Abstract: Computational overhead for private multiparty data function computation can be decreased by sharing parameters of dimensionality-reducing function between a client and a server, with both the client applying the function to a query vectors and the server applying the function to server vectors, both client and server creating embedded vectors. The client homomorphically encrypts the embedded query vector and provides the encrypted embedded query vector to the server. The server performs encrypted domain computations for an embedded vector processing function, each computation using the encrypted embedded query vector and one of the server embedded vectors as inputs for the function. The client receives encrypted computation results and identifies server vectors of interest using those results that are informative of a result of an application of an aggregate function to the query vector and one of the server vectors. The client obtains the vectors of interest using an oblivious transfer protocol.

Abstract: An input segment of an input video is encoded by first extracting and storing, for each segment of previously encoded videos, a set of reference features. The set of input features are matched with each set of the reference features to produce a set of scores. The reference segments having largest scores are selected to produce a first reduced set of reference segments. A rate-distortion cost for each reference segment in the first reduced set of reference segments is estimated. The reference segments in the first reduced set of reference segments is selected to produce a second reduced set of reference segments. Then, the input segment are encoded based on second reduced set of reference segments.

Abstract: In a decoder, a desired image is estimated by first retrieving coding modes from an encoded side information image. For each bitplane in the encoded side information image, syndrome bits or parity bits are decoded to obtain an estimated bitplane of quantized transform coefficients of the desired image. A quantization and a transform are applied to a prediction residual obtained using the coding modes, wherein the decoding uses the quantized transform coefficients of the encoded side information image, and is based on previously decoded bitplanes in a causal neighborhood. The estimated bitplanes of quantized transform coefficients of the desired image are combined to produce combined bitplanes. Then, an inverse quantization, an inverse transform and a prediction based on the coding modes are applied to the combined bitplanes to recover the estimate of the desired image.

Abstract: A system and method for data quality analysis between untrusted parties is provided. A dataset having attributes each associated with one or more elements is maintained. An encrypted request is received from a client regarding data quality for one of the attributes. The encrypted request includes an interest vector of separately encrypted values identifying those elements of interest for the attribute. A condensed data vector representing the elements is generated for the attribute and is the same length as the interest vector. An aggregate of the elements of interest is determined by calculating for each element in the condensed data vector, an encrypted product of that element and a corresponding element of the interest vector and by determining a total product of all the encrypted products. A data quality value is assigned to the elements of the attribute in the dataset based on the aggregate.

Abstract: A method classifies data to determine hidden states of a system, by first randomly permuting the data and inserting client to generate private data. A server classifies the private data according to a hidden Markov model (HMM) to obtain permuted noisy estimates of the states and the chaff, which are returned to the client. The client then removes the chaff, inverts the permuted noisy estimates to obtain unpermuted noisy estimates of the states.

Abstract: A pairwise distance computation transforms first and second signals using an absolute distance preserving mapping, such that a k-norm distance between the first mapped signal and the second mapped signal represents an absolute distance between the first signal and the second signal. The absolute distance preserving mapping maps an element of a first or a second signal to a vector having a size equal to a cardinality of the finite alphabet of the signals. The absolute distance preserving mapping determines a position N of the element in an ordered sequence of symbols of the finite alphabet and determines values for each of N elements of the vector as a fractional power 1/k of positive increments in the finite alphabet. The values for subsequent elements of the vector are determined as zero.

Abstract: A method extracts a low-rank descriptor of a video acquired of a scene by first extracting a set of descriptors for each image in the video. The sets of descriptors for the video are aggregated to form a descriptor matrix. Iteratively, a low-rank descriptor matrix is determined from the descriptor matrix, as well as a selection matrix that associates each column in the descriptor matrix to a corresponding column in the low-rank descriptor matrix. The low-rank descriptor matrix is output upon convergence.

Abstract: A method constructs a descriptor for an image of a scene, wherein the descriptor is associated with a vanishing point in the image by first quantizing an angular region around the vanishing point into a preset number of angular quantization bins, and a centroid of each angular quantization bin indicates a direction of the angular quantization bin. For each angular quantization bin, a sum of magnitudes of pixel gradients for pixels in the image at which a direction of the pixel gradient is aligned with the direction of the angular quantization bin is determined, wherein the steps are performed in a processor.

Abstract: A method for authenticating biometric data determines a first set of descriptors of a fingerprint. Each descriptor in the first set represents a region of the fingerprint that includes multiple minutiae. The method compares each descriptor in the first set of descriptors with each descriptor in a second set of descriptors to determine a number of matching descriptors and compares the number of matching descriptors with a threshold for authenticating the biometric data.

Abstract: A method classifies data to determine hidden states of a system, by first randomly permuting the data and inserting client to generate private data. A server classifies the private data according to a hidden Markov model (HMM) to obtain permuted noisy estimates of the states and the chaff, which are returned to the client. The client then removes the chaff, inverts the permuted noisy estimates to obtain unpermuted noisy estimates of the states.

