Physical Sciences and Mathematics Commons^™

Front Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

Masthead

Journal of Digital Forensics, Security and Law

No abstract provided.

Back Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

Implementing Namebers Using Microchip Implants: The Black Box Beneath The Skin, Katina Michael, M.G. Michael

Associate Professor Katina Michael

The use of electronic-based physical access cards to secure premises such as government buildings and large corporate offices has been in operation since the inception of bar code and magnetic-stripe cards in the 1970s. Over time, for secure access control, these first generation card technologies based on optical character recognition (OCR) and magnetic ink character recognition (MICR) were replaced by more sophisticated technologies such as smart cards and biometrics, containing encrypted data and techniques which were more difficult to dupe or to replicate \cite{michael2003a}.

An employee today wanting to gain access to their place of work, typically carries a photo …

Networks - I: Pre-Coordination Mechanism For Self Configuration Of Neighborhood Cells In Mobile Wi-Max, Abdul Qadeer, Khalid Khan

International Conference on Information and Communication Technologies

WiMax broadband services successfully providing triple play (Voice, Video and Data) support with combating the challenges of better quality and interoperability. Support for smooth mobility in real time with no wired infrastructure and being surrounded by GSM waves demanding a comprehensive and powerful network. Covering large areas through number of base stations which not only require time to configure but also need resources for implementation with a recurring cost of functionality. Automation is everywhere and to provide novel wireless services it is necessary to come up with some distinct features like intelligent base stations which have the capability of doing …

Learning The Structure Of Gene Regulatory Networks From Time Series Gene Expression Data, Haoni Li, Nan Wang, Ping Gong, Edward J. Perkins, Chaoyang Zhang

Faculty Publications

Background: Dynamic Bayesian Network (DBN) is an approach widely used for reconstruction of gene regulatory networks from time-series microarray data. Its performance in network reconstruction depends on a structure learning algorithm. REVEAL (REVerse Engineering ALgorithm) is one of the algorithms implemented for learning DBN structure and used to reconstruct gene regulatory networks (GRN). However, the two-stage temporal Bayes network (2TBN) structure of DBN that specifies correlation between time slices cannot be obtained by score metrics used in REVEAL.

Methods: In this paper, we study a more sophisticated score function for DBN first proposed by Nir Friedman for stationary …

Multi- Autonomous Vehicle Insertion-Extraction System (Mavies), Jamie C. Macbeth, Manal Habib, Armen Mkrtchyan, Missy Cummings

Computer Science: Faculty Publications

MAVIES (Multi-Autonomous Vehicle Insertion-Extraction System) is the culmination of a year-long multi-stakeholder e ort between UTRC and the Humans and Automation Lab at MIT to design a human inter- face for insertion and extraction missions with multiple UAVs and option- ally piloted rotorcraft. The design process is a successful application of the Hybrid Cognitive Task Analysis (hCTA) process that tracks dozens of tasks, decision-making processes and their associated situation aware- ness requirements to determine the proper allocation of responsibilities between the human operator and the automated mission planner.

This paper discusses the various accomplishments through several phases of a disciplined …

Hyperspectral Data Processing In A High Performance Computing Environment: A Parallel Best Band Selection Algorithm, Stefan Robila, Gerald Busardo

Department of Computer Science Faculty Scholarship and Creative Works

Hyperspectral data are characterized by a richness of information unique among various visual representations of a scene by representing the information in a collection of grayscale images with each image corresponding to a narrow interval in the electromagnetic spectrum. Such detail allows for precise identification of materials in the scene and promises to support advances in imaging beyond the visible range. However, hyperspectral data are considerably large and cumbersome to process and efficient computing solutions based on high performance computing are needed. In this paper we first provide an overview of hyperspectral data and the current state of the art …

Multivariate Models And Algorithms For Systems Biology, Lipi Rani Acharya

University of New Orleans Theses and Dissertations

Rapid advances in high-throughput data acquisition technologies, such as microarraysand next-generation sequencing, have enabled the scientists to interrogate the expression levels of tens of thousands of genes simultaneously. However, challenges remain in developingeffective computational methods for analyzing data generated from such platforms. In thisdissertation, we address some of these challenges. We divide our work into two parts. Inthe first part, we present a suite of multivariate approaches for a reliable discovery of geneclusters, often interpreted as pathway components, from molecular profiling data with replicated measurements. We translate our goal into learning an optimal correlation structure from replicated complete and incomplete …

