WIE Undergraduates: CS Scholars Projects
2009 Summer Research Projects
Please note that "Daily Activities" are provided as estimates of time commitment and do not include additional program activities.
- Security and Surveillance using Mobile Wireless Sensor Networks
Faculty Mentor: Dr. Sarah Bergbreiter, Mechanical Engineering - Quantification of Computer Security
Faculty Mentor: Dr. Michel Cukier, Mechanical Engineering - Designing the Next Generation of Software Test Automation Tools
Faculty Mentor: Dr. Atif Memon, Computer Science - Content Fingerprinting: Helping Your Favorite Online Community Legally
Faculty Mentor: Dr. Min Wu, Electrical and Computer Engineering
Security and Surveillance using Mobile Wireless Sensor Networks
Project Description
Wireless sensor networks can enable a host of new security and surveillance applications. However, to provide sensor coverage of a given space, these networks must be deployed in an appropriate manner. For hundreds to thousands of nodes, this deployment could take a great deal of time and resources. As the sensor size shrinks, it is expected that the number of sensors will grow even further.
One solution to this problem is to add mobility to the wireless sensors, creating networked robots from previously static sensors. Using their mobility, a dispersal algorithm can move the sensors from a single deployment spot to cover a much wider area. In addition, if some of these sensors fail or if somebody physically removes them from the network, the remaining mobile sensors should be able to cover the required space.
This summer project will allow the student to investigate new ideas for deploying networks to enable this kind of security. The student will research previous deployment algorithms and use computer simulation tools (Matlab or other) to investigate new dispersal ideas with simple sensor and mobility models. One challenge is to implement new algorithms without any robot location information -- one of the more difficult sensors to implement on a small robot. If time allows, the student will investigate implementing this algorithm on real robots.
CS Scholar Responsibilities and Daily Activities
All CS Scholars will be expected to perform background reading (10%) on previous work in mobile wireless sensor networks. All scholars will be trained on using Matlab or another simulation environment (20%) and each scholar will develop and test a new dispersal algorithm for mobile wireless sensor networks in this simulation environment (65%). The scholars will meet at least once a week to compare experiences and identify specific activities for ongoing study (5%). All scholars will compile their results for a presentation and report publication.
Quantification of Computer Security
Project Description
Most research in computer security focuses on developing methods and tools for preventing, detecting, or tolerating attacks or intrusions. Little research is conducted to quantify the security of a computer system. The Experimental Information Assurance Lab (EIAL) at the University of Maryland specializes in conducting experiments for quantifying various security aspects of a computer system. Recent research focused on: a) how to separate attacks among malicious traffic, b) how to analyze malicious activity over time, c) how to assess the threat of attacks due to IRC channels, d) how to understand behavior and diagnosing and finding solutions to issues encountered in organizational computer security systems using a systemic approach, namely system archetypes, e) How to build a profile of attacker behavior following a remote compromise, and f) how to analyze a large set of incident data using well-known tools developed by the software reliability community.
The Summer 2008 project focuses on modeling various parts of a large public university including attacks, networks, and users. More precisely, the focus will be on a large set of incident data (i.e., over 12,000 records collected over 6 years) and attack data collected by Intrusion Prevention Systems (IPSs) (i.e., about 4000 alerts a day since September 2006). The analysis and modeling activity will address among others: a) the correlation between incidents and IPS alerts, b) the evolution of the IPS data as a function of the attack type, and c) the evolution of the IPS data as a function of the location. This research will be an iterative process between model refinement and data collection and analysis to feed the models.
CS Scholar Responsibilities and Daily Activities
All CS Scholars will be expected to perform background reading (10%) on analysis methods and malicious traffic data collection. All Scholars will be trained on the test-bed deployed for collecting and analyzing malicious traffic (20%). Each scholar will analyze data and develop a model (65%). The Scholars will meet at least once a week to compare experiences and identify specific activities for ongoing study (5%). All Scholars will compile their results for a presentation and report publication.
Designing the Next Generation of Software Test Automation Tools
Project Description
Software testing is a critical component of the software development process and is required to ensure the safety, robustness and usability of software. Unfortunately, it is also complex, labor intensive and expensive, accounting for almost 67% of the total cost of software development. Hence, there has been significant research aimed at automating the testing process. Although
automation has achieved some success, many problems remain. In particular, it is not yet clear how to automate the testing of graphical user interfaces
(GUIs), which constitute an increasingly large portion of software systems (almost 50% of the total software code). Recognizing the importance of GUI testing, we have developed GUITAR, a GUI testing framework that presents a unified solution to the GUI testing problem. In the last four years, we have had considerable success in developing new technologies for GUI testing.
Most of the results of our research have been published. I encourage you to visit our publications page. Our emphasis has been on developing new event-based tools and techniques for various phases of GUI testing. Please look at http://guitar.cs.umd.edu.
The Summer 2009 project focuses on creating JUnit test cases from software GUI usage. More precisely, the focus will be on (1) identifying four subject applications for this work, (2) using code instrumenters to collect usage profiles, (3) creating Junit templates for all methods/classes in the subject applications, (4) selecting parameters for each test case from the collected information, and (5) composing integration tests.
CS Scholar Responsibilities and Daily Activities
All CS Scholars will be expected to perform background reading (10%) on unit testing and code instrumentation. All Scholars will be trained to use Junit and code instrumenters (10%). Each scholar will then collect instrumentation data for four subject applications (20%), study the collected data and use it to develop unit tests (40%) and integration tests (15%). The Scholars
will meet at least once a week to compare experiences and identify specific activities for ongoing study (5%). All Scholars will compile their results for a presentation and report publication.
Content Fingerprinting: Helping Your Favorite Online Community – Legally
Project Description
YouTube and other web services alike have revolutionized content sharing and online social networking by providing an easy-to-use platform for users to post and share video. At the same time, content owners have raised serious concerns on unauthorized uploads of copyrighted movies and TV shows to these websites, as witnessed by high-profile lawsuits filed against YouTube and Google. In order to deter copyright violation and more importantly, to help keep online communities alive legally, “content fingerprinting” technologies are deployed to compute a short string of bits to capture unique characteristics of each video and use it determine whether an uploaded video belongs to a set of copyrighted content or not. Content fingerprints are also used by such applications as Shazam on iPhone to use recordings of short audio clips to identify the song and provide information about the artist, the album, and where to buy.
Video and other multimedia data are typically stored in various formats and may exhibit minor differences among versions. Is it possible to identify that these different versions correspond to the same movie? The Summer 2009 project focuses on designing a benchmark suite to evaluate the performance of video fingerprinting schemes. As part of the project, students will be introduced to various fingerprinting algorithms and typical analog/digital processing that a video may undergo. Students will help create a database of reference videos with representatives from different genres such as animation, newscasts, movie scenes, sport telecasts, etc., subject to different processing. This benchmark suite will then be used to evaluate and compare the performance of different video identification schemes. If time permits, the students may also propose improvements, examine strategies to defeat content fingerprinting algorithms and devise countermeasures to resist such attacks.
CS Scholar Responsibilities and Daily Activities
All CS Scholars will be expected to perform background reading (10%) on previous work in video fingerprinting. All scholars will be trained on using programming and software tools to manipulate videos (20%). Scholars will be trained to create a test suite for evaluating and comparing different video fingerprinting schemes (65%). The scholars will meet at least once a week to compare experiences and identify specific activities for ongoing study (5%). All scholars will compile their results for a presentation and report publication.