Abstract: In a decoder, a desired image is estimated by first retrieving coding modes from an encoded side information image. For each bitplane in the encoded side information image, syndrome bits or parity bits are decoded to obtain an estimated bitplane of quantized transform coefficients of the desired image. A quantization and a transform are applied to a prediction residual obtained using the coding modes, wherein the decoding uses the quantized transform coefficients of the encoded side information image. The estimated bitplanes of quantized transform coefficients of the desired image are combined to produce combined bitplanes. Then, an inverse quantization, an inverse transform and a prediction based on the coding modes are applied to the combined bitplanes to recover the estimate of the desired image.

Abstract: In a decoder, a desired image is estimated by first retrieving coding modes from an encoded side information image. For each bitplane in the encoded side information image, syndrome bits or parity bits are decoded to obtain an estimated bitplane of quantized transform coefficients of the desired image. A quantization and a transform are applied to a prediction residual obtained using the coding modes, wherein the decoding uses the quantized transform coefficients of the encoded side information image. The estimated bitplanes of quantized transform coefficients of the desired image are combined to produce combined bitplanes. Then, an inverse quantization, an inverse transform and a prediction based on the coding modes are applied to the combined bitplanes to recover the estimate of the desired image.

Abstract: In a decoder, a desired image is estimated by first retrieving coding modes from an encoded side information image. For each bitplane in the encoded side information image, syndrome bits or parity bits are decoded to obtain an estimated bitplane of quantized transform coefficients of the desired image. A quantization and a transform are applied to a prediction residual obtained using the coding modes, wherein the decoding uses the quantized transform coefficients of the encoded side information image, and is based on previously decoded bitplanes in a causal neighborhood. The estimated bitplanes of quantized transform coefficients of the desired image are combined to produce combined bitplanes. Then, an inverse quantization, an inverse transform and a prediction based on the coding modes are applied to the combined bitplanes to recover the estimate of the desired image.

Abstract: A method authenticates an encryption of a probe vector of biometric data based on an encryption of an enrollment vector of the biometric data using consistency of discriminative elements of the biometric data. The method determines an encryption of a first distance between discriminative elements of an enrollment vector stored at a server and a probe vector presented for an authentication. The method also determines an encryption of a second distance between discriminative elements of a first consistency vector stored at the server and a second consistency vector presented for the authentication. Next, the biometric data is authenticated based on encryptions of the first and the second distances.

Abstract: A client queries a set of encrypted data instances located at a server with a query attribute of the client. The set of encrypted data instances is associated with a set of ciphertexts, wherein a ciphertext is an encrypted function of a representation of a corresponding data instance and a data instance attribute extracted from the corresponding data instance. The client decrypts the ciphertext from the set of ciphertexts based on a distance function of the query attribute and the data instance attribute to produce the representation, and accesses the corresponding data instance using the representation.

Abstract: Aggregate statistics are determined by first randomizing independently data X and Y to obtain randomized data {circumflex over (X)} and ?. The first randomizing preserves the privacy of the data X and Y. Then, the randomized data {circumflex over (X)} and ? is randomized secondly to obtain randomized data {tilde over (X)} and {tilde over (Y)} for a server, and helper information T{tilde over (X)}|{circumflex over (X)} and T?|? for a client, wherein T represents an empirical distribution, and wherein the randomizing secondly preserves the privacy of the aggregate statistics of the data X and Y. The server then determines T{tilde over (X)},{tilde over (Y)}. Last, the client applies the side information T{tilde over (X)}|{circumflex over (X)} and T?|? to T{tilde over (X)},{tilde over (Y)} to obtain an estimated {dot over (T)}X,Y, where “|” and “,” between X and Y represent a conditional and joint distribution, respectively.

Abstract: Scale-invariant features are extracted from an image. The features are projected to a lower dimensional random projection matrix by multiplying the features by a matrix of random entries. The matrix of random projections is quantized to produce a matrix of quantization indices, which form a query vector for searching a database of images to retrieve metadata related to the image.

Abstract: A system and a method select an encrypted element in an encrypted vector according to an order of the encrypted element in the encrypted vector. The selecting is performed in a privacy-preserving manner. Values of the elements of the encrypted vector are scaled, such that the order of the elements in the encrypted vector is preserved, and then permuted to produce a scaled permuted vector. Information in the encrypted domain indicative of an order of elements in the scaled permuted vector is provided to a second processor having a private key. The second processor decrypts the information to determine the index of the encrypted element based on the order of the elements. The encrypted element is obliviously selected based on the index.

Abstract: A method for authenticating biometric data determines a first set of descriptors of a fingerprint. Each descriptor in the first set represents a region of the fingerprint that includes multiple minutiae. The method compares each descriptor in the first set of descriptors with each descriptor in a second set of descriptors to determine a number of matching descriptors and compares the number of matching descriptors with a threshold for authenticating the biometric data.

Abstract: Aggregate statistics are securely determined on private data by first sampling independent first and second data at one or more clients to obtain sampled data, wherein a sampling parameter substantially smaller than a length of the data. The sampled data are encrypted to obtain encrypted data, which are then combined. The combined encrypted data are randomized to obtain randomized data. At an authorized third-party processor, a joint distribution of the first and second data is estimated from the randomized encrypted data, such that a differential privacy requirement of the first and second is satisfied.