Automated trust negotiation using cryptographic credentials
In automated trust negotiation (ATN), two parties exchange digitally signed credentials that contain attribute information to establish trust and make access control decisions. Because the information in question is often sensitive, credentials are protected according to access control policies. In traditional ATN, credentials are transmitted either in their entirety or not at all. This approach can at times fail unnecessarily, either because a cyclic dependency makes neither negotiator willing to reveal her credential before her opponent, because the opponent must be authorized for all attributes packaged together in a credential to receive any of them, or because it is necessary to fully disclose exact attribute values, rather than merely proving they satisfy some predicate (such as being over 21 years of age). Recently, several cryptographic credential schemes and associated protocols have been developed to address these and other problems. However, they can be used only as fragments of an ATN process. This paper introduces a framework for ATN in which the diverse credential schemes and protocols can be combined, integrated, and used as needed. A policy language is introduced that enables negotiators to specify authorization requirements that must be met by an opponent to receive various amounts of information about certified attributes and the credentials that contain it. The language also supports the use of uncertified attributes, allowing them to be required as part of policy satisfaction, and to place their (automatic) disclosure under policy control.

title: Enhanced smart-card based license management
abstract: In many e-commerce (electronic commerce) situations, the owner of a digital object wants to enforce policies on the object after the object is in the customer's hands. The object can be thought of as being software, because data is often protected by forcing access to it to take place through a particular authorized software (e.g., a "reader" for an encrypted media file, in which case a license to view the movie is, in some sense, a "software license"). One of the ways that were proposed for such policy enforcement is the use of smart cards. We describe an enhanced solution to software license management based on tamper-resistant smart cards. Our public-key protocols for binding software licenses to smart cards improve on previous schemes in that they support flexible and partial transfers of licenses between cards. The license is verified by checking the presence of the associated card. The user can therefore have several software licenses all of which are bound to one card, to avoid juggling several cards in and out of the card reader.

title: Private collaborative forecasting and benchmarking
abstract: Suppose a number of hospitals in a geographic area want to learn how their own heart-surgery unit is doing compared with the others in terms of mortality rates, subsequent complications, or any other quality metric. Similarly, a number of small businesses might want to use their recent point-of-sales data to cooperatively forecast future demand and thus make more informed decisions about inventory, capacity, employment, etc. These are simple examples of cooperative benchmarking and (respectively) forecasting that would benefit all participants as well as the public at large, as they would make it possible for participants to avail themselves of more precise and reliable data collected from many sources, to assess their own local performance in comparison to global trends, and to avoid many of the inefficiencies that currently arise because of having less information available for their decision-making. And yet, in spite of all these advantages, cooperative benchmarking and forecasting typically do not take place, because of the participants' unwillingness to share their information with others. Their reluctance to share is quite rational, and is due to fears of embarrassment, lawsuits, weakening their negotiating position (e.g., in case of over-capacity), revealing corporate performance and strategies, etc. The development and deployment of <i>private</i> benchmarking and forecasting technologies would allow such collaborations to take place without revealing any participant's data to the others, reaping the benefits of collaboration while avoiding the drawbacks. Moreover, this kind of technology would empower smaller organizations who could then cooperatively base their decisions on a much broader information base, in a way that is today restricted to only the largest corporations. This paper is a step towards this goal, as it gives protocols for forecasting and benchmarking that reveal to the participants the desired answers yet do not reveal to any participant any other participant's private data. We consider several forecasting methods, including linear regression and time series techniques such as moving average and exponential smoothing. One of the novel parts of this work, that further distinguishes it from previous work in secure multi-party computation, is that it involves floating point arithmetic, in particular it provides protocols to securely and efficiently perform division.

title: Secure Outsourcing of Sequence Comparisons
abstract: Large-scale problems in the physical and life sciences are being revolutionized by Internet computing technologies, like grid computing, that make possible the massive cooperative sharing of computational power, bandwidth, storage, and data. A weak computational device, once connected to such a grid, is no longer limited by its slow speed, small amounts of local storage, and limited bandwidth: It can avail itself of the abundance of these resources that is available elsewhere on the network. An impediment to the use of “computational outsourcing” is that the data in question is often sensitive, e.g., of national security importance, or proprietary and containing commercial secrets, or to be kept private for legal requirements such as the HIPAA legislation, Gramm-Leach-Bliley, or similar laws. This motivates the design of techniques for computational outsourcing in a privacy-preserving manner, i.e., without revealing to the remote agents whose computational power is being used, either one's data or the outcome of the computation on the data. This paper investigates such secure outsourcing for widely applicable sequence comparison problems, and gives an efficient protocol for a customer to securely outsource sequence comparisons to two remote agents, such that the agents learn nothing about the customer's two private sequences or the result of the comparison. The local computations done by the customer are linear in the size of the sequences, and the computational cost and amount of communication done by the external agents are close to the time complexity of the best known algorithm for solving the problem on a single machine (i.e., quadratic, which is a huge computational burden for the kinds of massive data on which such comparisons are made). The sequence comparison problem considered arises in a large number of applications, including speech recognition, machine vision, and molecular sequence comparisons. In addition, essentially the same protocol can solve a larger class of problems whose standard dynamic programming solutions are similar in structure to the recurrence that subtends the sequence comparison algorithm.

