Supporting conditional delegation in secure workflow management systems
Proceedings of the tenth ACM symposium on Access control models and technologies
DM-AMS: employing data mining techniques for alert management
dg.o '05 Proceedings of the 2005 national conference on Digital government research
LS3: a Linear Semantic Scan Statistic technique for detecting anomalous windows
Proceedings of the 2005 ACM symposium on Applied computing
DBSec'05 Proceedings of the 19th annual IFIP WG 11.3 working conference on Data and Applications Security
Automatic enforcement of access control policies among dynamic coalitions
ICDCIT'04 Proceedings of the First international conference on Distributed Computing and Internet Technology
Collusion set detection through outlier discovery
ISI'05 Proceedings of the 2005 IEEE international conference on Intelligence and Security Informatics
| Hi-index | 0.00 |
US Customs embarked on a major modernization initiative of its Information Technology systems. Drawing in data from Customs trade systems, targeting inspectors review manifest information as well as strategic and tactical intelligence to determine which shipments and containers are "high-risk." This entails a considerable level of communication and data sharing between various government agencies. Our NSF funded project, funded through the digital government program, aims at providing decision makers with the ability to extract and fuse information from multiple, heterogeneous sources in response to a query while operating under a decentralized security administration. Based on the idea of "Smart Borders", the system will utilize data available from different agencies, ports and customs divisions to supplement the profiling by targeting towards anomalies, and detect various flags raised by non-conforming shipments or abnormal behavior of inbound cargos and raise a combination of alerts. This project proposes generalizable development work, which devises solutions to accomplish secure interoperation among different government agencies. The output of this project would ideally enhance the security aspect of the Automated Commercial Environment (ACE) system by incorporating the concept of semantic interoperability, anomaly detection and subsequent spatial and geographical visualization of information that can help Customs inspectors make better decisions. This project is a collaboration between the industry, government and the academia, providing the opportunity to directly influence the practical needs of the government agency, in this case the US Customs.