UMBC researchers will combine sensors and social media to develop new flash flood alert system
Severe storms and rapidly accumulating rain recently contributed to historic flooding that caused extreme damage to the main street of Ellicott City, located not far from UMBC’s campus. This is not the first time this Howard County town has been affected by the intense rain in a short period of time.
A few years ago, Nirmalya Roy, assistant professor of information systems, was driving through a strong storm near Ellicott City when he was instructed to turn around by emergency personnel. Roy began thinking about how technology could help monitor flood-prone areas, alert authorities in real-time, and keep people out of harm’s way.
“After witnessing the devastating nature of flash flood in our own neighborhood, Ellicott City, now we understand even a fraction of a second can make a difference,” explains Roy.
Roy recently received a $225,000 grant from the National Science Foundation’s Computer and Network Systems. The funding will allow Roy to build a network of wireless sensors, using technology that is currently used in Spain but that has not yet been tested in the U.S., to monitor rainfall levels, develop predictive algorithms, and provide real-time flood updates to officials. The system will then be implemented in Howard County and Baltimore County to monitor future flood events in these areas.
The first phase of this project will seek to accurately monitor the depth of the water and speed at which accumulated water moves in a severe storm. This research is unique in how it combines more traditional data sources, from wireless sensors, with information from social media networks, like Twitter and Instagram, to forecast the severity of flash floods.
“This project will navigate the tradeoffs of combining the cyber, physical, and social aspects of a smart service system tuned to operate in an emergency situation in a smart city like real-time flash flood monitoring,” Roy explains.
Once the technology is implemented in flash-flood prone areas of Howard County and Baltimore County, human observations from social media will be incorporated to add contextual information about the weather event. Roy and Aryya Gangopadhyay, professor and chair of information systems, will combine data analytics and social network posts to understand the severity of the floods, to assist with the deployment of time-sensitive resources.
“We are thinking of adding a loud speaker module to our wireless sensor system to warn the people early, even before the emergency personnel get on the spot,” Roy says, “so that the daily commuters do not endanger their lives by driving further down the road, where they could be swept away by powerful streams of water.”
As the project progresses, Roy and Gangopadhyay will work with the National Institute of Standards and Technology’s Global City Team Challenge program to study the viability of the wireless sensor system in Howard and Baltimore Counties.
Roy’s work is featured in “UMBC prof from Ellicott City developing flood-warning system” in The Daily Record. The White House included Roy’s work in a press release about its Smart Cities Initiative.
Image: The bridge in Ellicott City, MD. Photo by Preservation Maryland, CC by-SA 2.0.
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Severe storms and rapidly accumulating rain recently contributed to historic flooding that caused extreme damage to the main street of Ellicott City, located not far from UMBC’s campus. This is...
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Tue, 06 Sep 2016 14:37:52 -0400
talk: Categorizing Misconceptions of Cybersecurity Reasoning
11:15am-12:30pm Friday, 9 Sept 2016, ITE 237
The UMBC Cyber Defense Lab presents
Categorizing Misconceptions of Cybersecurity Reasoning
Travis Scheponik, CSEE, UMBC
11:15am-12:30pm Friday, 9 September 2016, ITE 237
We present preliminary analysis of student responses to cybersecurity interview prompts.
During spring 2016, we interviewed twenty-six students at three diverse colleges and universities (UMBC, Prince George’s Community College, Bowie State University) to understand how they reason about cybersecurity. Each interview lasted approximately one hour during which we asked the subject to solve four cybersecurity problems. For this purpose, we developed twelve engaging interview prompts organized in three protocols each comprising four prompts. Using a paired expert-novice methodology, we are analyzing transcriptions of the interviews produced from audio and video recordings. The twelve prompts focused on five difficult and important concepts identified from a Delphi method with thirty-six experts, which we carried out in fall 2014.
Preliminary analysis of student responses reveals common misconceptions and problematic reasoning, including conflating concepts, biased reasoning, unsound logic, and factual errors. For example, students commonly conflate authentication and authorization, as well as encryption and hashing. Examples of biased reasoning include seeing the situation only from the user's perspective, placing inappropriately high trust in physical objects, and underestimating potential vulnerabilities from insider threats. Initially, we marked student statements as ``correct’’ or ``incorrect.’’ From the ``incorrect’’ responses, we identified misconceptions about cybersecurity. Then, we categorized why responses were incorrect and we identified a variety of biases and problematic reasonings.
Our motivation is to produce educational assessment tools that will measure how well students understand cybersecurity concepts, for the purpose of identifying effective ways to teach cybersecurity. Results of our work will also be useful in developing curricula, learning exercises, and other educational materials and policies.
Joint work with David Delatte, Geoffrey Herman, Michael Neary, Linda Oliva, Alan Sherman, and Julia Thompson. Support for this research is provided in part by the U.S. Department of Defense under CAE-R grants H98230-15-1-0294 and H98230-15-1-0273, and by the National Science Foundation under SFS grant 1241576. We will present our results at the Frontiers in Education Conference, October 12-15, 2016, in Erie, PA.
About the Speaker: Travis Scheponik is a PhD student in computer science at UMBC, working with Dr. Alan T. Sherman. His research interests include cybersecurity education.