Patents by Inventor Kim Laine
Kim Laine has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11757847Abstract: Systems and methods for computing a private set intersection are disclosed. A method includes storing, at a sender device, a first set of values. The method includes receiving, from a receiver device, a homomorphic encryption of a receiver device value. The method includes computing a homomorphically encrypted number based on a difference between the homomorphic encryption of the receiver device value and each value in the first set of values, and based on a hash function of the encryption of the receiver device value. The method includes transmitting the homomorphically encrypted number to the receiver device for determination, at the receiver device, whether the receiver device value is in the first set of values.Type: GrantFiled: December 16, 2020Date of Patent: September 12, 2023Assignee: Microsoft Technology Licensing, LLCInventors: Kim Laine, Hao Chen, Peter Byerley Rindal, Zhicong Huang
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Patent number: 11177935Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed to optimizing the generation, evaluation, and selection of tensor circuit specifications for a tensor circuit to perform homomorphic encryption operations on encrypted data. A computing device having an improved compiler and runtime configuration can obtain a tensor circuit and associated schema. The computing device can map the obtained tensor circuit to an equivalent tensor circuit, adapted to perform fully homomorphic encryption (FHE) operations, and instantiated based on the obtained associated scheme. The computing device can then monitor a flow of data through the equivalent FHE-adapted tensor circuit utilizing various tensor circuit specifications determined therefor.Type: GrantFiled: October 31, 2018Date of Patent: November 16, 2021Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Madanlal S. Musuvathi, Kim Laine, Kristin E. Lauter, Hao Chen, Olli Ilari Saarikivi, Saeed Maleki, Roshan Dathathri, Todd D. Mytkowicz
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Publication number: 20210194856Abstract: Systems and methods for computing a private set intersection are disclosed. A method includes storing, at a sender device, a first set of values. The method includes receiving, from a receiver device, a homomorphic encryption of a receiver device value. The method includes computing a homomorphically encrypted number based on a difference between the homomorphic encryption of the receiver device value and each value in the first set of values, and based on a hash function of the encryption of the receiver device value. The method includes transmitting the homomorphically encrypted number to the receiver device for determination, at the receiver device, whether the receiver device value is in the first set of values.Type: ApplicationFiled: December 16, 2020Publication date: June 24, 2021Inventors: Kim Laine, Hao Chen, Peter Byerley Rindal, Zhicong Huang
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Patent number: 10904225Abstract: Systems and methods for computing a private set intersection are disclosed. A method includes storing, at a sender device, a first set of values. The method includes receiving, from a receiver device, a homomorphic encryption of a receiver device value. The method includes computing a homomorphically encrypted number based on a difference between the homomorphic encryption of the receiver device value and each value in the first set of values, and based on a hash function of the encryption of the receiver device value. The method includes transmitting the homomorphically encrypted number to the receiver device for determination, at the receiver device, whether the receiver device value is in the first set of values.Type: GrantFiled: June 14, 2018Date of Patent: January 26, 2021Assignee: Microsoft Technology Licensing, LLCInventors: Kim Laine, Hao Chen, Peter Byerley Rindal, Zhicong Huang
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Patent number: 10853422Abstract: Systems, methods, and computer-executable instructions for reducing amortized computational costs for a query that includes receiving at least two indexes for elements stored in an n-element database. The n-element database is encoded into at least three buckets. Each element is stored within at least two buckets. Each bucket stores a proper subset of the n-elements. For each of the two indexes, a bucket is determined to retrieve the element at the index. The determined buckets are queried to retrieve the elements. The elements at the indexes are retrieved based on the querying the determined buckets.Type: GrantFiled: April 19, 2018Date of Patent: December 1, 2020Assignee: Microsoft Technology Licensing, LLCInventors: Kim Laine, Hao Chen, Srinath T V Setty, Sebastian Angel
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Patent number: 10608811Abstract: The disclosure herein relates to private set intersection techniques. The described private set intersection techniques enable entities to determine common data strings in their respective data sets. The private set intersection techniques described herein allow those common data strings to be shareable between the entities, while maintaining the secrecy of other data strings stored in their respective data sets.Type: GrantFiled: June 15, 2017Date of Patent: March 31, 2020Assignee: Microsoft Technology Licensing, LLCInventors: Hao Chen, Kim Laine
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Publication number: 20200076570Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed to optimizing the generation, evaluation, and selection of tensor circuit specifications for a tensor circuit to perform homomorphic encryption operations on encrypted data. A computing device having an improved compiler and runtime configuration can obtain a tensor circuit and associated schema. The computing device can map the obtained tensor circuit to an equivalent tensor circuit, adapted to perform fully homomorphic encryption (FHE) operations, and instantiated based on the obtained associated scheme. The computing device can then monitor a flow of data through the equivalent FHE-adapted tensor circuit utilizing various tensor circuit specifications determined therefor.Type: ApplicationFiled: October 31, 2018Publication date: March 5, 2020Inventors: Madanlal S. MUSUVATHI, Kim LAINE, Kristin E. LAUTER, Hao CHEN, Olli Ilari SAARIKIVI, Saeed MALEKI, Roshan DATHATHRI, Todd D. MYTKOWICZ
