Can an exchange be “dark,” so that orders are not displayed, while simultaneously trustworthy, so that the execution of trades and flow of information occur as promised? SEC actions against dark pools suggest cause for concern, and regulators seem to be moving towards requiring more disclosure. Yet

The ability to produce dynamic Depth of Field effects in live video streams was until recently a quality unique to movie cameras. In this paper, we present a computational camera solution coupled with real-time GPU processing to produce runtime dynamic Depth of Field effects. We first construct a hybrid-resolution stereo camera with a high-res/low-res camera pair. We recover a low-res disparity map of the scene using GPU-based Belief Propagation, and subsequently upsample it via fast Cross/Joint Bilateral Upsampling. With the recovered high-resolution disparity map, we warp the high-resolution video stream to nearby viewpoints to synthesize a light field toward the scene. We exploit parallel processing and atomic operations on the GPU to resolve visibility when multiple pixels warp to the same image location. Finally, we generate racking focus and tracking focus effects from the synthesized light field rendering. All processing stages are mapped onto NVIDIA’s CUDA architecture. Our system can produce racking and tracking focus effects for the resolution of 640×480 at 15 fps.

This paper presents a novel coprime blurred pair (CBP) model to improve data security in camera surveillance. While most previous approaches have focused on completely encrypting the video stream, we introduce a spatial encryption scheme by strategically blurring the image/video contents. Specifically, we form a public stream and a private stream by blurring the original video data using two different kernels. Each blurred stream will provide the user who has lower clearance less access to personally identifiable details while still allowing behavior to be monitored. If the behavior is recognized as suspicious, a supervisor can use both streams to deblur the contents. Our approach is based on a new CBP theory where the two kernels are coprime when mapped to bivariate polynomials in the $(z)$ domain. We show that coprimality can be derived in terms of the rank of Bézout matrix formed by sampled polynomials, and we present an efficient algorithm to factor the Bézout matrix for recovering the latent image. To make our solution practical, we implement our decryption scheme on a graphics processing unit (GPU) to achieve real-time performance. Extensive experiments demonstrate that our new scheme can effectively protect sensitive identity information in surveillance videos and faithfully reconstruct the unblurred video stream when both CBP sequences are available.

We present an interesting new protocol where participants in a securities exchange may submit cryptographically encrypted rules directly to an exchange rather than orders to buy and sell. We define this in two parts: a secure, partially trusted computer that runs the exchange and proves its actions correct, and a set of participants who define the rules and submit them to the exchange. At each “tick” of the exchange, market prices are taken from the national market system, all submitted rules are evaluated, with any resulting trades executed at market prices. Cryptography reduces information leakage, masks participants’ intent, and provides for verification. A cryptographic audit trail proves that all transactions executed by the exchange are according to a set of published exchange rules and the encrypted trading rules.

Large market participants (LMPs) must often execute trades while keeping their intentions secret. Sometimes secrecy is required before trades are completed to prevent other traders from anticipating (and exploiting) the price impact of their trades. This is known as “front-running”. In other cases, LMPs with proprietary trading strategies wish to keep their positions secret even after trading because their strategies and positions contain valuable information. LMPs include hedge funds, mutual funds, and other specialized market players.

Occluding contour (OC) plays important roles in many computer vision tasks. The study of using OC for visual inference tasks is however limited, partially due to the lack of robust OC acquisition technologies. In this work, benefit from a novel OC computation system, we propose applying OC information to category classification tasks. Specifically, given an image and its estimated occluding contours, we first compute a distance map with regard to the OCs. This map is then used to filter out distracting information in the image. The results are combined with standard recognition methods, bag-of-visual-words in our experiments, for category classification. In addition to the approach, we also present two OC datasets, which to the best of our knowledge are the first publicly available ones. The proposed method is evaluated on both datasets for category classification tasks. In all experiments, the proposed method significantly improves classification performances by about 10 percent.

We present a cryptographic protocol for conducting efficient, provably correct and secrecy-preserving combinatorial clock-proxy auctions. The "clock phase" functions as a trusted auction despite price discovery: bidders submit encrypted bids, and prove for themselves that they meet activity rules, and can compute total demand and thus verify price increases without revealing any information about individual demands. In the sealed-bid "proxy phase", all bids are revealed the auctioneer via time-lapse cryptography and a branch-and-bound algorithm is used to solve the winner-determination problem. Homomorphic encryption is used to prove the correctness of the solution, and establishes the correctness of the solution to any interested party. Still an NP-hard optimization problem, the use of homomorphic encryption imposes additional computational time on winner-determination that is linear in the size of the branch-and-bound search tree, and thus roughly linear in the original (search-based) computational time. The result is a solution that avoids, in the usual case, the exponential complexity of previous cryptographically-secure combinatorial auctions.