Android Memory Capture And Applications For Security And Privacy, Joseph T. Sylve

University of New Orleans Theses and Dissertations

The Android operating system is quickly becoming the most popular platform for mobiledevices. As Android’s use increases, so does the need for both forensic and privacy toolsdesigned for the platform. This thesis presents the first methodology and toolset for acquiringfull physical memory images from Android devices, a proposed methodology for forensicallysecuring both volatile and non-volatile storage, and details of a vulnerability discovered by theauthor that allows the bypass of the Android security model and enables applications to acquirearbitrary permissions.

The Vulnerability Assessment And Penetration Testing Of Two Networks, Steven L. Simpson

Regis University Student Publications (comprehensive collection)

Vulnerability assessments and penetration testing are two approaches available for use by internet security practitioners to determine the security posture of information networks. By assessing network vulnerabilities and attempting to exploit found vulnerabilities through penetration testing security professionals are able to evaluate the effectiveness of their network defenses by identifying defense weaknesses, affirming the defense mechanisms in place, or some combination of the two. This project is a discussion of the methods and tools used during the vulnerability assessment and penetration testing, and the respective test results of two varied and unique networks. The assessment and testing of the first …

Technology Enhanced Learning: Students' Views, Eileen O'Donnell, Mary Sharp

Eileen O'Donnell

User feedback is very important in all areas of computer science especially in the development of computer applications. Hence, student feedback on the use of technology enhanced learning in higher education in Ireland is relevant to the quality of the learning resources to be created by learning designers and academics in the future. The book “Student Reactions to Learning with Technologies: Perceptions and Outcomes” (Moyle & Wijngaards, 2012) was published by IGI Global in October 2011. This book includes contributions from various authors who are interested in students’ feedback regarding how technology has impacted on their educational experience. This book …

A General Model For Continuous Noninvasive Pulmonary Artery Pressure Estimation, Robert Anthony Smith

Theses and Dissertations

Elevated pulmonary artery pressure (PAP) is a significant healthcare risk. Continuous monitoring for patients with elevated PAP is crucial for effective treatment, yet the most accurate method is invasive and expensive, and cannot be performed repeatedly. Noninvasive methods exist but are inaccurate, expensive, and cannot be used for continuous monitoring. We present a machine learning model based on heart sounds that estimates pulmonary artery pressure with enough accuracy to exclude an invasive diagnostic operation, allowing for consistent monitoring of heart condition in suspect patients without the cost and risk of invasive monitoring. We conduct a greedy search through 38 possible …

Its Training Update, Veronica Trammell

Veronica O. Trammell

No abstract provided.

Multiple Biolgical Sequence Alignment: Scoring Functions, Algorithms, And Evaluations, Ken D. Nguyen

Computer Science Dissertations

Aligning multiple biological sequences such as protein sequences or DNA/RNA sequences is a fundamental task in bioinformatics and sequence analysis. These alignments may contain invaluable information that scientists need to predict the sequences' structures, determine the evolutionary relationships between them, or discover drug-like compounds that can bind to the sequences. Unfortunately, multiple sequence alignment (MSA) is NP-Complete. In addition, the lack of a reliable scoring method makes it very hard to align the sequences reliably and to evaluate the alignment outcomes.

In this dissertation, we have designed a new scoring method for use in multiple sequence alignment. Our scoring method …

Towards Node Cooperation In Mobile Opportunistic Networks, Abderrahmen Mtibaa, Khaled Harras

Computer Science Faculty Works

Mobile devices such as smart-phones and tablets are becoming ubiquitous, with ever increasing communication capabilities. In situations where the necessary infrastructure is unavailable, costly, or overloaded, opportunistically connecting theses devices becomes a challenging area of research. Data is disseminated using nodes that store-carry-and-forward messages across the network. In such networks, node cooperation is fundamental for the message delivery process. Therefore, the lack of node cooperation (e.g., a node may refuse to act as a relay and settle for sending and receiving its own data) causes considerable degradation in the network. In order to ensure node cooperation in such networks, we …

Syntactic And Semantic Analysis And Visualization Of Unstructured English Texts, Saurav Karmakar

Computer Science Dissertations

People have complex thoughts, and they often express their thoughts with complex sentences using natural languages. This complexity may facilitate efficient communications among the audience with the same knowledge base. But on the other hand, for a different or new audience this composition becomes cumbersome to understand and analyze. Analysis of such compositions using syntactic or semantic measures is a challenging job and defines the base step for natural language processing.

