Computer Engineering Commons^™

Data To Decisions For Cyberspace Operations, Steve Stone

Military Cyber Affairs

In 2011, the United States (U.S.) Department of Defense (DOD) named cyberspace a new operational domain. The U.S. Cyber Command and the Military Services are working to make the cyberspace environment a suitable place for achieving national objectives and enabling military command and control (C2). To effectively conduct cyberspace operations, DOD requires data and analysis of the Mission, Network, and Adversary. However, the DOD’s current data processing and analysis capabilities do not meet mission needs within critical operational timelines. This paper presents a summary of the data processing and analytics necessary to effectively conduct cyberspace operations.

Data And Network Optimization Effect On Web Performance, Steven Rosenberg, Surbhi Dangi, Isuru Warnakulasooriya

Surbhi Dangi

In this study, we measure the effects of two software approaches to improving data and network performance: 1. Content optimization and compression; and 2. Optimizing network protocols. We achieve content optimization and compression by means of BoostEdge by ActivNetworks and employ the SPDY network protocol by Google to lower the round trip time for HTTP transactions. Since the data and transport layers are separate, we conclude our investigation by studying the combined effect of these two techniques on web performance. Using document mean load time as the measure, we found that with and without packet loss, both BoostEdge and SPDY …

Learning Query And Image Similarities With Ranking Canonical Correlation Analysis, Ting Yao, Tao Mei, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

One of the fundamental problems in image search is to learn the ranking functions, i.e., similarity between the query and image. The research on this topic has evolved through two paradigms: feature-based vector model and image ranker learning. The former relies on the image surrounding texts, while the latter learns a ranker based on human labeled query-image pairs. Each of the paradigms has its own limitation. The vector model is sensitive to the quality of text descriptions, and the learning paradigm is difficult to be scaled up as human labeling is always too expensive to obtain. We demonstrate in this …

Estimation On Gibbs Entropy For An Ensemble, Lekhya Sai Sake

Electronic Theses, Projects, and Dissertations

In this world of growing technology, any small improvement in the present scenario would create a revolution. One of the popular revolutions in the computer science field is parallel computing. A single parallel execution is not sufficient to see its non-deterministic features, as same execution with the same data at different time would end up with a different path. In order to see how non deterministic a parallel execution can extend up to, creates the need of the ensemble of executions. This project implements a program to estimate the Gibbs Entropy for an ensemble of parallel executions. The goal is …

Modeling Information Reliability And Maintenance: A Systematic Literature Review, Daysi A. Guerra Garcia

Industrial Engineering Undergraduate Honors Theses

Operating a business efficiently depends on effective everyday decision-making. In turn, those decisions are influenced by the quality of data used in the decision-making process, and maintaining good data quality becomes more challenging as a business expands. Protecting the quality of the data and the information it generates is a challenge faced by many companies across all industrial sectors. As companies begin to use data from these large data bases they will need to begin to develop strategies for maintaining and assessing the reliability of the information they generate using this data. A considerable amount of literature exists on data …

Deep Multimodal Learning For Affective Analysis And Retrieval, Lei Pang, Shiai Zhu, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Social media has been a convenient platform for voicing opinions through posting messages, ranging from tweeting a short text to uploading a media file, or any combination of messages. Understanding the perceived emotions inherently underlying these user-generated contents (UGC) could bring light to emerging applications such as advertising and media analytics. Existing research efforts on affective computation are mostly dedicated to single media, either text captions or visual content. Few attempts for combined analysis of multiple media are made, despite that emotion can be viewed as an expression of multimodal experience. In this paper, we explore the learning of highly …

Direct Or Indirect Match? Selecting Right Concepts For Zero-Example Case, Yi-Jie Lu, Maaike De Boer, Hao Zhang, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

No abstract provided.

