H04L9/0656

Methods and devices for secure secret key generation

There is provided a cryptographic key determination device for determining one or more cryptographic keys in a cryptographic device, the cryptographic device being configured to execute one or more test programs, the cryptographic device comprising one or more components (11-i), each component (11-i) being configured to generate static and dynamic data, the dynamic data being generated in response to the execution of the one or more test programs, wherein the cryptographic key determination device comprises: a data extraction unit configured to extract at least one part of the static data and at least one part of the dynamic data generated by the one or more components (11-i), and a key generator configured to combine the at least one part of static data and the at least one part of dynamic data, and to determine the one or more cryptographic keys by applying a cryptographic function to the combined data.

Wideband featureless rateless chaotic waveform generation method

A wideband chaotic waveform that is rateless in that it may be modulated at virtually any rate and has a minimum of features introduced into the waveform. Further, the waveform provided may be operated below a signal to noise ratio wall to further enhance the LPD and LPE aspects, thereof. Additionally, the present disclosure may provide a mix of coherent and non-coherent processing techniques applied to signal samples to efficiently achieve coarse synchronization with a waveform that is faster, more efficient and more accurate than using time domain signal correlators alone.

Method for establishing a secure private interconnection over a multipath network

A method for establishing a fully private, information secure interconnection between a source and a destination over a data network with at least a portion of a public infrastructure. The method comprising at the source creating n shares of a source data according to a predetermined secret sharing scheme, and encrypting the n shares using (n, k) secret sharing. Further, defining for at least one node vi a directed edge (Vi1, Vi2) that has a k−1 capacity. All outgoing links of vi are connected to vi2. Additionally, using a maximum flow algorithm to define the maximum number of shares outgoing from vi2, and therefore from vi, on each outgoing link. The number of shares forwarded by node vi does not exceed the number of maximum shares that were defined by the maximum flow algorithm.

SECRET SHARED RANDOM ACCESS MACHINE
20180011996 · 2018-01-11 ·

A method of providing a distributed scheme for executing a RAM program, without revealing any information regarding the program, the data and the results, according to which the instructions of the program are simulated using SUBLEQ instructions and the execution of the program is divided among a plurality of participating computational resources such as one or more clouds, which do not communicate with each other, while secret sharing all the program's SUBLEQ instructions, to hide their nature of operation and the sequence of operations. Private string matching is secretly performed by comparing strings represented in secret shares, for ensuring the execution of the right instruction sequence. Then arithmetic operations are performed over secret shared bits and branch operations are performed according to the secret shared sign bit of the result.

Method and system for key agreement utilizing semigroups
11711208 · 2023-07-25 · ·

A method for key agreement between a first party and a second party over a public communications channel, the method including selecting, by the first party, from a semigroup, a first value “a”; multiplying the first value “a” by a second value “b” to create a third value “d”, the second value “b” being selected from the semigroup; sending the third value “d” to the second party; receiving, from the second party, a fourth value “e”, the fourth value comprising the second value “b” multiplied by a fifth value “c” selected by the second party from the semigroup; and creating a shared secret by multiplying the first value “a” with the fourth value “e”, wherein the shared secret matches the third value “d” multiplied by the fifth value “c”.

Quantum safe key exchange scheme

Aspects of the invention include a computer-implemented method of executing a hybrid quantum safe key exchange system. The computer-implemented method includes initially retrieving an authenticated random value from a trusted source, generating a first Z value using a first elliptic curve (EC) private key and a first certified form of an EC public key with an EC Diffie-Hellman (ECDH) algorithm, deriving a shared key using the authenticated random value and the first Z value with a key derivation function, decrypting the authenticated random value using a quantum safe algorithm (QSA) private key, generating a second Z value using a second EC private key and a second certified form of the EC public key with the ECDH algorithm and deriving the shared key using the authenticated random value and the second Z value with the key derivation function.

Fast unbreakable cipher
11711364 · 2023-07-25 · ·

An authentication and encryption protocol is provided that can be implemented within a single clock cycle of an integrated circuit chip while still providing unbreakable encryption. The protocol of the present invention is so small that it can co-exist on any integrated circuit chip with other functions, including a general purpose central processing unit, general processing unit, or application specific integrated circuits with other communication related functionality.

DATA PROCESSING PERMITS SYSTEM WITH KEYS

Methods, systems, and devices for data processing are described. Some systems may support data processing permits and cryptographic techniques tying user consent to data handling. By tying user consent to data handling, the systems may comply with data regulations on a technical level and efficiently update to handle changing data regulations and/or regulations across different jurisdictions. For example, the system may maintain a set of data processing permits indicating user consent for the system to use a user's data for particular data processes. The system may encrypt the user's data using a cryptographic key (e.g., a cryptographic nonce) and may encrypt the nonce using permit keys for any permits applicable to that data. In this way, to access a user's data for a data process, the system may first verify that a relevant permit indicates that the user complies with the requested process prior to decrypting the user's data.

DYNAMIC ENCRYPTION AND DECRYPTION METHOD AMONG LOCK CONTROL SYSTEM MODULES, MULTIPLE AUTHENTICATION LOCK CONTROL SYSTEM, LOCK CONTROL METHOD AND STRONGBOX
20230006822 · 2023-01-05 ·

Dynamic encryption and decryption method among lock control system modules comprise the following steps: step 1. filling hardware ID data, an unlocking communication protocol and a mask variable into an array according to a predefined variable space, and encrypting the array based on the mask variable to obtain an encrypted array; step 2. decrypting the encrypted array based on the mask variable to obtain a decrypted array, executing data division on the decrypted array according to the predefined variable space, matching the divided data with data recorded in advance one by one, and if the divided data are consistent with the data recorded in advance, executing related operations according to the decrypted unlocking communication protocol content; otherwise, executing no operation.

MANAGING INFORMATION FOR MODEL TRAINING USING DISTRIBUTED BLOCKCHAIN LEDGER
20230004841 · 2023-01-05 ·

Embodiments are directed to generating and training a distributed machine learning model using data received from a plurality of third parties using a distributed ledger system, such as a blockchain. As each third party submits data suitable for model training, the data submissions are recorded onto the distributed ledger. By traversing the ledger, the learning platform identifies what data has been submitted and by which parties, and trains a model using the submitted data. Each party is also able to remove their data from the learning platform, which is also reflected in the distributed ledger. The distributed ledger thus maintains a record of which parties submitted data, and which parties removed their data from the learning platform, allowing for different third parties to contribute data for model training, while retaining control over their submitted data by being able to remove their data from the learning platform.