In this dissertation I explore and propose a number of new techniques to analyze and visualize the syntactic and semantic patterns of unstructured English texts.

The syntactic analysis is …

A Perceptual Metric For Photo Retouching, Eric Kee, Hany Farid

Dartmouth Scholarship

In recent years, advertisers and magazine editors have been widely criticized for taking digital photo retouching to an extreme. Impossibly thin, tall, and wrinkle- and blemish-free models are routinely splashed onto billboards, advertisements, and magazine covers. The ubiquity of these unrealistic and highly idealized images has been linked to eating disorders and body image dissatisfaction in men, women, and children. In response, several countries have considered legislating the labeling of retouched photos. We describe a quantitative and perceptually meaningful metric of photo retouching. Photographs are rated on the degree to which they have been digitally altered by explicitly modeling and …

Framework To Secure Cloud-Based Medical Image Storage And Management System Communications, Timothy James Rostrom

Theses and Dissertations

Picture Archiving and Communication Systems (PACS) have been traditionally constrained to the premises of the healthcare provider. This has limited the availability of these systems in many parts of the world and mandated major costs in infrastructure for those who employ them. Public cloud services could be a solution that eases the cost of ownership and provides greater flexibility for PACS implementations. This could make it possible to bring medical imaging services to places where it was previously unavailable and reduce the costs associated with these services for those who utilize them. Moving these systems to public cloud infrastructure requires …

Kb-Anonymity: A Model For Anonymized Behavior-Preserving Test And Debugging Data, Aditya Budi, David Lo, Lingxiao Jiang, Lucia Lucia

David LO

It is often very expensive and practically infeasible to generate test cases that can exercise all possible program states in a program. This is especially true for a medium or large industrial system. In practice, industrial clients of the system often have a set of input data collected either before the system is built or after the deployment of a previous version of the system. Such data are highly valuable as they represent the operations that matter in a client's daily business and may be used to extensively test the system. However, such data often carries sensitive information and cannot …

Nort: Runtime Anomaly-Based Monitoring Of Malicious Behavior For Windows, Narcisa Andrea Milea, Siau-Cheng Khoo, David Lo, Cristi Pop

David LO

Protecting running programs from exploits has been the focus of many host-based intrusion detection systems. To this end various formal methods have been developed that either require manual construction of attack signatures or modelling of normal program behavior to detect exploits. In terms of the ability to discover new attacks before the infection spreads, the former approach has been found to be lacking in flexibility. Consequently, in this paper, we present an anomaly monitoring system, NORT, that verifies on-the-fly whether running programs comply to their expected normal behavior. The model of normal behavior is based on a rich set of …

Code Search Via Topic-Enriched Dependence Graph Matching, Shaowei Wang, David Lo, Lingxiao Jiang

David LO

Source code contains textual, structural, and semantic information, which can all be leveraged for effective search. Some studies have proposed semantic code search where users can specify query topics in a natural language. Other studies can search through system dependence graphs. In this paper, we propose a semantic dependence search engine that integrates both kinds of techniques and can retrieve code snippets based on expressive user queries describing both topics and dependencies. Users can specify their search targets in a free form format describing desired topics (i.e., high-level semantic or functionality of the target code); a specialized graph query language …

Search-Based Fault Localization, Shaowei Wang, David Lo, Lingxiao Jiang, - Lucia, Hoong Chuin Lau

David LO

Many spectrum-based fault localization measures have been proposed in the literature. However, no single fault localization measure completely outperforms others: a measure which is more accurate in localizing some bugs in some programs is less accurate in localizing other bugs in other programs. This paper proposes to compose existing spectrum-based fault localization measures into an improved measure. We model the composition of various measures as an optimization problem and present a search-based approach to explore the space of many possible compositions and output a heuristically near optimal composite measure. We employ two search-based strategies including genetic algorithm and simulated annealing …

Towards More Accurate Retrieval Of Duplicate Bug Reports, Chengnian Sun, David Lo, Siau-Cheng Khoo, Jing Jiang

