Techniques are described for algorithmic confidential computing on personal data and to an insights provider providing access to personal data using limited-use anonymous insights records stored on a blockchain. To enable service providers and other queriers to obtain such insights information in a secure manner, an insights provider creates an anonymous insights record that is recorded on a blockchain responsive a request from a subject indicating that the subject desires to share one or more items of insights information. An anonymous insights record contains a single-use (or limited number of use) random number that is used by the insights provider to index the data in a shards index database for the relevant shards of the insights data file. These multiple segments can then be stored across multiple separate repositories using a decentralized file storage service.

A computer-implemented method of generating random numbers based on blockchain transactions, wherein the method is performed by a generating party and comprises: obtaining a candidate block header, wherein the candidate block header is based on a set of blockchain transactions; applying a hash function to at least the candidate block header one or more times, wherein each application of the hash function to at least the candidate block header generates a respective hash digest; generating one or more random numbers, wherein each random number is generated based on a respective hash digest; and outputting the one or more random numbers to one or more consuming devices.

A method is provided for that includes representing a random number and a threshold as a sequence of bits and comparing the sequence of bits representing the random number with the sequence of bits representing the threshold on a bit-wise basis. The most significant bit of the sequence of bits representing the random number is compared with the most significant sequence of bits representing the threshold. If the bits are not equal, deciding that the random number is larger or smaller than the threshold. If the bits are equal, comparing the immediately following bit in the sequence of bits representing the random number with the immediately following bit in the sequence of bits representing the threshold, and repeating this until the bit of the random number does not equal that of the threshold is reached or until all bits have been compared and found to be equal.

Techniques are described for algorithmic confidential computing on personal data and to an insights provider providing access to personal data using limited-use anonymous insights records stored on a blockchain. To enable service providers and other queriers to obtain such insights information in a secure manner, an insights provider creates an anonymous insights record that is recorded on a blockchain responsive a request from a subject indicating that the subject desires to share one or more items of insights information. An anonymous insights record contains a single-use (or limited number of use) random number that is used by the insights provider to index the data in a shards index database for the relevant shards of the insights data file. These multiple segments can then be stored across multiple separate repositories using a decentralized file storage service.

Various examples are directed to systems and methods for securing a data storage device. A storage controller may receive a read request directed to the data storage device. The read request may comprise address data indicating a first address of a first storage location at the data storage device. The storage controller may request from the data storage device a first encrypted data unit stored at the first memory element and a first encrypted set of parity bits, such as Error Correction Code (ECC) bits, associated with the first storage location. An encryption system may decrypt the first encrypted set of parity bits to generate a first set of parity bits based at least in part on an a first location parity key for the first address.

A first system creates and sends encryption key data to multiple data sources. A second system receives data encrypted using the encryption key data from the multiple data sources; the data may include noise data such that, even if decrypted, the original data cannot be discovered. Because the encryption is additively homomorphic, the second system may create encrypted summation data using the encrypted data. The first system separately receives the noise data encrypted using the same technique as the encrypted data. The second system may send the encrypted summation data to the first system, which may then remove the noise data from the encrypted summation data to create unencrypted summation data.

Methods and systems for controlling access to secure data use a custodial TRNG disk. Source data is encrypted using first key data from a first TRNG disk to generate encrypted data which is stored at a first location by a first entity. A second TRNG disk has second key data which is stored at a second location by a second entity. A first TRNG disk copy and a second TRNG disk copy are made identical to the first TRNG disk and the second TRNG disk, respectively, and are stored at one or more locations by a custodial entity. The first key data and the second key data are encoded together, and then transmitted to one or more of the first or second entities. The first quantity of encrypted data is decryptable using the encoded first key data and the second key data.

Systems and methods for power control based on performance modification through pulse modulation include an integrated circuit (IC) that may evaluate certain limit conditions within a computing device and compare the limit conditions to corresponding predefined thresholds. When a given predefined threshold is exceeded, an overage signal may be sent to a limits management circuit within the initial IC or another IC. The limits management circuit may generate a single-bit throttle signal through a pulse modulation circuit. The single-bit throttle signal may modify internal processing of an associated processor, which in turn changes power consumption.

The disclosure provides a blockchain random number generating system and blockchain random number generating method. The blockchain random number generating system includes a smart contract. A second electronic device generates a second random number and a second hash value corresponding to the second random number, and transmits the second hash value to a first block of the smart contract. A first electronic device generates a first random number and a first hash value corresponding to the first random number, and transmits the first hash value to a second block of the smart contract. A fifth block of the smart contract receives a real-time transaction index, and generates a random seed according to the real-time transaction index, the first random number and the second random number and calculates a result of the smart contract in the fifth block according to the random seed.

The disclosed exemplary embodiments include computer-implemented apparatuses and methods that validate confidential data based privacy-preserving homomorphic computations involving encrypted data. For example, an apparatus may receive, from a first computing system, encrypted data that includes a first encrypted value representative of at least one of first account data or an element of cryptographic data. Based on the first encrypted value and on second encrypted values, the apparatus may generate encrypted residual values representative of second account data associated with one or more reference accounts, and the apparatus may request and receive a decrypted residual value associated with each of the encrypted residual values from a second computing system. The apparatus may transmit the decrypted residual values to the first computing system, which may validate the first account data based on at least the decrypted residual values and perform operations associated with the validated first account data.