Intelligent Information Systems

The Quest Team 2008 The Intelligent Information Systems Research (aka Quest) group designs information systems that enable the preservation of the privacy and ownership of data while not impeding the flow of information. Our work is motivated by the technical challenges posed by the ever-changing computing landscape, whose success is predicated on protecting the privacy, security, and integrity of interactions between individuals and enterprises as well as between enterprises. We do fundamental and visionary research that closely ties with applications, such as identifying and studying new frameworks, models, methodologies, and opportunities. The team has a solid track record of doing good work. Examples include innovating the initial concepts in data mining; creating data-level technology for enforcing privacy; creating technology to enabling traceability in the RFID network; producing middleware that enables localized mobile device disclosure-compliant information sharing and demonstrating how focused text analytics can change industries. We ground our work in the Healthcare Informatics space and ensure that our research is applicable across a myriad of other industries. We believe that research must have impact on the enterprise and on people. Thus, we strive to ensure that our work is not only applicable to real problems, but also theoretically sound.

Present Family: Varun Bhagwan, Karen Brannon, Sangeeta Doraiswamy, Alexandre Evfimievski, Tyrone Grandison

Immediate Extended Family: Alfredo Alba, Stefan Edlund, Ronald Fagin, Deon Glajchen, Niina Haiminen, Joshua Hui, Jerry Kiernan, Daniel Gruhl, Heikki Mannila, Jan Pieper, Christine Robson, David Woodruff

Past Family Members: Rakesh Agrawal, Dmitri Asonov, Roberto Bayardo, Rafae Bhatti, Alvin Cheung, Christan Grant, Bryan Hickerson, Christopher Johnson, Theodoros Lappas, Kristen Lefevre, Kun Liu, Karin Murthy, Ralf Rantzau, Stefan Schönauer, Ramakrishnan Srikant, Evimaria Terzi, Raja Velu, Niko Vuokko, Steve Watts, Yirong Xu

MONGOOSE

MONGOOSE technology is the bedrock that enables the construction of data analytics platforms and systems, while allaying the issues associated with ingesting data in an error where failure is the norm and not the exception. Read More

Privacy-Preserving Social Network Analysis

Privacy is currently burdensome for social network users. Keeping track of privacy configurations when settings explode and the number of networks increase is tiresome. Users have no ability to use best practices or transfer settings and most are unaware of the risky behavior they engage in. This project addresses these issues. Read More

• Tyrone Grandison, Rafae Bhatti. "Regulatory Compliance and the Correlation to Privacy Protection in Healthcare". International Journal of Computational Models and Algorithms in Medicine. Special Issue on Privacy and Security Issues for Medical Data. March 2010.
• Kun Liu, Evimaria Terzi. "A Framework for Computing the Privacy Scores of Users in Online Social Networks". To appear in the Proceedings of the IEEE International Conference on Data Mining (ICDM 2009). Miami, Florida. USA. December 6-9, 2009.
• Jerry Kiernan, Evimaria Terzi. "Constructing comprehensive summaries of large event sequences". To appear in ACM Transactions on Knowledge Discovery from Data. Editor: Jiawei Han.
• Varun Bhagwan, Tyrone Grandison, Alfredo Alba, Daniel Gruhl, Jan Pieper. "MONGOOSE: MONitoring Global Online Opinions via Semantic Extraction". To appear in 2009 Service Quality and Assurance Management (SQAM) workshop at IEEE 2009 International Conference on Cloud Computing (CLOUD-II 2009), September 21-25, 2009, Bangalore, India.
• Varun Bhagwan, Tyrone Grandison, Daniel Gruhl, "Sound Index: Music Charts By The People, For The People". Communications of the ACM. September 2009. Vol 52, No 9.

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White Papers

• Managing Disclosure of Private Healthcare Data with Hippocratic Databases.

• Managing Disclosure of Private Financial Data with Hippocratic Databases.

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• IBM Hippocratic Database Active Enforcement (Version 1.0) : User's Guide.

• IBM Hippocratic Database Compliance Auditing (Version 1.0) : User's Guide.

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MONGOOSE

Privacy-Preserving Social Network Analysis

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Data Mining

Discovery and Supervision

Epistemic Privacy

Health-e-Assistant

Hippocratic Database Technology

ÏNFÏNïTY

Intelligent Data Storage

PRIMA

RFID Traceability

Sound Index

Shipment Information Sharing Services (SISS)

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"IBM Develops Facebook Privacy Application". Owen Fletcher. March 12, 2009.

"How IBM's sprucing up its 'social' side". Charles Cooper. March 12, 2009.

"BBC Sound Index portends new popularity metrics for music". Tim Conneally. May 20, 2008.

"The BBC Sound Index". Darren Waters. May 20, 2008.

"BBC's Sound Index is good, but we won't get the data". Mike Buthcer. May 20, 2008.

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Hippocratic Management of Data

Privacy Preserving Analytics (Mining & OLAP)

RFID Traceability

Optimal Data De-identification

Data Pointillism

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Awards and Recognition

Research Accomplishment for Privacy Technology Impact on Science (2008)

Research Division Award for 1st Plateau Asset Award for Active Enforcement Privacy Technology (2007)

Research Division Award for 1st Plateau Asset Award for Compliance Auditing Technology (2007)

Research Division Award for Contributions to WebSphere Messaging (2007)

Research Division Award for Unraveling RFID Networks (2005)

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