Abstract: Embodiments disclosed herein describe computing private set intersection (PSI) between various parties using delegation to other devices and in one round of interaction (request and response). The various parties involved and their associated computing devices are referred to herein as participants. The protocol is forward-secure and completely hides the data of participants from an eavesdropper. Because the protocol only uses a single round of interaction, it is more efficient and does not require each participant to have servers that remain online continuously.

Abstract: Embodiments disclosed herein describe computing calculations based on two overlapping private sets between various parties. To conduct the calculation, an intersection of the overlapping private sets data lists is conducted without revealing the underlying data. A homomorphic encryption is conducted on the intersecting data elements to allow them to be compared.

Abstract: Embodiments disclosed herein describe computing calculations based on two overlapping private sets between various parties. To conduct the calculation, an intersection of the overlapping private sets data lists is conducted without revealing the underlying data. A homomorphic encryption is conducted on the intersecting data elements to allow them to be compared.

Abstract: Embodiments disclosed herein describe computing private set intersection (PSI) between various parties using delegation to other devices and in one round of interaction (request and response). The various parties involved and their associated computing devices are referred to herein as participants. The protocol is forward-secure and completely hides the data of participants from an eavesdropper. Because the protocol only uses a single round of interaction, it is more efficient and does not require each participant to have servers that remain online continuously.

Abstract: Embodiments disclosed herein describe computing private set intersection (PSI) between various parties using delegation to other devices and in one round of interaction (request and response). The various parties involved and their associated computing devices are referred to herein as participants. The protocol is forward-secure and completely hides the data of participants from an eavesdropper. Because the protocol only uses a single round of interaction, it is more efficient and does not require each participant to have servers that remain online continuously.

Abstract: Disclosed herein are system, method, and computer program product embodiments for generating and chaining zero-knowledge proofs (“ZKPs”) using proof chaining. A proof may be divided into different components to analyze data in a series and/or parallel manner using chained proof systems. The proof systems may generate hash values indicating that particular functions were applied to the instances of the underlying data. The hash values may prove that a particular function was applied to instances of the underlying data. Using the proof chaining configuration, a data supply system may generate a ZKP allowing a data requesting system to trust a function result without needing to receive the underlying data.

Abstract: Disclosed herein are system, method, and computer program product embodiments for generating and chaining zero-knowledge proofs (“ZKPs”) using proof chaining. A proof may be divided into different components to analyze data in a series and/or parallel manner using chained proof systems. The proof systems may generate hash values indicating that particular functions were applied to the instances of the underlying data. The hash values may prove that a particular function was applied to instances of the underlying data. Using the proof chaining configuration, a data supply system may generate a ZKP allowing a data requesting system to trust a function result without needing to receive the underlying data.

Abstract: A method and a system for generating private randomness and/or public randomness are provided. A measurement of a public randomness and/or a measurement of a plaintext may be obtained, and a desired size of a private randomness may be determined based on the measurements. The measurements may be based on one or more Tsallis entropy values of the public randomness and/or the plaintext. Private randomness may be generated, the private randomness may be encrypted, the private randomness may be deleted so that the private randomness is unrecoverable, and the encrypted private randomness may be published. Encrypted private randomness and public randomness may be obtained, and a new public randomness may be generated based on the public randomness and the encrypted private randomness.

Abstract: A method and a system for generating public randomness are provided. A measurement of a public randomness and/or a measurement of a plaintext may be obtained, and a desired size of a private randomness may be determined based on the measurements. Private randomness may be generated, the private randomness may be encrypted, the private randomness may be deleted so that the private randomness is unrecoverable, and the encrypted private randomness may be published. Encrypted private randomness and public randomness may be obtained, and a new public randomness may be generated based on the public randomness and the encrypted private randomness.

Abstract: A method and a system for generating public randomness are provided. A measurement of a public randomness and/or a measurement of a plaintext may be obtained, and a desired size of a private randomness may be determined based on the measurements. Private randomness may be generated, the private randomness may be encrypted, the private randomness may be deleted so that the private randomness is unrecoverable, and the encrypted private randomness may be published. Encrypted private randomness and public randomness may be obtained, and a new public randomness may be generated based on the public randomness and the encrypted private randomness.

Abstract: A method and a system for generating private randomness and/or public randomness are provided. A measurement of a public randomness and/or a measurement of a plaintext may be obtained, and a desired size of a private randomness may be determined based on the measurements. The measurements may be based on one or more Tsallis entropy values of the public randomness and/or the plaintext. Private randomness may be generated, the private randomness may be encrypted, the private randomness may be deleted so that the private randomness is unrecoverable, and the encrypted private randomness may be published. Encrypted private randomness and public randomness may be obtained, and a new public randomness may be generated based on the public randomness and the encrypted private randomness.