Abstract: Systems, methods and products for providing a centralized view of media production devices connected to a network. An example method includes identifying a set of media production devices connected to a network and compiling a list of the identified devices. Network position information is then collected for the identified devices using resources including IS-04 device registries, LLDP tables, FDB tables and ARP tables. For each of the identified devices, a corresponding connection to the network is identified and corresponding network statistics are collected for each of the identified connections of the devices to the network, where the network statistics are correlated to the identified devices. A list of the identified devices is then stored in a searchable format with the corresponding network statistics, and particular ones of the devices may be highlighted to denote conditions indicated by the corresponding network statistics.

Abstract: Dynamically detecting abnormalities in otherwise legitimate emails containing Uniform Resource Locators (URLs) is provided. An example method includes determining one or more rules defining normal patterns in a number of sending Top-Level Domains of previously received emails received via a computer network to a user or group of users; generating a trusted trends criteria for a received email, associated with the user or the group of users, by evaluating the received email against the one or more rules; determining whether the trusted trends criteria exceeds a predetermined threshold; in response to exceeding the predetermined threshold, generating a second URL and applying it to the received email by replacing a first URL of the received email with the second URL; and redetermining the one or more rules defining normal patterns in the number of sending Top-Level Domains based on the previously received emails and the received email.

Abstract: A method for filtering unsolicited emails may comprise dynamically aggregating historical email data associated with a user or a group of users and dynamically determining one or more trusted trends criteria associated with the historical email data. The method may further comprise receiving a new email addressed to the user or the group of users, calculating a score associated with the new email based on the one or more trusted trends criteria, determining that the score is above a predetermined threshold score, and, based on the determination, selectively filtering the new email.

Abstract: A method for filtering unsolicited emails may comprise dynamically aggregating historical email data associated with a user or a group of users and dynamically determining one or more trusted trends criteria associated with the historical email data. The method may further comprise receiving a new email addressed to the user or the group of users, calculating a score associated with the new email based on the one or more trusted trends criteria, determining that the score is above a predetermined threshold score, and, based on the determination, selectively filtering the new email.