Vireo-Tno @ Trecvid 2015: Multimedia Event Detection, Hao Zhang, Yi-Jie Lu, Maaike De Boer, Frank Ter Haar, Zhaofan Qiu, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper presents an overview and comparative analysis of our systems designed for the TRECVID 2015 [1] multimedia event detection (MED) task. We submitted 17 runs, of which 5 each for the zeroexample, 10-example and 100-example subtasks for the Pre-Specified (PS) event detection and 2 runs for the 10-example subtask for the Ad-Hoc (AH) event detection. We did not participate in the Interactive Run. This year we focus on three different parts of the MED task: 1) extending the size of our concept bank and combining it with improved dense trajectories; 2) exploring strategies for semantic query generation (SQG); and …

Lesinn: Detecting Anomalies By Identifying Least Similar Nearest Neighbours, Guansong Pang, Kai Ming Ting, David Albrecht

Research Collection School Of Computing and Information Systems

We introduce the concept of Least Similar Nearest Neighbours (LeSiNN) and use LeSiNN to detect anomalies directly. Although there is an existing method which is a special case of LeSiNN, this paper is the first to clearly articulate the underlying concept, as far as we know. LeSiNN is the first ensemble method which works well with models trained using samples of one instance. LeSiNN has linear time complexity with respect to data size and the number of dimensions, and it is one of the few anomaly detectors which can apply directly to both numeric and categorical data sets. Our extensive …

Bridging Researchers’ Active Data Storage Needs, Matt Schultz

Matt Schultz

Gvsu Repository Migration Update, Matt Schultz

Matt Schultz

Big Data Proteogenomics And High Performance Computing: Challenges And Opportunities, Fahad Saeed

Parallel Computing and Data Science Lab Technical Reports

Proteogenomics is an emerging field of systems biology research at the intersection of proteomics and genomics. Two high-throughput technologies, Mass Spectrometry (MS) for proteomics and Next Generation Sequencing (NGS) machines for genomics are required to conduct proteogenomics studies. Independently both MS and NGS technologies are inflicted with data deluge which creates problems of storage, transfer, analysis and visualization. Integrating these big data sets (NGS+MS) for proteogenomics studies compounds all of the associated computational problems. Existing sequential algorithms for these proteogenomics datasets analysis are inadequate for big data and high performance computing (HPC) solutions are almost non-existent. The purpose of this …

Practical Guidance For Integrating Data Management Into Long-Term Ecological Monitoring Projects, Robert D. Sutter, Susan Wainscott, John R. Boetsch, Craig Palmer, David J. Rugg

Library Faculty Publications

Long-term monitoring and research projects are essential to understand ecological change and the effectiveness of management activities. An inherent characteristic of long-term projects is the need for consistent data collection over time, requiring rigorous attention to data management and quality assurance. Recent papers have provided broad recommendations for data management; however, practitioners need more detailed guidance and examples. We present general yet detailed guidance for the development of comprehensive, concise, and effective data management for monitoring projects. The guidance is presented as a graded approach, matching the scale of data management to the needs of the organization and the complexity …

From Physical Security To Cybersecurity, Arunesh Sinha, Thanh H. Nguyen, Debarun Kar, Matthew Brown, Milind Tambe, Albert Xin Jiang

Research Collection School Of Computing and Information Systems

Security is a critical concern around the world. In many domains from cybersecurity to sustainability, limited security resources prevent complete security coverage at all times. Instead, these limited resources must be scheduled (or allocated or deployed), while simultaneously taking into account the importance of different targets, the responses of the adversaries to the security posture, and the potential uncertainties in adversary payoffs and observations, etc. Computational game theory can help generate such security schedules. Indeed, casting the problem as a Stackelberg game, we have developed new algorithms that are now deployed over multiple years in multiple applications for scheduling of …

Api-Based Acquisition Of Evidence From Cloud Storage Providers, Andres E. Barreto

University of New Orleans Theses and Dissertations

Cloud computing and cloud storage services, in particular, pose a new challenge to digital forensic investigations. Currently, evidence acquisition for such services still follows the traditional approach of collecting artifacts on a client device. In this work, we show that such an approach not only requires upfront substantial investment in reverse engineering each service, but is also inherently incomplete as it misses prior versions of the artifacts, as well as cloud-only artifacts that do not have standard serialized representations on the client.