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Publication number: 20190342270Abstract: Systems and methods for computing a private set intersection are disclosed. A method includes storing, at a sender device, a first set of values. The method includes receiving, from a receiver device, a homomorphic encryption of a receiver device value. The method includes computing a homomorphically encrypted number based on a difference between the homomorphic encryption of the receiver device value and each value in the first set of values, and based on a hash function of the encryption of the receiver device value. The method includes transmitting the homomorphically encrypted number to the receiver device for determination, at the receiver device, whether the receiver device value is in the first set of values.Type: ApplicationFiled: June 14, 2018Publication date: November 7, 2019Inventors: Kim Laine, Hao Chen, Peter Byerley Rindal, Zhicong Huang
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Publication number: 20190325082Abstract: Systems, methods, and computer-executable instructions for reducing amortized computational costs for a query that includes receiving at least two indexes for elements stored in an n-element database. The n-element database is encoded into at least three buckets. Each element is stored within at least two buckets. Each bucket stores a proper subset of the n-elements. For each of the two indexes, a bucket is determined to retrieve the element at the index. The determined buckets are queried to retrieve the elements. The elements at the indexes are retrieved based on the querying the determined buckets.Type: ApplicationFiled: April 19, 2018Publication date: October 24, 2019Inventors: Kim Laine, Hao Chen, Srinath T V Setty, Sebastian Angel
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Patent number: 10333695Abstract: Homomorphic encryption systems encode plaintext represented as rational numbers based on modular products of the rational numbers and a power of an integer basis with respect to a modulus defined by the integer basis. Decrypted ciphertexts are decoded based on modular products of the decrypted ciphertexts and an integer power of the integer basis. Typically, the integer power is one-half the number of available digits if the integer basis is odd; if the integer basis is even, the integer power is one-half the number of available digits plus one.Type: GrantFiled: November 10, 2016Date of Patent: June 25, 2019Assignee: Microsoft Technology Licensing, LLCInventors: Kim Laine, Rachel Louise Player, Hao Chen
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Patent number: 10296709Abstract: The techniques and/or systems described herein are directed to improvements in genomic prediction using homomorphic encryption. For example, a genomic model can be generated by a prediction service provider to predict a risk of a disease or a presence of genetic traits. Genomic data corresponding to a genetic profile of an individual can be batch encoded into a plurality of polynomials, homomorphically encrypted, and provided to a service provider for evaluation. The genomic model can be batch encoded as well, and the genetic prediction may be determined by evaluating a dot product of the genomic model data the genomic data. A genomic prediction result value can be provided to a computing device associated with a user for subsequent decrypting and decoding. Homomorphic encoding and encryption can be used such that the genomic data may be applied to the prediction model and a result can be obtained without revealing any information about the model, the genomic data, or any genomic prediction.Type: GrantFiled: June 10, 2016Date of Patent: May 21, 2019Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Kim Laine, Nicolo Fusi, Ran Gilad-Bachrach, Kristin E. Lauter
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Publication number: 20180367293Abstract: The disclosure herein relates to private set intersection techniques. The described private set intersection techniques enable entities to determine common data strings in their respective data sets. The private set intersection techniques described herein allow those common data strings to be shareable between the entities, while maintaining the secrecy of other data strings stored in their respective data sets.Type: ApplicationFiled: June 15, 2017Publication date: December 20, 2018Inventors: Hao CHEN, Kim LAINE
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Patent number: 10153894Abstract: The techniques and/or systems described herein are directed to improvements in homomorphic encryption to improve processing speed and storage requirements. For example, the techniques and/or systems can be used on a client device to encode data to be sent to a remote server, to be operated on while maintaining confidentiality of data. For example, data including a real number can be encoded as a polynomial, with the fractional part of the real number encoded as high-order coefficients in the polynomial. Further, real numbers can be approximated and encoded in a polynomial using a fractional base, and/or the encoding can include slot encoding. Thus, the optimized encodings disclosed herein provide an optimized homomorphic encryption scheme.Type: GrantFiled: November 5, 2015Date of Patent: December 11, 2018Assignee: Microsoft Technology Licensing, LLCInventors: Kim Laine, Nathan Dowlin, Ran Gilad-Bachrach, Michael Naehrig, John Wernsing, Kristin E. Lauter
