686538
Protecting Privacy during On-Line Trust Negotiation
The dramatic growth of services and information on the Internet is accompanied by growing concerns over privacy. Trust negotiation is a new approach to establishing trust between strangers on the Internet through the bilateral exchange of digital credentials, the on-line analogue to the paper credentials people carry in their wallets today. When a credential contains sensitive information, its disclosure is governed by an access control policy that specifies credentials that must be received before the sensitive credential is disclosed. This paper identifies the privacy vulnerabilities present in on-line trust negotiation and the approaches that can be taken to eliminate or minimize those vulnerabilities. The paper proposes modifications to negotiation strategies to help prevent the inadvertent disclosure of credential information during online trust negotiation for those credentials or credential attributes that have been designated as sensitive, private information.
16823379
A compressed accessibility map for XML
XML is the undisputed standard for data representation and exchange. As companies transact business over the Internet, letting authorized customers directly access, and even modify, XML data offers many advantages in terms of cost, accuracy, and timeliness. Given the complex business relationships between companies, and the sensitive nature of information, access must be provided selectively, using sophisticated access control specifications. Using the specification directly to determine if a user has access to an XML data item can be extremely inefficient. The alternative of fully materializing, for each data item, the users authorized to access it can be space-inefficient. In this article, we introduce a compressed accessibility map (CAM) as a space- and time-efficient solution to the access control problem for XML data. A CAM compactly identifies the XML data items to which a user has access, by exploiting structural locality of accessibility in tree-structured data. We present a CAM lookup algorithm for determining if a user has access to a data item that takes time proportional to the product of the depth of the item in the XML data and logarithm of the CAM size. We develop an algorithm for building an optimal size CAM that takes time linear in the size of the XML data set. While optimality cannot be preserved incrementally under data item updates, we provide an algorithm for incrementally maintaining near-optimality. Finally, we experimentally demonstrate the effectiveness of the CAM for multiple users on a variety of real and synthetic data sets.
625233
Routing XML queries
In file-sharing P2P networks, a fundamental problem is that of identifying databases that are relevant to user queries. This problem is referred to as the location problem in P2P literature. We propose a scalable solution to the location problem in a data-sharing P2P network, consisting of a network of XML database nodes and XML router nodes, and make the following contributions. We develop the internal organization and routing protocols for the XML router nodes, to enable scalable XPath query and update processing, under the open and the agreement cooperation models between nodes. Since router nodes tend to be memory constrained, we facilitate a space/performance tradeoff by permitting aggregated routing states, and developing algorithms for generating and using such aggregated information. We experimentally demonstrate the scalability of our approach, and the performance of our query and update protocols, using a detailed simulation model, varying key design parameters.
1690622
Aggregate Query Answering on Anonymized Tables
Privacy is a serious concern when microdata need to be released for ad hoc analyses. The privacy goals of existing privacy protection approaches (e.g., k-anonymity and l-diversity) are suitable only for categorical sensitive attributes. Since applying them directly to numerical sensitive attributes (e.g., salary) may result in undesirable information leakage, we propose privacy goals to better capture the need of privacy protection for numerical sensitive attributes. Complementing the desire for privacy is the need to support ad hoc aggregate analyses over microdata. Existing generalization-based anonymization approaches cannot answer aggregate queries with reasonable accuracy. We present a general framework of permutation-based anonymization to support accurate answering of aggregate queries and show that, for the same grouping, permutation-based techniques can always answer aggregate queries more accurately than generalization-based approaches. We further propose several criteria to optimize permutations for accurate answering of aggregate queries, and develop efficient algorithms for each criterion.
2722770
Preventing attribute information leakage in automated trust negotiation
Automated trust negotiation is an approach which establishes trust between strangers through the bilateral, iterative disclosure of digital credentials. Sensitive credentials are protected by access control policies which may also be communicated to the other party. Ideally, sensitive information should not be known by others unless its access control policy has been satisfied. However, due to bilateral information exchange, information may flow to others in a variety of forms, many of which cannot be protected by access control policies alone. In particular, sensitive information may be inferred by observing negotiation participants' behavior even when access control policies are strictly enforced.In this paper, we propose a general framework for the safety of trust negotiation systems. Compared to the existing safety model, our framework focuses on the actual information gain during trust negotiation instead of the exchanged messages. Thus, it directly reflects the essence of safety in sensitive information protection. Based on the proposed framework, we develop policy databases as a mechanism to help prevent unauthorized information inferences during trust negotiation. We show that policy databases achieve the same protection of sensitive information as existing solutions without imposing additional complications to the interaction between negotiation participants or restricting users' autonomy in defining their own policies.
