A method is provided for conducting an operation, the method including: determining a first result based on combining a first input with a first mask; determining a second result based on combining a second input with a second mask, the first mask and the second mask fulfilling a precondition; and conducting the operation based on the first result and the second result. A corresponding device is also provided.

An example of the instant solution comprises at least one of receiving an encrypted data and an encryption key, generating a randomized matrix, dispersing the encrypted data based on the randomized matrix resulting in a fragmented encrypted data and dispersing the encryption key based on the randomized matrix and the fragmented encrypted data.

Certain aspects of the present disclosure provide techniques for performing computations on encrypted data. One example method generally includes obtaining, at a computing device, encrypted data, wherein the encrypted data is encrypted using fully homomorphic encryption and performing at least one computation on the encrypted data while the encrypted data remains encrypted. The method further includes identifying a clear data operation to perform on the encrypted data and transmitting, from the computing device to a server, a request to perform the clear data operation on the encrypted data, wherein the request includes the encrypted data. The method further includes receiving, at the computing device in response to the request, encrypted output from the server, wherein the encrypted output is of the same size and the same format for all encrypted data transmitted to the server.

A random flux of rising bubbles generates a fluctuating electrical current that is processed into a high-quality bit stream. Any stream of fully or mildly randomized bits is measured for its degree of randomness, and that randomness is amplified or attenuated as the case may be. Impact on ciphers and cyber security tools that rely on randomness.

Methods, systems, and apparatus for quantum random number generation. In one aspect, a method includes initializing N qubits in respective superposition states; computing a randomly selected oracle randomization function using i) the initialized N qubits and ii) multiple ancilla qubits, wherein the multiple ancilla qubits comprise a first ancilla qubit and one or more second ancilla qubits; performing a phase flip operation on the first ancilla qubit; computing an inverse of the randomly selected oracle randomization function using i) the N qubits and ii) the multiple ancilla qubits; performing a diffusion operation on the N qubits; and measuring the N qubits and providing data representing the measured states of the N qubits as N random bits.

An apparatus generates truly random numbers. The apparatus includes a container that is at least partially filled with a fluid (e.g., water or air). The apparatus also includes objects (e.g., dice) suspended freely in the fluid. The apparatus includes agitators configured to agitate the fluid, and cameras configured to capture images of the objects. When the agitators agitate the fluid, the objects move freely (e.g., move with the created currents) in the fluid in the container. The apparatus also includes a random number generation circuit coupled to the cameras. The random number generation circuit is configured to generate random numbers based on the images captured by the cameras. In some embodiments, the agitators are one or more motor-driven propellers that stir the fluid. Some embodiments use a hydraulic pump to agitate the fluid (e.g., circulating the fluid using both a push action and a pull action).

Aspects of the current subject matter are directed to performing privacy-preserving analytics over sensitive data without sharing plaintext data. According to an aspect, a system includes at least one data processor and at least one memory storing instructions which, when executed by the at least one data processor, result in operations including: receiving, from each of a plurality of clients, a utility score and a partial noise value; performing, based on the received utility scores and the partial noise values, a secure multi-party computation of a privacy-preserving statistic, the performing of the secure multi-party computation of the privacy-preserving statistic further comprising determining a noisy utility score for each data value in a domain of output values and selecting a highest noise utility score from the determined noisy utilities scores; and providing, based on the selected highest utility score, an output value for the privacy-preserving statistic.

Described are techniques for privacy-preserving endorsements in blockchain transactions. The techniques include a method comprising associating a ledger key in a local collection with an ephemeral key, where the ephemeral key is a re-randomization of a key associated with a first organization. The method further comprises generating, by a first peer associated with the first organization, an anonymous endorsement of a transaction in a blockchain using the ephemeral key. The method further comprises determining, by a second peer associated with the first organization, that the first peer endorsed the transaction. The method further comprises retrieving, by the second peer, a preimage from the first peer. The method further comprises providing information including the anonymous endorsement and the transaction to a second organization associated with the blockchain, where the anonymous endorsement is anonymous to peers associated with the second organization.

Some implementations disclosed herein enable matching identifiers across multiple sources. This may involve adding a unique attribute (e.g., anonymous unique homomorphic identifiers) and/or using randomization to enable comparing data from multiple sources, while also maintaining data privacy. In one example, matches across multiple sources are identified, for example, identifying that there are 100 user identifiers that are in private data sets of three different sources. Such matching may be used to enable private, multi-touch attribution. In another example, techniques are used to determine that data maintained by one source is not also within other sources (e.g., identifying that there are 200 user identifiers that are in data from a first source but not in data from a second source and not in data from a third source. Such determinations may be used to generate control group data that does not match data from other sources.

Embodiments are directed to countermeasures for side-channel attacks on protected sign and key exchange operations. An embodiment of storage mediums includes instructions for commencing a process including an elliptic curve scalar multiplication (ESM) operation including application of a secret scalar value; splitting the secret scalar value into two random scalar values; counting a number of leading ‘0’ bits in the scalar value and skipping the number of leading ‘0’ bits in processing; performing an ESM iteration for each bit of the secret scalar value beginning with a most significant ‘1’ bit of the scalar value including a Point Addition operation and a Point Double operation for each bit on randomized points; performing ESM operation dummy iterations equal to the number of leading ‘0’ bits; and returning an output result for the ESM operation.