Summer 2015

Mentor: Dr. XiaoFeng Wang

Keywords: Android System, malicious attacks, vulnerabilities, Android System security

Abstract: Android System is a mobile open-source operating system (OS), developed by Google, utilized by a large community of users from around the globe [1]. Due to its free and vast ecosystem, users with good intentions as well as criminals have taken advantage of the OS, unfortunately, implementing malicious attacks on many of Android’s vulnerable applications [2]. Because of security risks and exposures facing Android OS, the primary concern has been exploring methods that enable Android to remain open-source and sustain a high level of security. As a result, this research investigates the recent vulnerabilities and security risks of Android System, in addition, utilizes one of vulnerabilities explored (CVE-2014-3500) to design and conduct an attack via application on Android mobile device. Essentially, this study will produce familiarity with how Android System security is approached and operated to keep the operating system secure for its users.

URL: http://nia.ecsu.edu/ur/1516/summerinterns/matthews_Android_poster.pdf

Title: Remote Sensing Archaeological Sites through Unmanned Aerial Vehicle (U.A.V.) Imaging

Spring 2015

Mentors: Edward Swindell, Dr. Malcom LeCompte

Team Members: Cornelius Holness, Tatyana Matthews, Khaliq Satchell

Keywords: archaeology, aerial imagery, DJI Phantom 2 Vision+, drone, remote sensing, U.A.V.

Abstract: Advances in technology and lowering cost make drones, or Unmanned Aerial Vehicles (U.A.V.), appealing platforms for remote sensing. Data acquired through these technologies have broad appeal and widespread application across many industries and disciplines. Archaeologists have used aerial imagery derived from many sources as a means of identifying sites and ancient landscapes, yet this imagery has traditionally been acquired through satellite and aircraft platforms making cost and time a primary concern. For this reason, the availability of inexpensive U.A.V.s afford archaeologists access to obtaining their own data at a fraction of the cost. However, are they effective? For the purposes of this study, the DJI Phantom 2 Vision+ UAV, along with supporting software, was evaluated for its ability to create visible light imagery and elevation datasets useful in remote sensing archaeological sites. To test its effectiveness, a site was chosen in Bertie County, North Carolina discovered in 2007. The Salmon Creek site (31BR264), as it is known, is partially understood from previous archaeological studies as the location of a 16th Century Native American village. This previous work provided a foundation which our results could be tested and evaluated against and proved important to our interpretation of the data. The project not only demonstrated the effectiveness of the U.A.V. to acquire usable datasets, but contributed to the ongoing research.

URL: http://nia.ecsu.edu/ur/1415/teams/uav/Index.html

Title: Apache Big Data Stack

Summer 2014

Mentor: Scott McCaulay

Keywords: Apache Big Data Stack, Chef, FutureGrid, Big Data

Abstract: As the amount of data generated around the world continues to accelerate by the second, the more the term Big Data finds its way into scientific conversation. Because of this tremendous surge, it has become imperative that such mass data use “computing power and space” for it to be processed, analyzed, and serve other purposes [1]. Hence, in order to meet head-on the enormous challenges rendered by Big Data, open source software from the Apache Foundation is evaluated as a “Big Data Stack” to support scientific computing. The approach to handling the complications surrounding Big Data involve installing and testing as many open-source software packages from the Apache Big Data Stack as possible on FutureGrid machines and later making those packages accessible utilizing Chef. The packages will be built into projects and from that point Chef will be used to transform the infrastructure of each project’s code, making it agile and accessible through a network of servers [2]. Essentially, this research will demonstrate how the Apache Big Data Stack can be used and applied to solve complex problems regarding Big Data.

URL: http://cloudmesh.github.io/reu/projects/bigdata.html

Title: Configuring and Customizing the HUBzero Experience

Spring 2014

Mentors: Je'aime Powell, Justin Deloatch

Team Members: Antonio Guion, Tatyana Matthews, Nigel Pugh

Keywords: HUBzero, gateway user experience

Abstract: HUBzero is an open source software package used to construct websites for scientific research and educational activities. HUBzero was originally created by researchers at Purdue University in conjunction with the National Science Foundation (NSF) who sponsored the Network for Computational Nanotechnology to support nanoHUB.org. The HUBzero platform currently supports over 40 hubs across a variety of disciplines, including cancer research, biofuels, climate modeling, water quality, education, and more.
The team investigated how HUBzero features are utilized for research, education, and scientific collaboration. The project involved configuring and customizing the user experience on a new hub. The team also learned how to work with simulation workspaces, plus the process of allowing groups to collaborate. Finally, the team learned how to publish the hub so that it could be viewed publicly and how to use the new database component.

To accomplish this, the HUBzero team members used data collected by the 2013 Research Experience for Undergraduates Pasquotank River Watershed Team who completed tests of five tributaries and the river itself. Streams tested were Newbegun Creek, Knobbs Creek, Areneuse Creek, Mill Dam Creek, and Sawyers Creek. The team uploaded test data to a database to determine how HUBzero handles databases.

URL: http://nia.ecsu.edu/ur/1314/teams/hubzero/index.html