An information processing program causes a computer to execute a process including: specifying, from an image that is captured by a camera, a person and a plurality of objects, generating, by inputting the image of the person into a machine learning model, skeleton information on the person, identifying, based on the plurality of objects and the skeleton information, a first feature value associated with one or more first motions of the person who retrieves an object from among the plurality of objects, identifying a second feature value associated with one or more objects registered to a first terminal by the person from among the plurality of object, and generating, based on a difference between the first feature value and the second feature value, an alert indicates that an object retrieved by the person is not registered in the first terminal.

Supply chain factoring utilizing shared state information stored in a distributed ledger includes the selection of an electronic supply chain document associated with an order for goods by a purchaser of the goods and the minting of a cryptographic token on behalf of a seller of the goods. the token encapsulating a purchase price for the order and associated order terms. A location is reserved in the ledger into which the token is uploaded. Subsequently, factoring terms are published at the reserved location by a factoring agency supporting the factorization of the purchase price. The seller then validates an ascension to the factoring terms in the reserved location. Finally, the reserved location is annotated to indicate satisfaction of the factoring terms upon the purchase price being paid to the factoring agency and a fraction of the purchase price being paid by the factoring agency to the seller of goods.

Described herein are systems and methods for generating security event case files with unstructured data. For example, the method can include receiving, by a computing system, unstructured data and system-based inferences from devices positioned throughout a store, and adding structure to the unstructured data and system-based inferences based on applying one or more structuring models. Adding structure can include labeling the data and system-based inferences, classifying them into security event categories, and identifying objective identifiers to identify users in the data and system-based inferences. The method also can include generating case files for each of the objective identifiers, where the case files include the associated data. The method can include determining whether the case files satisfy alerting rules. The case files can then be reported out and acted upon (e.g., based on satisfying the alerting rules) and/or stored for subsequent analysis and use.

In an embodiment, a computer stores a bipartite graph that consists of a source subgraph and a target subgraph. Each vertex in the bipartite graph represents an entity. The source subgraph and the target subgraph are connected by many similarity edges. Each similarity edge indicates an original amount of similarity between the entity of a source vertex in the source subgraph and the entity of a target vertex in the target subgraph. For each similarity edge, the computer determines: a set of neighbor source vertices that are reachable from the source vertex of the similarity edge by traversing at most a source radius count of source edges in the source subgraph, a set of neighbor target vertices that are reachable from the target vertex of the similarity edge by traversing at most a target radius count of target edges in the target subgraph, and various amounts based on graph topology. For each similarity edge, the computer calculates a new amount of similarity based on those various amounts.

A system and its methods are described for implementing meta-transactional interactions across one or more decentralized computing networks (“blockchains”) with a managed (“custodial”) wallet, satisfying an important need of lowering the barrier of entry for interacting with smart contracts across multiple blockchain networks. First, the method of encoding and storing a transactional request created by a user's managed account, representing an intention to broadcast the invocation of a specific function of a specific smart contract on one or more peer nodes of a specific blockchain. Then, calculating a cost for processing the encoded transaction within the specific blockchain via analysis including the value and type of cryptocurrency, complexity of transaction, historical trend of transaction fees, and analyses to eliminate the chance of loss due to insufficient transaction fees. Next, obtaining a payment from the user for the transfer of the amount to successfully process their queued transaction. Then, confirming the payment was received in its correct and sufficient form resulting in a transfer of cryptocurrency from a reserve to the user's managed account. Subsequently, determining the transfer is completed and a sufficient balance exists for the execution of the queued transaction. Finally, dequeuing and executing the stored transaction on a specific blockchain by the system on behalf of the managed account, where transaction fees are paid by the managed account and unspent fees are accrued in the balances of the managed wallet.

There are provided systems and methods for a dynamic value appended to cookie data for fraud detection and step-up authentication. A service provider, such as an electronic transaction processor for digital transactions, may utilize computer cookies for authentication and/or login for a user account. In order to further secure cookies from being compromised and used by malicious parties for fraudulent account access, the service provider may add or append a dynamic value that changes at each subsequent login to the computer cookie. The dynamic value may be used so that if a computer cookie is misappropriated, only one device may use the cookie once without the cookie updating and invalidating the cookie with another device or application on the device. Thereafter, when a login is requested, the dynamic value is matched to an expected value by the service provider when determining whether to authenticate the device.

A plurality of bank identification number (BIN) ranges are characterized according to credit risk. A list of the plurality of bank identification number (BIN) ranges characterized by credit risk is made available to a transit-specific payment network interface processor, which is coupled to a plurality of memory-constrained fare gates of a transit authority. The list is configured to be distributed to the memory-constrained fare gates of the transit authority. Advantageously, the list based on BIN ranges takes up less memory than a list based on individual account numbers or the like and can be maintained in memory at the memory-constrained fare gates for rapid decisioning.

Example methods, apparatuses, and systems are presented that allows a consumer to conduct a purchase backed by a volatile currency that is not recognized by a merchant as a valid form of payment, such as a cryptocurrency. A third-party payment system is configured to issue a secure, reliable token to replace a reserved amount of volatile currency that represents a reliable amount of currency that is recognized by the merchant as a valid form of payment. The third-party payment platform may issue the reliable amount of currency in the reliable token based on one or more risk factors associated with the volatile currency. After purchase, the third-party payment platform may perform a consumer settlement process at a later time, including performing a cryptocurrency blockchain verification process that typically takes at least several minutes and would be impractical to perform at the point of sale.

An apparatus for storing a set of events, is provided, the apparatus comprising one or more circuitry configured to: receive an electronic message comprising information of a first event between a first party and a second party, the first event being initiated by the first party; determine whether a record of the first event exists in a first storage unit; wherein when it is determined that the record of the first event does not exist, the one or more circuitry is configured to: determine whether any subsequent events between the second party and a third party are initiated by the second party within a predetermined time of the first event; and store an association between the second party and a first set of events, the first set of events comprising the first event and the subsequent event, in a second storage unit, when the subsequent event is initiated within the predetermined time.

Cryptocurrency based malware and ransomware detection systems and methods are disclosed herein. An example method includes analyzing a plurality of malware or ransomware attacks to determine cryptocurrency payment address of malware or ransomware attacks, building a malware or ransomware attack database with the cryptocurrency payment addresses of the plurality of malware or ransomware attacks, identifying a proposed cryptocurrency transaction that includes an address that is included in the malware or ransomware attack database, and denying the proposed cryptocurrency transaction.