News Item: New ITR Grants

The competition was intense for NSF's ITR grants this year, with thousands of proposals received in the small, medium, and large ITR categories. When the dust settled, DAIS faculty had garnered four ITR grants, including one in the "large" category, two in the "medium" category, and one in the "small" category. They are:

Title: Responding to the Unexpected

This project aims to create robust information systems that enable first responders and decision-makers to make well-informed and better decisions, to prioritize their responses, and to focus on activities that have the highest potential to save lives and property. Such information systems must provide access to the right information by the right individuals and organizations at the right time. Social scientists play a crucial role in this project to investigate the nature of dynamic virtual organizations, such as the multi-agency response teams formed at the site of a disaster, and the social and cultural aspects of information sharing in such situations.

Title: Automated Trust Negotiation in Open Systems

Automated trust negotiation (ATN) is a new approach to access control and authentication for the open, flexible systems formed by sets of organizations that must dynamically form coalitions and work together to respond to unforeseen needs and opportunities. ATN enables open computing by assigning an access control policy to each resource that is to be made accessible to "outsiders"; an attempt to access the resource triggers a trust negotiation, consisting of the iterative, bilateral disclosure of digital credentials and related information.

This project will show that ATN is a practical solution to the access control and authentication problems of open computing systems, by resolving the most critical remaining theoretical and systems issues for the deployment of trust negotiation facilities. Specific areas that the project will address include access control policy languages for ATN, light-weight policy evaluation engines, improved ATN protocols and strategies compatible with the new languages, provable privacy and autonomy guarantees for negotiating parties, and a next-generation version of the TrustBuilder ATN prototype, demonstrating the deployment of ATN in a modular, reusable, and highly scalable implementation. These enhancements will be explored in the context of health care applications and additional scenarios supplied by the project partners.

Title: Automatic On-The-Fly Detection, Characterization, Recovery and Correction of Software Bugs in Production Runs

We propose to develop a comprehensive debugging system for automatic on-the-fly debugging of production runs. Our system addresses all the aspects of debugging, including bug detection, characterization, recovery and correction. The system tightly integrates innovations in computer hardware, operating system, data mining, and compiler support. More specifically, our proposed system hinges on the following innovations: (1) low-overhead compiler-directed checking to detect bugs and pass information to the data miner, operating system, and hardware to characterize the bugs; (2) Low-overhead data mining algorithms that build and use models for bug detection, characterization, and correction; (3) Novel hardware support to roll back and deterministically re-execute buggy sections of code with very low overhead and transparently to the user; and (4) operating system support to roll back and re-execute code sections that cannot be supported by hardware. These four layers are tightly integrated in a software prototype.

Our work directly aims at improving what has historically been the dark spot of the IT revolution: poor programmer productivity. We can meet the software debugging challenge by focusing on debugging production runs, thanks to providing very low-overhead bug characterization support in hardware. The additional compiler, data miner, and operating system layers can enhance the power of the hardware once the bug is detected. We hope the work will have a broad impact, since expediting the debugging process can lead to dramatic increases in the productivity of IT professionals and students. In addition, the ideas developed can also be used for other anomaly detection, such as intrusion detection and security attacks, which is very important to our society.

Title: Shallow Integration over the Deep Web: A Holistic Approach

This project aims to build a MetaIntegrator for integrating databases on the Internet. To realize large-scale integration over this "deep Web," the research pursues the "shallow integration" philosophy, which does not rely on deep semantic annotations or deep probing of sources. In particular, it takes a holistic approach, which essentially leverages the challenge of large-scale itself as an opportunity, by resorting to hidden statistical regularities for enabling shallow integration. Specifically, this project focuses on three tasks: (1) Deep Web survey: To characterize the nature of the deep Web (as pertinent to semantic integration), this project extensively surveys databases on the Web. (2) Source selection: Since there are so many potential sources, "what sources should be involved in answering a given query?" This project thus develops the dynamic selection of sources for matching a query. (3) Schema integration: Since sources are heterogeneous, in querying the problem "how does an attribute in one source correspond to that in another?" Needs to be resolved. This project thus studies the matching and unification of schemas across myriad sources. Information on this project will be posted on the Web (http://eagle.cs.uiuc.edu/metaquerier) and the results are expected to have broad impact by advancing the understanding of dynamic, large-scale integration and develop a set of general techniques, and constructing a MetaIntegrator for providing access to (selected domains of) the deep Web. These fundamental results are likely to have technology transfer into a broad spectrum of Web applications.

DAIS - Database and Information Systems Laboratory, Department of Computer Science, University of Illinois at Urbana-Champaign, 201 N. Goodwin Ave., Urbana, IL 61801, USA.  Fax: 217-265-6494, Phone: 217-244-6241.