Ensuring secure and authorized access to remote services and information resources in a dynamic collaborative environment is a challenging task. Two major issues that need to be addressed in this regard are: specification of access control requirements and trust management. Specification of access control requirements for dynamic collaboration is challenging mainly because of the limited or lack of knowledge about remote users

Privacy and security considerations can prevent sharing of data, derailing data mining projects. Distributed knowledge discovery can alleviate this problem. We present a technique that uses EM mixture modeling to perform clustering on distributed data. This method controls data sharing, preventing disclosure of individual data items or any results that can be traced to an individual site.

Advances in the media and entertainment industries, including streaming audio and digital TV, present new challenges for managing and accessing large audio-visual collections. Current content management systems support retrieval using low-level features, such as motion, color, and texture. However, low-level features often have little meaning for naive users, who much prefer to identify content using high-level semantics or concepts. This creates a gap between systems and their users that must be bridged for these systems to be used effectively. To this end, in this paper, we first present a knowledge-based video indexing and content management framework for domain specific videos (using basketball video as an example). We will provide a solution to explore video knowledge by mining associations from video data. The explicit definitions and evaluation measures (e.g., temporal support and confidence) for video associations are proposed by integrating the distinct feature of video data. Our approach uses video processing techniques to find visual and audio cues (e.g., court field, camera motion activities, and applause), introduces multilevel sequential association mining to explore associations among the audio and visual cues, classifies the associations by assigning each of them with a class label, and uses their appearances in the video to construct video indices. Our experimental results demonstrate the performance of the proposed approach.

Trust management is a form of distributed access control that allows one principal to delegate some access decisions to other principals. While this makes trust management more flexible than the access matrix model, it makes safety and security analysis more important. We show that in contrast to the undecidability of classical HRU safety properties, our primary security properties are decidable. In particular, most safety properties we study are decidable in polynomial time.  The computational complexity of containment analysis, the most complicated security property we study, forms a complexity hierarchy based on the expressive power of the trust management language.

We propose a new cryptographic primitive called oblivious signature-  based envelope (OSBE). Informally, an OSBE scheme enables a sender to send an envelope (encrypted message) to a receiver, and has the following two properties: (1) The receiver can open the envelope if and only if it has a third party

uppose Alice and Bob are two entities (e.g. agents, organi-  zations, etc.) that wish to negotiate a contract. A contract consists of several clauses, and each party has certain constraints on the acceptabil-  ity and desirability (i.e., a private

This paper presents computationally

n this paper, we investigate the use of multiple directional antennas on sensor motes for location determination and mobile node monitoring. One key aspect that distinguishes wireless sensor networks is inexpensive transmitters and receivers that still maintain acceptable connectivity. Therefore, complex RF solutions are often not applicable. We propose and demonstrate a location estimation algorithm on a single sensor node equipped with inexpensive directional antennas by measuring the received signal strength of the transmission peers. This algorithm is further applied to the dynamic tracking of a wandering mote. The location tracking error can be reduced from 30% to 16% by using moving average schemes and merging estimates from different sets of antennas. The mean error of tracking estimates can be obtained to provide the certainty of location tracking. Therefore, only a single mote with angular diverse multiple antennas is needed to determine the location of a mote without triangulation.

s organizations increase their reliance on, possibly distributed, information systems for daily business, they become more vulnerable to security breaches even as they gain productivity and efficiency advantages. Though a number of techniques, such as encryption and electronic signatures, are currently available to protect data when transmitted across sites, a truly comprehensive approach for data protection must also include mechanisms for enforcing access control policies based on data contents, subject qualifications and characteristics, and other relevant contextual information, such as time. It is well understood today that the semantics of data must be taken into account in order to specify effective access control policies. Also, techniques for data integrity and availability specifically tailored to database systems must be adopted. In this respect, over the years the database security community has developed a number of different techniques and approaches to assure data confidentiality, integrity, and availability.  However, despite such advances, the database security area faces several new challenges. Factors such as the evolution of security concerns, the