. We present a cryptographic protocol for conducting efficient, provably-correct and secrecy-preserving combinatorial clock-proxy auctions. The “clock phase” functions as a trusted auction despite price discovery: bidders submit encrypted bids, and prove for themselves that they meet activity rules, and can compute total demand and thus verify price increases without revealing any information about individual demands. In the sealed-bid “proxy phase”, all bids are revealed the auctioneer via time-lapse cryptography and a branch-and-bound algorithm is used to solve the winner-determination problem. Homomorphic encryption is used to prove the correctness of the solution, and establishes the correctness of the solution to any interested party. Still an NP-hard optimization problem, the use of homomorphic enryption imposes additional computational time on winner-determination that is linear in the size of the branch-and-bound search tree, and thus roughly linear in the original (search-based) computational time. The result is a solution that avoids, in the usual case, the exponential complexity of previous cryptographically-secure combinatorial auctions.

We present a useful new mechanism that facilitates the atomic exchange of many large baskets of securities in a combinatorial exchange. Cryptography prevents information about the securities in the baskets from being exploited, enhancing trust. Our exchange offers institutions who wish to trade large positions a new alternative to existing methods of block trading: they can reduce transaction costs by taking advantage of other institutions’ available liquidity, while third party liquidity providers guarantee execution—preserving their desired portfolio composition at all times. In our exchange, institutions submit encrypted orders which are crossed, leaving a “remainder”. The exchange proves facts about the portfolio risk of this remainder to third party liquidity providers without revealing the securities in the remainder, the knowledge of which could also be exploited. The third parties learn either (depending on the setting) the portfolio risk parameters of the remainder itself, or how their own portfolio risk would change if they were to incorporate the remainder into a portfolio they submit. In one setting, these third parties submit bids on the commission, and the winner supplies necessary liquidity for the entire exchange to clear. This guaranteed clearing, coupled with external price discovery from the primary markets for the securities, sidesteps difficult combinatorial optimization problems. This latter method of proving how taking on the remainder would change risk parameters of one’s own portfolio, without revealing the remainder’s contents or its own risk parameters, is a useful protocol of independent interest.

We present a practical protocol based on homomorphic cryptography for conducting provably fair sealed-bid auctions. The system preserves the secrecy of the bids, even after the announcement of auction results, while also providing for public verifiability of the correctness and trustworthiness of the outcome. No party, including the auctioneer, receives any information about bids before the auction closes, and no bidder is able to change or repudiate any bid. The system is illustrated through application to first-price, uniform-price and second-price auctions, including multi-item auctions. Empirical results based on an analysis of a prototype demonstrate the practicality of our protocol for real-world applications.

We present a practical protocol based on homomorphic cryptography for conducting provably fair sealed-bid auctions. The system preserves the secrecy of the bids, even after the announcement of auction results, while also providing for public verifiability of the correctness and trustworthiness of the outcome. No party, including the auctioneer, receives any information about bids before the auction closes, and no bidder is able to change or repudiate any bid. The system is illustrated through application to first-price, uniform-price and second-price auctions, including multi-item auctions. Empirical results based on an analysis of a prototype demonstrate the practicality of our protocol for real-world applications.

These notes were prepared to explore ideas developed in a panel discussion at Financial Cryptography 2007. Moderator: Jean Camp. Panelists: Mike Bond, Jon Callas, Christopher Thorpe.

We present a highly efficient method for proving correctness of computations while preserving secrecy of the input values. This is done in an Evaluator-Prover model which can also be realized by a secure processor. We describe an application to secure auctions.

While transparency in financial markets should enhance liquidity, its exploitation by unethical and parasitic traders discourages others from fully embracing disclosure of their own information. Traders exploit both the private information in upstairs markets used to trade large orders outside traditional exchanges and the public information present in exchanges' quoted limit order books. Using homomorphic cryptographic protocols, market designers can create "partially transparent" markets in which every matched trade is provably correct and only beneficial information is revealed. In a cryptographic securities exchange, market operators can hide information to prevent its exploitation, and still prove facts about the hidden information such as bid/ask spread or market depth.

The notion of “sending a secret message to the future” has been around for over a decade. Despite this, no solution to this problem is in common use, or even attained widespread acceptance as a fundamental cryptographic primitive. We name, construct and specify an implementation for this new cryptographic primitive, “Time-Lapse Cryptography”, with which a sender can encrypt a message so that it is guaranteed to be revealed at an exact moment in the future, even if this revelation turns out to be undesirable to the sender. Our solution combines new ideas with Pedersen distributed key generation, Feldman verifiable threshold secret sharing, and ElGamal encryption, all of which rest upon the single, broadly accepted Decisional Diffie-Hellman assumption. We develop a Time-Lapse Cryptography Service (“the Service”) based on a network of parties who jointly perform the service. The protocol is practical and secure: at a given time T the Service publishes a public key so that anyone can use it, even anonymously. Senders encrypt their messages with this public key whose private key is not known to anyone – not even a trusted third party – until a predefined and specific future time T + δ, at which point the private key is constructed and published. At or after that time, anyone can decrypt the ciphertext using this private key. The Service is envisioned as a public utility publishing a continuous stream of encryption keys and subsequent corresponding time-lapse decryption keys. We complement our theoretical foundation with descriptions of specific attacks and defenses, and describe important applications of our service in sealed bid auctions, insider stock sales, clinical trials, and electronic voting. ∗Supported in part by National Science Foundation grant CNS-0205423.