18437356
Index-based approximate XML joins
XML data integration tools are facing a variety of challenges for their efficient and effective operation. Among these is the requirement to handle a variety of inconsistencies or mistakes present in the data sets. We study the problem of integrating XML data sources through index assisted join operations, using notions of approximate match in the structure and content of XML documents as the join predicate. We show how a well known and widely deployed index structure, namely the R-tree, can be adopted to improve the performance of such operations. We propose novel search and join algorithms for R-trees adopted to index XML document collections. We also propose novel optimization objectives for R-tree construction, making R-trees better suited for this application.
14377828
Switching observation models for contour tracking in clutter
We propose a generative model approach to contour tracking against nonstationary clutter and to coping with occlusions by explicit modelling and inferring. The proposed dynamic Bayesian networks consist of multiple hidden processes, which model the target, the clutter and the occlusions. The image observation models, which depict the generation of the image features, are conditioned on all the hidden processes. Based on this framework, the tracker can automatically switch among different observation models according to the hidden states of the clutter and occlusions. In addition, the inference of these hidden states provides self-evaluations for the tracker. The tracking and inference are implemented based on sequence Monte Carlo techniques. The effectiveness of the proposed approach to robust tracking and inferring nonstationary clutter and occlusion is demonstrated for a variety of image sequences.
14568428
A reputation and trust management broker framework for Web applications
This paper presents a distributed reputation and trust management framework that addresses the challenges of eliciting, evaluating and propagating reputation for Web applications. We propose a broker framework where every service user is associated with a broker who may represent multiple users. A broker collects for its users the distributed reputation ratings about any Web service. In return, a user provides its broker the transaction rating after every transaction with any service in order to build up the reputation database on all services. In addition, brokers form a trust network where they exchange and collect reputation data about services. By delegating trust management to brokers, individual users only need to ask their brokers about the reputation of a service before any transaction with a server. The only overhead for a user is the responsibility to share the reputation feedback with its broker. We present the distributed reputation and trust management framework and show the performance of the system by simulations.
1794794
Service Selection Algorithms for Composing Complex Services with Multiple QoS Constraints
One of the promises of the service-oriented architecture (SOA) is that complex services can be composed using individual services. Individual services can be selected and integrated either statically or dynamically based on the service functionalities and performance constraints. For many distributed applications, the runtime performance (e.g. end-to-end delay, cost, reliability and availability) of complex services are very important. In our earlier work, we have studied the service selection problem for complex services with only one QoS constraint. This paper extends the service selection problem to multiple QoS constraints. The problem can be modelled in two ways: the combinatorial model and the graph model. The combinatorial model defines the problem as the multi-dimension multi-choice 0-1 knapsack problem (MMKP). The graph model defines the problem as the multi-constraint optimal path (MCOP) problem. We propose algorithms for both models and study their performances by test cases. We also compare the pros & cons between the two models.
31957917
Modeling and Measuring Privacy Risks in QoS Web Services
The privacy issue for QoS Web services is considered. As more Web services are constructed and deployed, many of our personal needs may be served by more than one service providers regardless of their platforms and implementation technologies. Service selection is performed by comparing the QoS attributes of all candidate services. Releasing private data without due control may raise the risk of allowing potential adversaries to collect, reveal or utilize one's data in undesirable ways. We propose a QoS model that quantifies a user's privacy risk in order to make the service selection process manageable. The privacy risk is derived using the percentage of the private data set to be released, and user-defined context-oriented weights that quantify the potential damage of privacy leaking in a specific context. We have included privacy risk cost as one of the QoS parameters by extending the end-to-end QoS composition algorithms developed previously
415460
Model Driven Development of Business Process Monitoring and Control Systems
This paper describes a model-driven approach in monitoring and controlling the behaviour of business processes. The business-level monitoring and control requirements are first described by a series of policies that can be combined together to construct a Directed Acyclic Graph (DAG), which can be regarded as the Platform Independent Model (PIM) for the high level business solution. PIM provides a convenient and clear way for business users to understand, monitor and control the interactions in the target business process. Then the PIM is transformed to an executable representation (Platform Specific Model, PSM), such as BPEL (Business Process Execution Language for Web Service) by decomposing the DAG into several sub-processes and modelling each sub-process as a BPEL process that will be deployed to runtime.