Disclosed herein is attack-less adversarial training for robust adversarial defense. The attack-less adversarial training for robust adversarial defense includes the steps of: (a) generating individual intervals (c.sub.i) by setting the range of color (C) and then discretizing the range of color (C) by a predetermined number (k); (b) generating one batch from an original image (X) and training a learning model with the batch; (c) predicting individual interval indices (ŷ.sub.i.sup.alat) from respective pixels (x.sub.i) of the original image (X) by using an activation function; (d) generating a new image (X.sup.alat) through mapping and randomization; and (e) training a convolutional neural network with the image (X.sup.alat) generated in step (d) and outputting a predicted label (Ŷ).

Disclosed herein is attack-less adversarial training for robust adversarial defense. The attack-less adversarial training for robust adversarial defense includes the steps of: (a) generating individual intervals (c.sub.i) by setting the range of color (C) and then discretizing the range of color (C) by a predetermined number (k); (b) generating one batch from an original image (X) and training a learning model with the batch; (c) predicting individual interval indices (ŷ.sub.i.sup.alat) from respective pixels (x.sub.i) of the original image (X) by using an activation function; (d) generating a new image (X.sup.alat) through mapping and randomization; and (e) training a convolutional neural network with the image (X.sup.alat) generated in step (d) and outputting a predicted label (Ŷ).

A system and method for storing and recovering a computer file. The method includes calculating fingerprint data of the file, separating the file into a plurality of data sub-files each having the same size and a single data sub-file having a smaller size than the other data sub-files, and attaching file metadata to the single data sub-file or as a metadata sub-file. The method also includes padding the single data sub-file including the metadata so that it is the same size as the plurality of data sub-files or the metadata sub-file so that it is the same size as the plurality of data sub-files, adding a header to each data sub-file that includes information about the sub-file, assigning a unique filename to each data sub-file, encrypting each data sub-file, and storing each data sub-file as separate files under their unique filename.

An example operation may include one or more of capturing a current version of sensitive data by a data processor node, hashing, by the data processor node, the current version of the sensitive data, storing, by the data processor node, a hash of the current version of the sensitive data on a first blockchain, encrypting, by the data processor node, the current version of the sensitive data using a secret key, and storing the encrypted current version of the sensitive data on a second blockchain.

A computer system is provided. The computer system includes a memory and a processor. The processor is configured to scan user interface (UI) data representative of a plurality of UI controls; detect a portion of the UI data associated with private information, the portion corresponding to a UI control of the plurality of UI controls; record first session data comprising an obfuscated version of the UI control and unobfuscated versions of other UI controls of the plurality of UI controls; record second session data comprising an unobfuscated version of the UI control; encrypt the second session data to generate encrypted session data; and store the encrypted session data in association with the first session data.

A device obtains previously created data content. The device unmasks and extracts one or more chain of custody blocks stored in association with the data content. The one or more chain of custody blocks includes chain of custody data identifying who, when, where, and, with what hardware and/or software, created or edited the data content. The device analyzes the one or more chain of custody blocks and validates an origination of the data content based on the analysis of the one or more chain of custody blocks.

A device obtains previously created data content. The device unmasks and extracts one or more chain of custody blocks stored in association with the data content. The one or more chain of custody blocks includes chain of custody data identifying who, when, where, and, with what hardware and/or software, created or edited the data content. The device analyzes the one or more chain of custody blocks and validates an origination of the data content based on the analysis of the one or more chain of custody blocks.

A method for preparing a credential package includes providing access to a credential record of a plurality of credential records stored in a database system. The credential record includes information identifying a credential candidate and credential information associated with the credential candidate. The method further comprising receiving a credential document associated with the credential information, receiving credential document information associated with the credential document, and storing the credential document in a distributed ledger system comprising a plurality of nodes.

Techniques for database and file management herein include a processor and a memory device storing instructions that cause the processor to perform operations comprising creating a request based on an extensible markup language (XML) or an interpreted scripting language object, wherein the request comprises unauthenticated data for validation. The operations can also include transmitting the request to a remote device), updating metadata corresponding to the request to indicate the successful validation by the remote device, validating a response file, and detecting a discrepancy between the unauthenticated data and the authenticated data accessible by the remote device. Additionally, the operations include obtaining correction data to resolve the discrepancy, and executing a transaction based on the request and the correction data.

A method and system for deployment of services for customers. Network service templates (NSTs) are determined, from a permissioned distributed ledger that is distributed between network operator systems of one or more network operators and customer systems. The NSTs include respective descriptions of network characteristics that provide respective logical networks. A subset of the NSTs and a corresponding subset of the network operator systems are selected based on a service description of the first service for deployment of the first service. Instantiation of the subset of the NSTs is requested on the corresponding subset of network operator systems as a subset of network slice instances to form the first service deployed for the first customer.