Briefly, embodiments are directed to a system, method, and article for acquiring a symbol comprising a representation of input data. The symbol may be converted into an emergent language expression in an emergent language via processing of a first neural network. Transmission of the emergent language expression may be initiated over a communications network, where the emergent language comprises a language based on and specific to the input data. The emergent language expression may be translated back into the representation of the input data via processing of a second neural network.

Methods, systems, and computer programs for generating cryptographic function parameters are described. In some examples, astronomical data from an observed astronomical event is obtained. A pseudorandom generator is seeded based on the astronomical data. After seeding the pseudorandom generator, an output from the pseudorandom generator is obtained. A parameter for a cryptographic function is generated by operation of one or more data processors. The parameter is generated from the output from the pseudorandom generator.

Disclosed are an apparatus and method with homomorphic encryption using automorphism. A computing apparatus includes one or more processors and a memory storing instructions configured to cause the one or more processors to, for a blind rotation key for performing a blind rotation operation and an operand ciphertext of the blind rotation operation: generate a preprocessed ciphertext by performing preprocessing on the operand ciphertext based on automorphism, and generate an operation result of the homomorphic encryption by performing the blind rotation operation for the operand ciphertext on a vector component of the preprocessed ciphertext and a vector component of the blind rotation key.

Disclosed is a ciphertext calculation method. The ciphertext calculation method comprises the steps of: receiving a comparative calculation command for a plurality of ciphertexts of the same type; performing a calculation by reflecting the plurality of ciphertexts of the same type on a synthesis function corresponding to the comparative calculation command; and outputting the calculated ciphertexts of the same type.

An encryption device (50) generates a ciphertext. A master re-encryption key generation device (40) generates a master re-encryption key that cannot decrypt a ciphertext generated by the encryption device (50), but can generate a re-encryption key for changing an access range for a ciphertext generated by the encryption device (50). A re-encryption device (60) generates a re-encryption key for re-encrypting a target ciphertext generated by the encryption device (50), using the master re-encryption key, and re-encrypts the target ciphertext to generate a re-encrypted ciphertext, using the generated re-encryption key.

A method for storing data on a storage entity (SE) includes the steps of: (a) dividing a file to be stored into a plurality of chunks by a client; (b) computing a secret key for each of the chunks of the file; (c) computing for each of the chunks a chunk identifier by the client; (d) checking, by the SE, whether one or more of the chunks have already been stored based on the computed chunk identifiers; and (e) it a case where it is determined that one or more of the chunks have not already been stored, performing the following: encoding the corresponding chunks; computing chunk tags for the chunks using the computed secret key; and storing the encoded chunks and the chunk tags.

One embodiment provides for an electronic device, comprising a network interface, a memory coupled with the network interface, at least one application processor coupled with the memory, the at least one processor to execute instructions stored in the memory, and a secure processor including a cryptographic engine, wherein the cryptographic engine is to generate a sealed encrypted message to be transmitted via the network interface, the sealed encrypted message encrypted on behalf of the at least one application processor and includes a signature to enable integrity verification of the sealed encrypted message, the signature generated based on an identity key of the electronic device and data including ciphertext of the encrypted message and a public key of a recipient of the sealed encrypted message.

According to one embodiment, a method performed by a first communication device for generating a symmetric session key for encrypted communication with a second communication device is described comprising generating a blinding value for each of a first and a second private key component, generating a blinded public key from the first private key component, the second private key component, and the blinding values using a public key generation function, transmitting the blinded public key to the second communication device for encryption of a shared secret, receiving the shared secret, generating a session key for encrypted communication with the second communication device from the shared secret, encrypting, using the session key, an information from which the blinding values are derivable and transmitting the encrypted information to the second communication device.

A method may include collecting from each of multiple endpoint devices a set of anonymized interactions of the corresponding endpoint device with other endpoint devices. Each anonymized interaction in the set of anonymized interactions may be based on an ephemeral unique identifier of another endpoint device involved in a corresponding anonymized interaction with the corresponding endpoint device. The method may include, for each endpoint device, resolving identities of the other endpoint devices with which the corresponding endpoint device has interacted from the corresponding set of anonymized interactions.

A method is provided for solving a computational problem that is reducible to a problem of counting solutions to an associated decision problem. The method includes, using a quantum computer, estimating a number of the solutions to the decision problem by determining if there is at least one solution to the decision problem that lies in a pseudo-random set. The method also includes outputting or using the estimated number of the solutions to the decision problem as a solution to the computational problem. Determining if there is at least one solution to the decision problem that lies in the pseudo-random set could include determining if there is a sequence of solutions to the decision problem that, taken together, lies in the pseudo-random set.