David LO

In a bug tracking system, different testers or users may submit multiple reports on the same bugs, referred to as duplicates, which may cost extra maintenance efforts in triaging and fixing bugs. In order to identify such duplicates accurately, in this paper we propose a retrieval function (REP) to measure the similarity between two bug reports. It fully utilizes the information available in a bug report including not only the similarity of textual content in summary and description fields, but also similarity of non-textual fields such as product, component, version, etc. For more accurate measurement of textual similarity, we extend …

Bug Signature Minimization And Fusion, David Lo, Hong Cheng, Xiaoyin Wang

David LO

Debugging is a time-consuming activity. To help in debugging, many approaches have been proposed to pinpoint the location of errors given labeled failures and correct executions. While such approaches have been shown to be accurate, at times the location alone is not sufficient in helping programmers understand why the bug happens and how to fix it. Furthermore, a single location might not be powerful enough to discriminate failures from correct executions. To address the above challenges, there have been recent studies on extracting bug signatures which are composed of multiple locations appearing together in a particular order signifying an occurrence …

Finding Relevant Answers In Software Forums, Swapna Gottopati, David Lo, Jing Jiang

David LO

Online software forums provide a huge amount of valuable content. Developers and users often ask questions and receive answers from such forums. The availability of a vast amount of thread discussions in forums provides ample opportunities for knowledge acquisition and summarization. For a given search query, current search engines use traditional information retrieval approach to extract webpages containing relevant keywords. However, in software forums, often there are many threads containing similar keywords where each thread could contain a lot of posts as many as 1,000 or more. Manually finding relevant answers from these long threads is a painstaking task to …

Mining Top-K Large Structural Patterns In A Massive Network, Feida Zhu, Qiang Qu, David Lo, Xifeng Yan, Jiawei Han, Philip S. Yu

David LO

With ever-growing popularity of social networks, web and bio-networks, mining large frequent patterns from a single huge network has become increasingly important. Yet the existing pattern mining methods cannot offer the efficiency desirable for large pattern discovery. We propose Spider- Mine, a novel algorithm to efficiently mine top-K largest frequent patterns from a single massive network with any user-specified probability of 1 − ϵ. Deviating from the existing edge-by-edge (i.e., incremental) pattern-growth framework, SpiderMine achieves its efficiency by unleashing the power of small patterns of a bounded diameter, which we call “spiders”. With the spider structure, our approach adopts a …

Recommending People In Developers' Collaboration Network, Didi Surian, Nian Liu, David Lo, Hanghang Tong, Ee Peng Lim, Christos Faloutsos

David LO

Many software developments involve collaborations of developers across the globe. This is true for both open-source and closed-source development efforts. Developers collaborate on different projects of various types. As with any other teamwork endeavors, finding compatibility among members in a development team is helpful towards the realization of the team’s goal. Compatible members tend to share similar programming style and naming strategy, communicate well with one another, etc. However, finding the right person to work with is not an easy task. In this work, we extract information available from Sourceforge.Net, the largest database of open source software, and build developer …

Concern Localization Using Information Retrieval: An Empirical Study On Linux Kernel, Shaowei Wang, David Lo, Zhenchang Xing, Lingxiao Jiang

David LO

Many software maintenance activities need to find code units (functions, files, etc.) that implement a certain concern (features, bugs, etc.). To facilitate such activities, many approaches have been proposed to automatically link code units with concerns described in natural languages, which are termed as concern localization and often employ Information Retrieval (IR) techniques. There has not been a study that evaluates and compares the effectiveness of latest IR techniques on a large dataset. This study fills this gap by investigating ten IR techniques, some of which are new and have not been used for concern localization, on a Linux kernel …

Towards Succinctness In Mining Scenario-Based Specifications, David Lo, Shahar Maoz

David LO

Specification mining methods are used to extract candidate specifications from system execution traces. A major challenge for specification mining is succinctness. That is, in addition to the soundness, completeness, and scalable performance of the specification mining method, one is interested in producing a succinct result, which conveys a lot of information about the system under investigation but uses a short, machine and human-readable representation. In this paper we address the succinctness challenge in the context of scenario-based specification mining, whose target formalism is live sequence charts (LSC), an expressive extension of classical sequence diagrams. We do this by adapting three …