Secure Outsourcing of Sequence Comparisons
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: OACerts: Oblivious Attribute Certificates
abstract: We propose oblivious attribute certificates (OACerts), an attribute certificate scheme in which a certificate holder can select which attributes to use and how to use them. In particular, a user can use attribute values stored in an OACert obliviously, i.e., the user obtains a service if and only if the attribute values satisfy the policy of the service provider, yet the service provider learns nothing about these attribute values. This way, the service provider's access control policy is enforced in an oblivious fashion. To enable the oblivious access control using OACerts, we propose a new cryptographic primitive called oblivious commitment-based envelope (OCBE). In an OCBE scheme, Bob has an attribute value committed to Alice and Alice runs a protocol with Bob to send an envelope (encrypted message) to Bob such that: 1) Bob can open the envelope if and only if his committed attribute value satisfies a predicate chosen by Alice and 2) Alice learns nothing about Bob's attribute value. We develop provably secure and efficient OCBE protocols for the Pedersen commitment scheme and comparison predicates as well as logical combinations of them

title: Trust Negotiation with Hidden Credentials, Hidden Policies, and Policy Cycles
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 examples where protecting the credentials and the access control policies is useful, and there are numerous protocols that achieve this. In many of these schemes, the server does not learn whether the client obtained access (e.g., to a message, or a service via an eticket). A consequence of this property is that the client can use all of her credentials without fear of “probing” attacks by the server, because the server cannot glean information about which credentials the client has (when this property is lacking, the literature uses a framework where the very use of a credential is subject to a policy specific to that credential). The main result of this paper is a protocol for negotiating trust between Alice and Bob without revealing either credentials or policies, when each credential has its own access policy associated with it (e.g., “a top-secret clearance credential can only be used when the other party is a government employee and has a top-secret clearance”). Our protocol carries out this privacy-preserving trust negotiation between Alice and Bob, while enforcing each credential’s policy (thereby protecting sensitive credentials). Note that there can be a deep nesting of dependencies between credential policies, and that there can be (possibly overlapping) policy cycles of these dependencies. Our result is not achieved through the routine use of standard techniques to implement, in this framework, one of the known strategies for trust negotiations (such as the “eager strategy”). Rather, this paper uses novel techniques to implement a non-standard trust negotiation strategy specifically suited to this framework (and in fact unusable outside of this framework, as will become clear). Our work is therefore Portions of this work were supported by Grants IIS-0325345, IIS0219560, IIS-0312357, and IIS-0242421 from the National Science Foundation, Contract N00014-02-1-0364 from the Office of Naval Research, by sponsors of the Center for Education and Research in Information Assurance and Security, and by Purdue Discovery Park’s e-enterprise Center. a substantial extension of the state-of-the-art in privacypreserving trust negotiations.

title: Universal Accumulators with Efficient Nonmembership Proofs
abstract: Based on the notion of accumulators, we propose a new cryptographic scheme called universal accumulators. This scheme enables one to commit to a set of values using a short accumulator and to efficiently compute a membership witness of any value that has been accumulated. Unlike traditional accumulators, this scheme also enables one to efficiently compute a nonmembership witness of any value that has not been accumulated. We give a construction for universal accumulators and prove its security based on the strong RSA assumption. We further present a construction for dynamic universal accumulators; this construction allows one to dynamically add and delete inputs with constant computational cost. Our construction directly builds upon Camenisch and Lysyanskaya's dynamic accumulator scheme. Universal accumulators can be seen as an extension to dynamic accumulators with support of nonmembership witness. We also give an efficient zero-knowledge proof protocol for proving that a committed value is not in the accumulator. Our dynamic universal accumulator construction enables efficient membership revocation in an anonymous fashion.

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: A Construction for General and Efficient Oblivious Commitment Based Envelope Protocols
abstract: The notion of Oblivious Commitment Based Envelope (OCBE) was recently proposed; it enables attribute-based access control without revealing any information about the attributes. Previous OCBE protocols are designed by taking zero-knowledge proof protocols that prove a committed value satisfies some property and changing the protocols so that instead of one party proving to the other party, the two parties compute two keys that agree if and only if the committed value indeed satisfy the property. In this paper, we introduce a more general approach for designing OCBE protocols that uses zero-knowledge proof protocols in a black-box fashion. We present a construction such that given a zero-knowledge proof protocol that proves a committed value satisfies a predicate, we have an OCBE protocol for that predicate with constant additional cost. Compared with previous OCBE protocols, our construction is more general, more efficient, and has wide applicability.