title: Hidden access control policies with hidden credentials
abstract: In an open environment such as the Internet, the decision to collaborate with a stranger (e.g., by granting access to a resource) is often based on the characteristics (rather than the identity) of the requester, via digital credentials: Access is granted if Alice's credentials satisfy Bob's access policy. The literature contains many scenarios in which it is desirable to carry out such trust negotiations in a privacy-preserving manner, i.e., so as minimize the disclosure of credentials and/or of access policies. Elegant solutions were proposed for achieving various degrees of privacy-preservation through minimal disclosure. In this paper, we present an efficient protocol that protects both sensitive credentials and policies. That is, Alice gets the resource only if she satisfies Bob's policy, Bob does not learn anything about Alice's credentials (not even whether Alice got access or not), and Alice learns neither Bob's policy structure nor which credentials caused her to gain access.

title: Secure outsourcing of sequence comparisons
abstract: Internet computing technologies, like grid computing, enable a weak computational device connected to such a grid to be less limited by its inadequate local computational, storage, and bandwidth resources. However, such a weak computational device (PDA, smartcard, sensor, etc.) often cannot avail itself of the abundant resources available on the network because its data are sensitive. This motivates the design of techniques for computational outsourcing in a privacy-preserving manner, i.e., without revealing to the remote agents whose computational power is being used either one’s data or the outcome of the computation. This paper investigates such secure outsourcing for widely applicable sequence comparison problems and gives an efficient protocol for a customer to securely outsource sequence comparisons to two remote agents. The local computations done by the customer are linear in the size of the sequences, and the computational cost and amount of communication done by the external agents are close to the time complexity of the best known algorithm for solving the problem on a single machine.

title: DLB: a novel real-time QoS control mechanism for multimedia transmission
abstract: This paper presents a new QoS guarantee scheme called R-(m,k)-firm (Relaxed-(m,k)-firm) which provides the guarantee on transmission delay of at least m out of any k consecutive packets (m/spl les/k). It has several advantages: (1) during network congestion, packets are dropped according to the (m,k) model rather than uncontrollably as the case of TD and RED, avoiding thus undesirable long consecutive packet drops; (2) it allows to admit more real-time flows than the traditional over-provisioning approach. A new mechanism, called DLB (double leaks bucket) is also proposed for dropping a proportion of packets of a flow or of aggregated-flows in case of network congestion while still guaranteeing the R-(m,k)-firm constraint. The sufficient condition for this guarantee is given for configuring the DLB parameters. It is easy to implement DLB in the actual IntServ and Diffserv architectures (by simply replacing the actual leaky, bucket by DLB) for providing respectively per flow and per class (m,k) guarantee, or event per flow R-(m,k)-firm guarantee in Diffserv.

title: Distributed hosting of Web content with erasure coding and unequal weight assignment
abstract: By sharing and hosting personal Web content in a peer-to-peer (P2P) fashion, we may increase the bandwidth of retrieval and improve the reliability of retrieval. The cost is that the Web content has to be replicated to and stored in the peers, consuming valuable network bandwidth and peer storage space. In this work, we develop two technologies, namely hierarchical content organization with unequal weight assignment and erasure coding, to reduce the amount of content to be distributed, yet still maintain the retrieval speed up and reliability. Significant improvement over the ordinary Web server is demonstrated.

title: Two-way Poisson mixture models for simultaneous document classification and word clustering
abstract: An approach to simultaneous document classification and word clustering is developed using a two-way mixture model of Poisson distributions. Each document is represented by a vector with each dimension specifying the number of occurrences of a particular word in the document in question. As a collection of documents across several classes usually makes use of a large number of words, the document vectors are of high dimension. On the other hand, the number of distinct words in any single document is usually substantially smaller than the size of the vocabulary, leading to sparse document vectors. A mixture of Poisson distributions is used to model the multivariate distribution of the word counts in the documents within each class. To address the issues of high dimensionality and sparsity, the parameters in the mixture model are regularized by imposing a clustering structure on the set of words. An EM-style algorithm for the two-way mixture model will be derived for parameter estimation with the clustering of words part of the estimation process. The connection of the two-way mixture model with dimension reduction will also be elucidated. Experiments on the newsgroup data have demonstrated promising results.

title: Automatic patent classification using citation network information: an experimental study in nanotechnology
abstract: Classifying and organizing documents in repositories is an active research topic in digital library studies. Manually classifying the large volume of patents and patent applications managed by patent offices is a labor-intensive task. Many previous studies have employed patent contents for patent classification with the aim of automating this process. In this research we propose to use patent citation information, especially the citation network structure information, to address the patent classification problem. We adopt a kernel-based approach and design kernel functions to capture content information and various citation-related information in patents. These kernels. performances are evaluated on a testbed of patents related to nanotechnology. Evaluation results show that our proposed labeled citation graph kernel, which utilized citation network structures, significantly outperforms the kernels that use no citation information or only direct citation information.

title: A grid oriented approach to reusing legacy code in ICENI framework
abstract: Legacy systems are valuable assets for organisations. They continuously evolve with new emerged technologies in rapidly changing business environment. ICENI provided an excellent grid middleware framework for developing grid-based systems. It creates an opportunity for legacy systems to evolve in grid environment. In this paper, we propose a component-based reengineering approach which applies software clustering techniques and program slicing techniques to recover components from legacy systems. It supports component encapsulation with JNI and component integration with CXML. The resulting components with core legacy code function in grid environment.