|The Leading Source for Global News and Information Covering the Ecosystem of High Productivity Computing / November 23, 2007|
RENO, Nev., Nov. 15 -- A new approach for protecting cyberinfrastructure won first place at the Third Annual Analytics Challenge at the SC07 conference in Reno, Nev.
Cyberinfrastructure refers to the Internet-based infrastructure that allows businesses, consumers and the government to use the Internet and Internet-based applications. There is a growing awareness that protecting cyberinfrastructure from interference by criminals and other threats is becoming a national priority.
A team led by the National Center for Data Mining (NCDM) at the University of Illinois at Chicago and including participants from Northwestern University, the University of Chicago, Argonne National Laboratory and the University of Southern California developed an application to protect cyberinfrastructure, called Angle.
Given the high volume of the data that is transported over the Internet, methods for identifying attacks on cyberinfrastructure can produce so many alerts that analysts monitoring the infrastructure are often overwhelmed. In these circumstances, it is common for analysts to miss new behavior that might be the beginning of new types of attacks. The Angle application developed by the team introduced a new algorithm for identifying possibly malicious activity for further study.
Since the Internet is distributed, so is the data that must be analyzed to protect it. With today's supercomputers, the data must be collected, transported to the supercomputer, and then transported back. For large data, the time required to do this can be a significant fraction of the total time required by the analysis.
One of the innovations of the Angle project was the use of a data and compute cloud so that the data could be left in place and computation performed over the data. Although cloud computing has been used in the past several years by companies such as Google, Yahoo, Amazon and Microsoft to provide their services, these cloud infrastructures, by and large, are based on the standard Internet. In contrast, the Sector data cloud used by the Angle Project was a second-generation data cloud that is based on wide area high performance networks. These high performance networks enabled the large data sets produced by the project to be handled easily.
"Winning the Analytics Challenge shows the potential that second generation data and compute clouds have for changing the way we manage and compute with large distributed data," said Robert Grossman, director of the National Center for Data Mining (NCDM) at the University of Illinois at Chicago and managing partner of Open Data Group.
The Angle Project was sponsored in part by CDAR, a Chicago-based research consortium that is developing new technologies and methodologies for analyzing large, complex and distributed data.
The National Center for Data Mining has led teams that have won two of the first three Analytic Challenges (at SC05 and SC07).
About the National Center for Data Mining (NCDM)
The National Center for Data Mining (NCDM) at the University of Illinois at Chicago (UIC) was founded in 1998 as a national resource for high-performance and distributed data mining and data intensive computing. NCDM performs research, hosts standards, operates testbeds, and engages in outreach. NCDM coordinates the development of the Predictive Model Markup Language (PMML), a standard for statistical and data mining models, and operates the Teraflow Network, a network for distributing large e-science datasets. For more information about NCDM, see www.ncdm.uic.edu.
About Consortium for Data Analysis Research (CDAR)
The Consortium for Data Analysis Research (CDAR) is a consortium that is developing new technology and methodologies for working with large, complex and distributed data. The consortium consists of The National Center for Data Mining at The University of Illinois at Chicago, the Computation Institute at University of Chicago, the International Center for Advanced Internet Research (iCAIR) at Northwestern University, the Mathematics and Computer Science Division at Argonne National Laboratory, and the Toyota Technological Institute at Chicago.
Source: National Center for Data Mining