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Patent number: 10075289Abstract: The techniques and/or systems described herein are directed to improvements in homomorphic encryption to improve processing speed and storage requirements. For example, the techniques and/or systems can be used on a client device to encode data to be sent to a remote server, to be operated on while maintaining confidentiality of data. The encoding scheme can be optimized by automatically selecting one or more parameters using an error growth simulator based on an actual program that operates on the encoded data. For example, the simulator can be used iteratively to determine an optimized parameter set which allows for improved homomorphic operations while maintaining security and confidentiality of a user's data.Type: GrantFiled: November 5, 2015Date of Patent: September 11, 2018Assignee: Microsoft Technology Licensing, LLCInventors: Kim Laine, Nathan Dowlin, Ran Gilad-Bachrach, Michael Naehrig, John Wernsing, Kristin E. Lauter
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Publication number: 20180131506Abstract: Homomorphic encryption systems encode plaintext represented as rational numbers based on modular products of the rational numbers and a power of an integer basis with respect to a modulus defined by the integer basis. Decrypted ciphertexts are decoded based on modular products of the decrypted ciphertexts and an integer power of the integer basis. Typically, the integer power is one-half the number of available digits if the integer basis is odd; if the integer basis is even, the integer power is one-half the number of available digits plus one.Type: ApplicationFiled: November 10, 2016Publication date: May 10, 2018Applicant: Microsoft Technology Licensing, LLCInventors: Kim Laine, Rachel Louise Player, Hao Chen
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Patent number: 9900147Abstract: The techniques and/or systems described herein are directed to improvements in homomorphic operations within a homomorphic encryption scheme. The homomorphic operations may be performed on encrypted data received from a client device without decrypting the data at a remote computing device, thereby maintaining the confidentiality of the data. In addition to the operations of addition, subtraction, and multiplication, the homomorphic operations may include an approximate division, a sign testing, a comparison testing, and an equality testing. By combining these operations, a user may perform optimized operations with improved processor and memory requirements.Type: GrantFiled: December 18, 2015Date of Patent: February 20, 2018Assignee: Microsoft Technology Licensing, LLCInventors: Kim Laine, Nathan P. Dowlin, Ran Gilad-Bachrach, Michael Naehrig, John Wernsing, Kristin E. Lauter
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Publication number: 20170357749Abstract: The techniques and/or systems described herein are directed to improvements in genomic prediction using homomorphic encryption. For example, a genomic model can be generated by a prediction service provider to predict a risk of a disease or a presence of genetic traits. Genomic data corresponding to a genetic profile of an individual can be batch encoded into a plurality of polynomials, homomorphically encrypted, and provided to a service provider for evaluation. The genomic model can be batch encoded as well, and the genetic prediction may be determined by evaluating a dot product of the genomic model data the genomic data. A genomic prediction result value can be provided to a computing device associated with a user for subsequent decrypting and decoding. Homomorphic encoding and encryption can be used such that the genomic data may be applied to the prediction model and a result can be obtained without revealing any information about the model, the genomic data, or any genomic prediction.Type: ApplicationFiled: June 10, 2016Publication date: December 14, 2017Inventors: Kim Laine, Nicolo Fusi, Ran Gilad-Bachrach, Kristin E. Lauter
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Publication number: 20170359321Abstract: Techniques and architectures may be used to provide an environment where a data owner storing private encrypted data in a cloud and a data evaluator may engage in a secure function evaluation on at least a portion of the data. Neither of these involved parties is able to learn anything beyond what the parties already know and what is revealed by the function, even if the parties are actively malicious. Such an environment may be useful for business transactions, research collaborations, or mutually beneficial computations on aggregated private data.Type: ApplicationFiled: June 13, 2016Publication date: December 14, 2017Inventors: Peter B. Rindal, Ran Gilad-Bachrach, Kim Laine, Michael J. Rosulek, Kristin E. Lauter
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Publication number: 20170180115Abstract: The techniques and/or systems described herein are directed to improvements in homomorphic operations within a homomorphic encryption scheme. The homomorphic operations may be performed on encrypted data received from a client device without decrypting the data at a remote computing device, thereby maintaining the confidentiality of the data. In addition to the operations of addition, subtraction, and multiplication, the homomorphic operations may include an approximate division, a sign testing, a comparison testing, and an equality testing. By combining these operations, a user may perform optimized operations with improved processor and memory requirements.Type: ApplicationFiled: December 18, 2015Publication date: June 22, 2017Inventors: Kim Laine, Nathan P. Dowlin, Ran Gilad-Bachrach, Michael Naehrig, John Wernsing, Kristin E. Lauter
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Publication number: 20170134156Abstract: The techniques and/or systems described herein are directed to improvements in homomorphic encryption to improve processing speed and storage requirements. For example, the techniques and/or systems can be used on a client device to encode data to be sent to a remote server, to be operated on while maintaining confidentiality of data. The encoding scheme can be optimized by automatically selecting one or more parameters using an error growth simulator based on an actual program that operates on the encoded data. For example, the simulator can be used iteratively to determine an optimized parameter set which allows for improved homomorphic operations while maintaining security and confidentiality of a user's data.Type: ApplicationFiled: November 5, 2015Publication date: May 11, 2017Inventors: Kim Laine, Nathan Dowlin, Ran Gilad-Bachrach, Michael Naehrig, John Wernsing, Kristin E. Lauter