18018686
Limiting the Disclosure of Access Control Policies during Automated Trust Negotiation
Automated trust negotiation is a new approach to establishing trust between strangers through the exchange of property-based digital credentials, and the use of mobile access control policies that specify what combinations of credentials a stranger must supply in order to gain access to each local service or credential. In this paper, we show that access control policies can also contain sensitive information that should be protected from inappropriate access by strangers during negotiation. We present and analyze two automated trust negotiation strategies that support protection for access control policies. The first is the relevant credentials set strategy, which does not directly disclose access control policies and has a fast running time, but may disclose more credentials than strictly necessary. The second strategy is the all relevant policies strategy, which freely discloses all relevant access control policies that the other negotiating party has earned access to during negotiation, and offers the possibility of disclosing fewer credentials
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.
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.
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.
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.
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.
61674575
Collaborative tracking of multiple targets
Coalescence, meaning the tracker associates more than one trajectories to some targets while loses track for others, is a challenging problem for visual tracking of multiple targets, especially when similar targets move close or present occlusions. Existing approaches that are based on joint data association are confronted by the combinatorial complexity due to the concatenation of the state spaces of individual targets. This paper presents a novel collaborative approach with linear complexity to the coalescence problem. The basic idea is the collaborative inference mechanism, in which the estimate of an individual target is not only determined by its own observation and dynamics, but also through the interaction and collaboration with the estimates of its adjacent targets, which leads to a competition mechanism that enables different targets to compete for the common image observations. The theoretical foundation of the new approach is based on Markov networks. Variational analysis of this Markov network reveals a mean field approximation to the posterior density of each target, therefore provides a computationally efficient way for such a difficult inference problem. In addition, a mean field Monte Carlo (MFMC) algorithm is designed to achieve Bayesian inference by simulating the competition among a set of low dimensional particle filters. Compared with the existing solutions, the proposed new collaborative approach stands out by its effectiveness and low computational cost to the coalescence problem, as pronounced in the extensive experiments.
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.
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.
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.
584843
Identifying Error-Prone Software&#8212;An Empirical Study
A major portion of the effort expended in developing commercial software today is associated with program testing. Schedule and/ or resource constraints frequently require that testing be conducted so as to uncover the greatest number of errors possible in the time allowed. In this paper we describe a study undertaken to assess the potential usefulness of various product-and process-related measures in identifying error-prone software. Our goal was to establish an empirical basis for the efficient utilization of limited testing resources using objective, measurable criteria. Through a detailed analysis of three software products and their error discovery histories, we have found simple metrics related to the amount of data and the structural complexity of programs to be of value for this purpose.