In this work, we introduce the concept of API-based evidence acquisition for cloud services, which addresses these concerns …

Integrity Coded Databases (Icdb) - An Evaluation Of Efficiency, Performance, And Practicality, Jake Rodden, Jyh-Haw Yeh (Mentor), Elmer Duran, Dan Kondratyuk

Idaho Conference on Undergraduate Research

Recently, cloud database storage has become an inexpensive and convenient option to store information; however, this relatively new area of service can be vulnerable to security breaches. Storing data in a foreign location requires the owner to relinquish control of their information. This opens the possibility for internal, malicious attacks that can involve the manipulation, omission, or addition of data. Our research tests a potential solution for retaining data as it was intended to be stored (known as integrity) in these cloud-stored databases: by converting the original databases to Integrity-Coded Databases (ICDB). ICDBs utilize Integrity Codes: cryptographic codes created for …

Converting Medical Service Provider Data Into A Unified Format For Processing, Brandon Krugman

Master's Theses (2009 -)

Most organizations process flat files regularly. There are different options for processing files, including SQL Server Integration Services (SSIS), BizTalk, SQL import job, and other Extract, Transform, and Load (ETL) processes. All of these options have very strict requirements for file formats. If the format of the file changes, all of these options throw a catastrophic error, and implementing a fix to handle the new format is difficult. With each of the methods, the new format needs to be configured in the development environment, and the data flow must be modified to process all of the changes. Due to the …

Creating A Data-Based Facebook Engagement Plan For Chabad At Binghamton, Justin Hayet

Capstone Projects 2015-Present

Core Capstone Question: How does Chabad at Binghamton maximize its online Facebook Engagement in a fashion which mirrors the needs of its diverse online stakeholders?

Schmalzbauer (2013) calculated that two thirds of America’s 400,000 Jewish college students attend schools with a Chabad chapter” (p. 120). Binghamton University’s student population is thirty percent Jewish, that is, 3,500 Jewish students (Hillel, 2014). Chabad at Binghamton’s seven full time staff members and student leadership of eighty-seven designated positions seek to engage all 3,500 of those students through weekly programs, Shabbat dinners, large scale programs and individual meetings. Chabad at Binghamton has been serving …

Oversubscribing Inotify On Embedded Platforms, Donald Percivalle, Scott Vanderlind

Computer Engineering

For most computers running the popular Linux operating system, the inte- grated kernel component inotify provides adequate functionality for monitor- ing changes to files present on the filesystem. However, for certain embedded platforms where resources are very limited and filesystems are very populated (like network attached storage (NAS) devices), inotify may not have enough resources to provide watchers for every file. This results in applications missing change notifications for files they have watched. This paper explores methods for using inotify most effectively on embedded systems by leveraging more la- tent storage. Benefits of this include a reduction in dropped notifications …

Big Data: Big Value And Big Concerns, Singapore Management University

Perspectives@SMU

Digital information can serve lots of purposes, but timeliness, relevance and privacy issues abound

A Modular Approach For Key-Frame Selection In Wide Area Surveillance Video Analysis, Almabrok Essa, Paheding Sidike, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

This paper presents an efficient preprocessing algorithm for big data analysis. Our proposed key-frame selection method utilizes the statistical differences among subsequent frames to automatically select only the frames that contain the desired contextual information and discard the rest of the insignificant frames.

We anticipate that such key frame selection technique will have significant impact on wide area surveillance applications such as automatic object detection and recognition in aerial imagery. Three real-world datasets are used for evaluation and testing and the observed results are encouraging.

Rest Api To Access And Manage Geospatial Pipeline Integrity Data, Alexandra Michelle Francis

Master's Theses

Today’s economy and infrastructure is dependent on raw natural resources, like crude oil and natural gases, that are optimally transported through a net- work of hundreds of thousands of miles of pipelines throughout America[28]. A damaged pipe can negatively a↵ect thousands of homes and businesses so it is vital that they are monitored and quickly repaired[1]. Ideally, pipeline operators are able to detect damages before they occur, but ensuring the in- tegrity of the vast amount of pipes is unrealistic and would take an impractical amount of time and manpower[1].

