Digital identity is defined as the digital representation of the information known about a specific individual or organization. An emerging approach for protecting identities of individuals while at the same time enhancing user convenience is to focus on inter-organization management of identity...

In a history-based trust-management system, users and service providers use information about past transactions to make trust-based decisions concerningcurrent transactions. One category of such systems is represented by the reputation systems. However, despite the growing body of experience in...

In this paper we highlight the need for privacy of user data used in digital identity management systems. We investigate the issues from the individual, business, and government perspectives. We provide surveys related to the growing problem of identity theft and the sociological concerns of...

Nowadays privacy becomes a major concern and many research efforts have been dedicated to the development of privacy protecting technology. Anonymization techniques provide an e±cient approach to protect data privacy. We recently proposed a systematic clustering1 method based on k-...

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...

The first Workshop on Security and Privacy in GIS and LBS (SPRINGL 2008) was organized on November 4, 2008 at Irvine (CA) in conjunction with the SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM GIS 2008). The goal of the SPRINGL workshop series is to...