The emerging Web service technology has enabled the development of Internet-based applications that integrate distributed and heterogeneous systems and processes which are owned by different organizations.  However, while Web services are rapidly becoming a fundamental paradigm for the development of complex Web applications, several security issues still need to be addressed. Among the various open issues concerning security, an important issue is represented by the development of suitable access control models, able to restrict access to Web services to authorized users. In this paper we present an innovative access control model for Web services. The model is characterized by a number of key features, including identity attributes and service negotiation capabilities. We formally define the protocol for carrying on negotiations, by specifying the types of message to be exchanged and their contents, based on which requestor and provider can reach an agreement about security requirements and services. We also discuss the architecture of the prototype we are currently implementing. As part of the architecture we propose a mechanism for mapping our policies onto the WS-Policy standard which provides a standardized grammar for expressing Web services policies

The Generalized Temporal Role-Based Access Control (GTRBAC) model provides a comprehensive set of temporal constraint expressions which can facilitate the specification of fine-grained time-based access control policies. However, the issue of the expressiveness and usability of this model has not been previously investigated. In this paper, we present an analysis of the expressiveness of the constructs provided by this model and illustrate that its constraints-set is not minimal. We show that there is a subset of GTRBAC constraints that is sufficient to express all the access constraints that can be expressed using the full set. We also illustrate that a nonminimal GTRBAC constraint set can provide better flexibility and lower complexity of constraint representation.  Based on our analysis, a set of design guidelines for the development of GTRBAC-based security administration is presented.

Recently, a new class of data mining methods, known as privacy preserving data mining (PPDM)  algorithms, has been developed by the research community working on security and knowledge discovery. The aim of these algorithms is the extraction of relevant knowledge from large amount of data, while protecting at the same time sensitive information. Several data mining techniques, incorporating privacy protection mechanisms, have been developed that allow one to hide sensitive itemsets or patterns, before the data mining process is executed.  Privacy preserving classification methods, instead, prevent a miner from building a classifier which is able to predict sensitive data. Additionally, privacy preserving clustering techniques have been recently proposed, which distort sensitive numerical attributes, while preserving general features for clustering analysis. A crucial issue is to determine which ones among these privacy-preserving techniques better protect sensitive information. However,  this is not the only criteria with respect to which these algorithms can be evaluated. It is also important to assess the quality of the data resulting from the modifications applied by each algorithm, as well as the performance of the algorithms. There is thus the need of identifying a comprehensive set of criteria with respect to which to assess the existing PPDM algorithms and determine which algorithm meets specific requirements.  In this paper, we present a first evaluation framework for estimating and comparing different kinds of PPDM algorithms. Then, we apply our criteria to a specific set of algorithms and discuss the evaluation results we obtain.  Finally, some considerations about future work and promising directions in the context of privacy preservation in data mining are discussed.

In this paper we discuss issues concerning the development of inter-  active virtual reality (VR) environments. We argue that the integration of such type of environments with database technology has the potential of providing on one side much flexibility and on the other hand of resulting in enhanced in-  terfaces for accessing contents from digital archives.  The paper also describes a project dealing with the dissemination of cultural heritage contents. Within the project an integrated framework has been developed that enhances conventional VR environments with database interactions.

Abstract. Trust negotiation between two subjects require each one proving its properties to the other. Each subject specifies disclosure policies stating the types of credentials and attributes the counterpart has to provide to obtain a given re-  source. The counterpart, in response, provides a disclosure set containing the nec-  essary credentials and attributes. If the counterpart wants to remain anonymous,  its disclosure sets should not contain identity revealing information. In this pa-  per, we propose anonymization techniques using which a subject can transform its disclosure set into an anonymous one. Anonymization transforms a disclosure set into an alternative anonymous one whose information content is different from the original one. This alternative disclosure set may no longer satisfy the original disclosure policy causing the trust negotiation to fail. To address this problem, we propose that trust negotiation requirements be expressed at a more abstract level using property-based policies. Property-based policies state the high-level prop-  erties that a counterpart has to provide to obtain a resource. A property-based policy can be implemented by a number of disclosure policies. Although these disclosure policies implement the same high-level property-based policy, they re-  quire different sets of credentials. Allowing the subject to satisfy any policy from the set of disclosure policies, increases not only the chances of a trust negotiation succeeding but also the probability of ensuring anonymity.