Natural disasters, like earthquakes, as well as construction are just …

Improving Automatic Name-Face Association Using Celebrity Images On The Web, Zhineng Chen, Bailan Feng, Chong-Wah Ngo, Caiyan Jia, Xiangsheng Huang

Research Collection School Of Computing and Information Systems

This paper investigates the task of automatically associating faces appearing in images (or videos) with their names. Our novelty lies in the use of celebrity Web images to facilitate the task. Specifically, we first propose a method named Image Matching (IM), which uses the faces in images returned from name queries over an image search engine as the gallery set of the names, and a probe face is classified as one of the names, or none of them, according to their matching scores and compatibility characterized by a proposed Assigning-Thresholding (AT) pipeline. Noting IM could provide guidance for association for …

Presentation On Evaluating The Creation And Preservation Challenges Of Photogrammetry-Based 3d Models, Michael J. Bennett

UConn Library Presentations

No abstract provided.

Evaluating The Creation And Preservation Challenges Of Photogrammetry-Based 3d Models, Michael J. Bennett

Published Works

Though the roots of photogrammetry can be traced back to photography’s earliest days, only recent advances in both digital technology and software applications have put the possibilities of 3D modeling from 2D source images in the hands of the greater cultural heritage community. The possibilities of such 3D digital rendering are many. With these possibilities come unique digital preservation challenges. This study explores basic close-range photogrammetry as applied to sample archival objects. Additionally, the latest BagIt and ZIP-based bundling formats along with repository-based solutions are also surveyed as potential 3D data management and archiving aggregators for resulting 3D models.

Data Management In Cloud Environments: Nosql And Newsql Data Stores, Katarina Grolinger, Wilson A. Higashino, Abhinav Tiwari, Miriam Am Capretz

Wilson A Higashino

: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the …

Data Integrity Verification In Cloud Computing, Katanosh Morovat

Graduate Theses and Dissertations

Cloud computing is an architecture model which provides computing and storage capacity as a service over the internet. Cloud computing should provide secure services for users and owners of data as well. Cloud computing services are a completely internet-based technology where data are stored and maintained in the data center of a cloud provider. Lack of appropriate control over the data might incur several security issues. As a result, some data stored in the cloud must be protected at all times. These types of data are called sensitive data. Sensitive data is defined as data that must be protected against …

Mining Patterns Of Unsatisfiable Constraints To Detect Infeasible Paths, Sun Ding, Hee Beng Kuan Tan, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

Detection of infeasible paths is required in many areas including test coverage analysis, test case generation, security vulnerability analysis, etc. Existing approaches typically use static analysis coupled with symbolic evaluation, heuristics, or path-pattern analysis. This paper is related to these approaches but with a different objective. It is to analyze code of real systems to build patterns of unsatisfiable constraints in infeasible paths. The resulting patterns can be used to detect infeasible paths without the use of constraint solver and evaluation of function calls involved, thus improving scalability. The patterns can be built gradually. Evaluation of the proposed approach shows …

Cloud Computing, Contractibility, And Network Architecture, Christopher S. Yoo

All Faculty Scholarship

The emergence of the cloud is heightening the demands on the network in terms of bandwidth, ubiquity, reliability, latency, and route control. Unfortunately, the current architecture was not designed to offer full support for all of these services or to permit money to flow through it. Instead of modifying or adding specific services, the architecture could redesigned to make Internet services contractible by making the relevant information associated with these services both observable and verifiable. Indeed, several on-going research programs are exploring such strategies, including the NSF’s NEBULA, eXpressive Internet Architecture (XIA), ChoiceNet, and the IEEE’s Intercloud projects.

Teaching Cybersecurity Using The Cloud, Khaled Salah, Mohammad Hammoud, Sherali Zeadally

Information Science Faculty Publications

Cloud computing platforms can be highly attractive to conduct course assignments and empower students with valuable and indispensable hands-on experience. In particular, the cloud can offer teaching staff and students (whether local or remote) on-demand, elastic, dedicated, isolated, (virtually) unlimited, and easily configurable virtual machines. As such, employing cloud-based laboratories can have clear advantages over using classical ones, which impose major hindrances against fulfilling pedagogical objectives and do not scale well when the number of students and distant university campuses grows up. We show how the cloud paradigm can be leveraged to teach a cybersecurity course. Specifically, we share our …