their valuable credentials. Therefore, the focus of this research is to develop a browser extension, which manipulates the user credentials, whenever a user ignores anti-phishing tools warnings about malicious websites. This browser extension will protect user's information from being handed to attackers.

Event Coverage In Sparse Mobile Sensor Networks, Mark Snyder, Sriram Chellappan

Computer Science Faculty Research & Creative Works

Autonomous mobile sensors are employed with ever-increasing frequency, in applications ranging from search and rescue, detection of forest fires, and battlefield surveillance. in this paper, we consider a representative surveillance problem wherein a sparse number of mobile sensors are expected to cover events of interest in a deployment field. Each event appears for a certain time and then disappears. Furthermore, the location of each event and its duration is unknown. in this paper, we design a sensor movement strategy based on efficient traversal in the network to fulfill two objectives: maximizing event detection and minimizing detection delay. Analysis and simulations …

What Does Security Culture Look Like For Small Organizations?, Patricia A. Williams

Australian Information Security Management Conference

The human component is a significant factor in information security, with a large numbers of breaches occurring due to unintentional user error. Technical solutions can only protect information so far and thus the human aspect of security has become a major focus for discussion. Therefore, it is important for organisations to create a security conscious culture. However, currently there is no established representation of security culture from which to assess how it can be manoeuvred to improve the overall information security of an organization. This is of particular importance for small organizations who lack the resources in information security and …

Playing Safe: A Prototype Game For Raising Awareness Of Social Engineering, Michael Newbould, Stephen Furnell

Australian Information Security Management Conference

Social engineering is now a major threat to users and systems in the online context, and it is therefore vital to educate potential victims in order to reduce their susceptibility to the related attacks. However, as with other aspects of security education, this firstly requires a means of getting the user’s attention. This paper presents details of an awarenessraising game that was developed in order to educate users in a more interactive way. A board game approach, combining reference material with themed multiple-choice questions, was implemented as an initial prototype, and evaluated with 21 users. The results suggested that the …

Mining Data From Multiple Software Development Projects, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao, Naeem Seliya

Computer Science Faculty Publications

A large system often goes through multiple software project development cycles, in part due to changes in operation and development environments. For example, rapid turnover of the development team between releases can influence software quality, making it important to mine software project data over multiple system releases when building defect predictors. Data collection of software attributes are often conducted independent of the quality improvement goals, leading to the availability of a large number of attributes for analysis. Given the problems associated with variations in development process, data collection, and quality goals from one release to another emphasizes the importance of …

Directed Coverage In Wireless Sensor Networks: Concept And Quality, Xiaole Bai, Lei Ding, Jin Teng, Sriram Chellappan, Changqing Xu, Dong Xuan

Computer Science Faculty Research & Creative Works

In this paper, we introduce a new type of coverage for wireless sensor networks, called Directed Coverage (D-Coverage). Basically, D-Coverage is the coverage provided by a sensor network monitoring an area between two boundaries, through which the intruder attempts to penetrates the area. We also study how to measure the quality of D-Coverage. Our first evaluation approach is a projection-Based simple approach, while our second approach is a more comprehensive Markov chain-based approach. Our evaluation approaches can accurately evaluate the quality and provide good guidelines for sensor network deployment and run-time repair. ©2009 IEEE.

Recursive Decomposition Of Progress Graphs, David A. Cape, Bruce M. Mcmillin, Benjamin W. Passer, Mayur Thakur

Computer Science Faculty Research & Creative Works

Search of a state transition system is traditionally how deadlock detection for concurrent programs has been accomplished. This paper examines an approach to deadlock detection that uses geometric semantics involving the topo-logical notion of dihomotopy to partition the state space into components; after that the reduced state space is exhaustively searched. Prior work partitioned the state space inductively. in this paper we show that a recursive technique provides greater reduction of the size of the state transition system and therefore more efficient deadlock detection. If the preprocessing can be done efficiently, then for large problems we expect to see more …

Sparql Query Re-Writing For Spatial Datasets Using Partonomy Based Transformation Rules, Prateek Jain, Cory Andrew Henson, Amit P. Sheth, Peter Z. Yeh, Kunal Verma

Kno.e.sis Publications

Often the information present in a spatial knowledge base is represented at a different level of granularity and abstraction than the query constraints. For querying ontology’s containing spatial information, the precise relationships between spatial entities has to be specified in the basic graph pattern of SPARQL query which can result in long and complex queries. We present a novel approach to help users intuitively write SPARQL queries to query spatial data, rather than relying on knowledge of the ontology structure. Our framework re-writes queries, using transformation rules to exploit part-whole relations between geographical entities to address the mismatches between query …

A Local Qualitative Approach To Referral And Functional Trust, Krishnaprasad Thirunarayan, Dharan Althuru, Cory Andrew Henson, Amit P. Sheth

Kno.e.sis Publications

Trust and confidence are becoming key issues in diverse applications such as ecommerce, social networks, semantic sensor web, semantic web information retrieval systems, etc. Both humans and machines use some form of trust to make informed and reliable decisions before acting. In this work, we briefly review existing work on trust networks, pointing out some of its drawbacks. We then propose a local framework to explore two different kinds of trust among agents called referral trust and functional trust, that are modelled using local partial orders, to enable qualitative trust personalization. The proposed approach formalizes reasoning with trust, distinguishing between …

Privacy Preserving Portable Health Record (P³Hr), Pavan Roy Marupally, Vamsi Paruchuri, Sriram Chellappan

Computer Science Faculty Research & Creative Works

Personal health records (PHRs) offer significant potential to stimulate transformational changes in health care delivery and self-care by patients. There is a gap between today's personal health records (PHRs) and what patients say they want and need from this electronic tool for managing their health information. Current barriers to PHR adoption among patients include cost, concerns that information is not protected or private, inconvenience, design shortcomings, and the inability to share information across organizations. We propose a novel architecture to bridge the gap based on Privacy Preserving Portable Health Record(P³HR), a device that incorporates a smart card into …