NSF Org:	IIS Division of Information & Intelligent Systems
Recipient:	UNIVERSITY OF CALIFORNIA, DAVIS
Initial Amendment Date:	June 24, 2003
Latest Amendment Date:	September 27, 2005
Award Number:	0242414
Award Instrument:	Continuing Grant
Program Manager:	Gia-Loi Le Gruenwald IIS  Division of Information & Intelligent Systems CSE  Directorate for Computer and Information Science and Engineering
Start Date:	July 1, 2003
End Date:	June 30, 2007 (Estimated)
Total Intended Award Amount:	$240,000.00
Total Awarded Amount to Date:	$240,000.00
Funds Obligated to Date:	FY 2003 = $80,000.00 FY 2004 = $80,000.00 FY 2005 = $80,000.00
History of Investigator:	Michael Gertz (Principal Investigator) gertz@cs.ucdavis.edu Karl Levitt (Former Co-Principal Investigator)
Recipient Sponsored Research Office:	University of California-Davis 1850 RESEARCH PARK DR STE 300 DAVIS CA  US  95618-6153 (530)754-7700
Sponsor Congressional District:	04
Primary Place of Performance:	University of California-Davis 1850 RESEARCH PARK DR STE 300 DAVIS CA  US  95618-6153
Primary Place of Performance Congressional District:	04
Unique Entity Identifier (UEI):	TX2DAGQPENZ5
Parent UEI:
NSF Program(s):	DATA AND APPLICATIONS SECURITY
Primary Program Source:	app-0103  app-0104  app-0105
Program Reference Code(s):	9218, HPCC
Program Element Code(s):	722800
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.070

ABSTRACT

Many of today's mission critical databases have not been designed with a particular focus on security aspects such as integrity, confidentiality, and availability. Even if security mechanisms have been used during the initial design, these mechanisms are often outdated due to new requirements and applications, and do not reflect current security polices, thus leaving ways for insider misuse and intrusion. The proposed research is concerned with analyzing various security aspects of mission critical (relational)databases that are embedded in complex information system infrastructures. We propose four complementary avenues of research: (1) models and techniques to profile the behavior of mission critical data stored in databases, (2) algorithms to correlate (anomalous) data behavior to application/user behavior, (3) techniques to determine and model user profiles and roles from behavioral descriptions, and (4) the integration of techniques, algorithms, and mechanisms into a security re-engineering workbench for (relational) databases. Two major themes build the core of the proposed approaches. First, the analysis of database vulnerabilities and violations of security paradigms is data-driven, i.e., first the behavior of the data is analyzed and modeled before it is correlated to users and applications. Second, we introduce the concept of access path model to uniformly model and correlate data flow and access behavior among relations, users, and applications. This model allows security personnel to fully inspect database security aspects in complex settings in a focused, aspect (policy) driven fashion.

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