Machine learning adversarial campaign mitigation on a computing device. The method may include deploying an original machine learning model in a model environment associated with a client device; deploying a classification monitor in the model environment to monitor classification decision outputs in the machine learning model; detecting, by the classification monitor, a campaign of adversarial classification decision outputs in the machine learning model; applying a transformation function to the machine learning model in the model environment to transform the adversarial classification decision outputs to thwart the campaign of adversarial classification decision outputs; determining a malicious attack on the client device based in part on detecting the campaign of adversarial classification decision outputs; and implementing a security action to protect the computing device against the malicious attack.

The systems and methods disclosed herein comprise computer-based platforms configured for automated early-stage application security monitoring for allowing users (e.g., application developers) to make decisions at the early stage of the application development.

The present disclosure generally relates to managing access to credentials. In some examples, an electronic device authorizes release of credentials for use in an operation for which authorization is required. In some examples, an electronic device causes display of one or more steps to be taken to enable an input device for user input. In some examples, an electronic device disambiguates between commands to change the account that is actively logged-in on the device and commands to cause credentials to be released from the secure element.

A system and method for authenticating users of a digital device includes an authentication device attached to an authorized user. The authentication device includes one or more motion sensors and acts as a user identity token. To authenticate with a digital device, the user performs one or more interactions with the digital device using the hand associated with the authentication device. The digital device correlates the inputs received due to the interactions with the user's hand and/or wrist movement, as measured by the authentication device. Access to the digital device is allowed if the inputs and movements are correlated.

Systems and methods of improving the operation of a transaction network and transaction network devices are disclosed. An online purchase autofill plugin includes various modules and engines. The fields of online forms may be identified and the fields of online forms may be automatically filled. The user experience may be improved, and data security enhanced so that the transaction network more properly functions according to approved parameters, such as protecting the integrity of sensitive data.

Price mining and dynamic online marketing campaign adjustment data processing systems and methods are disclosed. A system and method for dynamically adjusting an online marketing campaign, in various embodiments, is configured to increase and/or decrease one or more keyword bids that make up part of an online marketing campaign for a particular product from a particular retailer based on whether: (1) the particular product is or is not competitively priced relative to one or more competing retailers; and/or (2) an advertisement for the particular product from the particular retailer on a search engine results page or in an online marketplace is in a relatively desirable position.

Systems and methods to identify a software vulnerability are described. The system receives a message identifying a software vulnerability. The system identifies snapshot images taken of a production machine and stored in a database. The snapshot images include a snapshot image including a virtual machine. The snapshot images are identified being based on the message. The system identifies whether the snapshot images include the software vulnerability. The system registers the software vulnerability in association with a snapshot image in the database responsive to the identification of the snapshot image of the virtual machine including the software vulnerability.

A system, method, device, and platform for managing data. Data associated with a user received from one of a number of sources. The data is automatically confirmed as applicable to a user. The data is added to a data set associated with the user. A determination is made whether the data set is complete after adding the data to the data set. One or more tokens are created based on the data set of the user.

Systems and methods to detect malicious software include an application software repository including a stored header file associated with a driver, an executable, or both, and are operable to (i) receive a memory dump file upon an operating system crash including a driver copy, an executable copy, or both, (ii) verify the memory dump file is new for analysis, (iii) compress the verified memory dump file to generate a memory snapshot of the verified memory dump file, (iv) scan the memory snapshot for a memory dump header file associated with the driver copy, the executable copy, or both, and (v) identify and extract malicious software when the memory dump header file from the memory snapshot fails to match at least one stored header file in the application software repository.

A baseband processor of a communication device, the baseband processor comprising a multiple encryption manager that utilizes a transmit data stream as an input data stream in the case that the transmit data stream is determined not to already have encryption applied by a higher layer component, and that utilizes a known unencrypted dataset as an input data stream in the case that the transmit data stream is determined to already have encryption applied by a higher layer component, an encryptor block that encrypts the input data stream into an encrypted data stream, and a randomness inspector that is in communication with the encryptor block, the randomness inspector unit accessing the input data stream and the encrypted data stream from the encryptor block and determining a randomness gain by comparing a first randomness measurement associated with the input data stream to a second randomness measurement associated with the encrypted data stream.