A system for automatic collection and analysis of digital forensic evidence by a cloud service provider is disclosed. The system utilizes machine learning models to identify and store digital forensic evidence relating to cybercrimes committed using a cloud service. Particularly, if an image or video file uploaded to the cloud service provider is determined to relate to illicit, illegal, or malicious activity, relevant digital forensic evidence is extracted and stored for later provision to law enforcement. The digital forensic evidence that is collected may be used to assist law enforcement in their investigations of criminal activity, as well as aid in the successful prosecution of criminals in court proceedings.

Methods and devices overcome the issue caused when target’s location is not known at the beginning of a location dependent interception thereby being not possible to determine whether the target is in a law enforcement’s agency jurisdiction. The network operator delivers lawful interception data encrypted to the law enforcement agency and provides the decryption information when jurisdiction is confirmed.

A system may be configured to: obtain one or more attributes of an RF environment of a user device; detect that the user device is neither associated with any AP nor authenticated; after the detection, stimulating the user device to be associated with at least one AP and authenticated to respond to an RTS PDU with a CTS PDU; receive the CTS PDU; and after the reception, adjust an RF link with which the user device is currently connected to operate at one or more different frequencies.

A server computing device configured to receive, via an anonymization network and from a first mobile computing device that determines a location from a set of locations of the first mobile computing device is within a threshold distance of an event, a proximity indication that a first user associated with the first mobile computing device is proximate to the event; in response to receiving an indication of a remittance for the event from a second user, generate an association between the remittance and the event; in response to receiving descriptive data that is descriptive of the event, send the descriptive data to a second mobile computing device of the second user; and in response to receiving an indication to release the remittance, send a message that executes a transaction that transfers at least a portion of the amount of the remittance to an account associated with the first user.

A server computing device configured to receive, via an anonymization network and from a first mobile computing device that determines a location from a set of locations of the first mobile computing device is within a threshold distance of an event, a proximity indication that a first user associated with the first mobile computing device is proximate to the event; in response to receiving an indication of a remittance for the event from a second user, generate an association between the remittance and the event; in response to receiving descriptive data that is descriptive of the event, send the descriptive data to a second mobile computing device of the second user; and in response to receiving an indication to release the remittance, send a message that executes a transaction that transfers at least a portion of the amount of the remittance to an account associated with the first user.

The disclosed computer-implemented method for protecting users may include (i) identifying a first light-and-radio frequency signature that was captured by a security device based on signals emanating from a mobile computing device at a first time and location, (ii) identifying a second light-and-radio frequency signature that was captured by a same or different security device based on signals emanating from the same mobile computing device at a second time and location, (iii) determining that the first light-and-radio frequency signature and the second light-and-radio frequency signature match such that an inference is made that an individual possessing the mobile computing device was present at both the first time and location and the second time and location, and (iv) performing, based on the inference, a security action to protect a user. Various other methods, systems, and computer-readable media are also disclosed.

The embodiments disclose a method including creating a live time connection platform for providing users with live time connection application purposes including augmented reality, users logged into the live time connection application earn from a group of compensation forms comprising cryptocurrency, fiat money, credit, and award for their participation on the application per unit of time, users logged into the live time connection application earn to access saved data including at least one from a group of videos, GIFs, texts, blogs, pictures, feeds, multisensory experiences, and other content, users using earnings make purchases from advertisers at an on-line store, using digital devices to login to the live time connection application, providing security to look for key words from user reported connection abuses, flagging abusers and reporting to police where appropriate, and providing geo advertising facilitates users choosing targeted advertising according to their interests and demographics from advertisers in their location.

In particular embodiments, a Cross-Border Visualization Generation System is configured to: (1) identify one or more data assets associated with a particular entity; (2) analyze the one or more data assets to identify one or more data elements stored in the identified one or more data assets; (3) define a plurality of physical locations and identify, for each of the identified one or more data assets, a respective particular physical location of the plurality of physical locations; (4) analyze the identified one or more data elements to determine one or more data transfers between the one or more data systems in different particular physical locations; (5) determine one or more regulations that relate to the one or more data transfers; and (6) generate a visual representation of the one or more data transfers based at least in part on the one or more regulations.

Disclosed are various embodiments providing automated management of security operations centers. In one embodiment, a correlation and decision engine correlates event data generated by a plurality of monitoring services with a plurality of alerts generated by a plurality of threat intelligence services. The engine then adjusts at least one rule of one or more threat intelligence services with respect to at least one event based at least in part on a corresponding frequency of at least one of the plurality of alerts meeting a threshold, where the adjusted alert(s) are associated with the event(s).

A method, computer program product, and computer system for applying a firewall security layer to software for hardware interface. Sensor data imported by the hardware interface may be secured using the firewall security layer. The sensor data may be provided to an artificial intelligence (AI) expert system. The sensor data provided to the AI expert system may be analyzed. An indication of an insecure condition may be provided via a user interface based upon, at least in part, analysis of the sensor data.