Collaborative and distributed applications, such as dynamic coalitions and virtualized grid computing, often require integrating access control policies of collaborating parties. Such an integration must be able to support complex authorization specifications and the fine-grained integration...

Collaborative and distributed applications, such as dynamic coalitions and virtualized grid computing, often require integrating access control policies of collaborating parties. Such an integration must be able to support complex authorization specifications and the fine-grained integration...

With the advances in web service techniques, new collaborative applications have emerged like supply chain arrangements and coalition in government agencies. In such applications, the collaborating parties are responsible for managing and protecting resources entrusted to them. Access control...

As distributed collaborative applications and architectures are adopting policy-based solutions for tasks such as access control, network security and data privacy, the management and consolidation of a large number of policies is becoming a crucial component of such solutions. In large-scale...

The expanding use of location-based services has profound implications on the privacy of personal information. If no adequate protection is adopted, information about movements of specific individuals could be disclosed to unauthorized subjects or organizations, thus resulting in privacy...

Assessing the trustworthiness of location data corresponding to individuals is essential in several applications, such as forensic science and epidemic control. To obtain accurate and trustworthy location data, analysts must often gather and correlate information from several independent...

As sensor networks are being increasingly deployed in decision-making infrastructures such as battlefield monitoring systems and SCADA (Supervisory Control and Data Acquisition) systems, making decision makers aware of the trustworthiness of the collected data is a crucial. To address this...

In recent years, anonymization methods have emerged as an important tool to preserve individual privacy when releasing privacy sensitive data sets. This interest in anonymization techniques has resulted in a plethora of methods for anonymizing data under different privacy and utility...

Geospatial data play a key role in a wide spectrum of critical data management applications, such as disaster and emergency management, environmental monitoring, land and city planning, and military operations, often requiring the coordination among diverse organizations, their data...

This paper proposes a novel approach for privacy-preserving distributed model-based classifier training. Our approach is an important step towards supporting customizable privacy modeling and protection. It consists of three major steps. First, each data site independently learns a weak concept...