title: A mutual semantic endorsement approach to image retrieval and context provision
abstract: Learning semantics from annotated images to enhance content-based retrieval is an important research direction. In this paper,annotation data are assumed available for only a subset of images inside the database. An on the fly learning method is developed to capture the semantics of query images. Specifically, the semantics of annotated images in a visual proximity of a query are compared with each other to determine the amount of mutual endorsement. An image is considered endorsed by another if they possess similar semantics. Annotations with high mutual endorsement are used to narrow down a candidate pool of images. The new retrieval method is inherently dynamic and treats seamlessly different forms of annotation data. Experiments show that semantic endorsement can increase precision by as much as 70%in average for a wide range of parameter settings. We also develop a context provision mechanism to reveal the relationship between a query and semantic clusters extracted from the database. Context helps users explore the content of a database and provides a platform for them to tailor searches by stressing different perspectives in the interpretation of a query.

title: mSSL: extending SSL to support data sharing among collaborative clients
abstract: Client-server applications often do not scale well when a large number of clients access a single server. To solve this, a new trend is to allow a client to download data from other peer clients, in addition to from the server directly. This paradigm, which we call the hybrid peer-to-peer paradigm, is friendly to the server's scalability, but also faces new security challenges. For example, how can the server authenticate its clients and support data confidentiality? How can a client trust the data downloaded from other clients? What if a client refuses to acknowledge the service it received or overstates the service it offered? In this paper, we present a protocol, called mSSL, that provides a set of security functions to enable secure sharing of the data of a server among its clients. In addition to access control and confidentiality support, mSSL provides an original design on supporting data integrity and proof of service in this new context. Our evaluation further shows that mSSL has a reasonable overhead

title: Secure Untrusted Data Repository (SUNDR)
abstract: SUNDR is a network file system designed to store data securely on untrusted servers. SUNDR lets clients detect any attempts at unauthorized file modification by malicious server operators or users. SUNDR's protocol achieves a property called fork consistency, which guarantees that clients can detect any integrity or consistency failures as long as they see each other's file modifications. An implementation is described that performs comparably with NFS (sometimes better and sometimes worse), while offering significantly stronger security.

title: Two sufficient conditions for a graphic sequence to have a realization with prescribed clique size
abstract: A graphic sequence @p=(d"1,d"2,...,d"n) is said to be potentially K"r"+"1-graphic, if @p has a realization G containing K"r"+"1, a clique of r+1 vertices, as a subgraph. In this paper, we give two simple sufficient conditions for a graphic sequence @p=(d"1,d"2,...,d"n) to be potentially K"r"+"1-graphic. We also show that the two sufficient conditions imply a theorem due to Rao [An Erdos-Gallai type result on the clique number of a realization of a degree sequence unpublished.], a theorem due to Li et al [The Erdos-Jacobson-Lehel conjecture on potentially P"k-graphic sequences is true, Sci. China Ser. A 41 (1998) 510-520.], the Erdos-Jacobson-Lehel conjecture on @s(K"r"+"1,n) which was confirmed (see [Potentially G-graphical degree sequences, in: Y. Alavi et al.  An extremal problem on the potentially P"k-graphic sequence,  (2000) 223-231; The Erdos-Jacobson-Lehel conjecture on potentially P"k-graphic sequences is true, Sci. China Ser. A 41 (1998) 510-520.]) and the Yin-Li-Mao conjecture on @s(K"r"+"1-e,n) [An extremal problem on the potentially K"r"+"1-e-graphic sequences,  (2005) 151-159.], where K"r"+"1-e is a graph obtained by deleting one edge from K"r"+"1.

title: Learning-based linguistic indexing of pictures with 2--d MHMMs
abstract: Automatic linguistic indexing of pictures is an important but highly challenging problem for researchers in computer vision and content-based image retrieval. In this paper, we introduce a statistical modeling approach to this problem. Categorized images are used to train a dictionary of hundreds of concepts automatically based on statistical modeling. Images of any given concept category are regarded as instances of a stochastic process that characterizes the category. To measure the extent of association between an image and the textual description of a category of images, the likelihood of the occurrence of the image based on the stochastic process derived from the category is computed. A high likelihood indicates a strong association. In our experimental implementation, the ALIP (Automatic Linguistic Indexing of Pictures) system, we focus on a particular group of stochastic processes for describing images, that is, the two-dimensional multiresolution hidden Markov models (2-D MHMMs). We implemented and tested the system on a photographic image database of 600 different semantic cat- egories, each with about 40 training images. Tested using 3,000 images outside the training database, the system has demonstrated good accuracy and high potential in linguistic indexing of these test images.