The Visual Analytics Research Team at Oak Ridge National Laboratory is looking for summer interns at all levels as well as post-docs, post-masters, and post-bacs. We are also looking for qualified full time candidates.

We have a variety of projects in the areas of cyber security/network defense and health care. Projects tend to be 'big data' type projects that leverage diverse open-source platforms and technologies, such as Hadoop, Storm, graph databases, node.js, and d3js. Successful candidates will perform research and development activities in visual analytics, HCI, user testing, machine learning, probabilistic modeling, data fusion, or distributed computing.

See below for more information on each of the programs. We also have post-masters and post-doc programs in visual analytics.

If you are interested, have questions, or intend to apply, please contact John Goodall, Sorry, you need javascript to view this email address.

DHS HS-STEM (undergrad)

The HS-STEM program is specific to one of our group's projects, "Visually Fusing Contextual Data for Situational Understanding". For more information on the project, see: https://www3.orau.gov/DHS-Ed/Posting/Details/78.

The U.S. Department of Homeland Security (DHS) sponsors a 10-week summer internship program for students majoring in homeland security related science, technology, engineering and mathematics (HS-STEM) disciplines. Undergraduate students receive a stipend of $500 per week ($5,000 for 10 weeks). The application deadline for summer 2013 is January 15.

DOE SULI (undergrad)

Science Undergraduate Laboratory Internship (SULI) encourages undergraduate students to pursue science, technology, engineering and mathematics careers by providing research experiences at DOE laboratories. Students receive a stipend of $500 per week during the internship period. Appointments are 10 weeks (summer term) or 16 weeks (semester term) and are offered fall/spring/summer. The application deadline for summer 2013 is January 10.

DOE HERE (undergrad, graduate)

Higher Education Research Experiences at Oak Ridge National Laboratory (HERE at ORNL) provides research opportunities and associated activities for students at all levels, beginning the term before college entrance through thesis/dissertation research, and higher education faculty. Stipend is determined by category of participant.

“The Truth” by Michael D’Antuono

This painting isn’t controversial at all.

Michael D’Antuono, and artist from New York City, painted this picture called “The Truth” for an art exhibit on President Obama’s 100th day in office. Held in Union Square Park, the painting was

“to be in a mock voting booth for people to view privately and then interviewed to express their own views.”

Instead, D’Antuono cancelled the event after receiving approximately 4,000 angry emails, many from conservative Christians who said he was 

“trying to promote the idea that liberals believe the president to literally be our savior.”

His original intention, he claims, was to paint a “metaphor” and not compare Obama to Jesus.

But, President Obama is neither dying, nor Jesus. So what’s the metaphor here?

“The Truth” is currently on display at the Bunker Hill Community College Art Gallery in Boston in his exhibit titled “Artists on the Stump — The Road to the White House 2012.”

What do you think about this painting, and what exactly is D’Antuono’s message?

How do you think President Obama would feel about this?

Courtesy of DoSomething.org

This photo went viral on Facebook a few days ago, and has received over 40,000 likes in the past four days.

Is this a war of the people?

Or is it a war of the government?

Whose war is this, anyways?

MS Thesis Defense

Stateless Detection of Malicious Traffic:
Emphasis on User Privacy

Paul Halvorsen

1:00pm Monday, 3 December 2012, ITE 346, UMBC

In order to allow flexibility in deployment location and to preserve user privacy we have performed research into stateless classification of network traffic. Stateless detection allows for flexibility in deployment location because traffic on a network does not necessarily follow the same path to and from the end points. By only requiring a single direction of traffic, we have the ability to deploy this classifier anywhere on a network. We also do not require the data from a packet which preserves user privacy and allows for the classification of encrypted traffic.

Our research shows that it is possible to determine if traffic is malicious by using packets traveling in a single direction and without the data contained in the packet. Our research shows that with the use of the timing of the packets, time to live value, and source and destination IP addresses and ports, it is possible to determine if the traffic is malicious. In this way we are able to deploy the classifier anywhere on a network, preserve user privacy, and classify encrypted traffic.

Committee members:

• Dr. Anupam Joshi (chair)
• Dr. Charles Nicholas
• Dr. Tim Finin