MS Morgan Stanley Dashboard

A system for detecting and responding to an anomaly in a chaotic environment, comprising one or more autonomous agent devices and a central server comprising a processor and non-transitory memory.

A system for executing software, wherein a computing device stores first software instructions for a code execution module such that, when the first software instructions are executed, the computing device will: receive, for execution by the code execution module, second software instructions; create one or more immutable software nodes described in the second software instructions; determine that the second software instructions comprise an instruction to begin a simulated change at runtime of the one or more immutable software nodes; store the simulated change in a simulated change apparatus; using the simulated change apparatus, perform one or more operations of the second software instructions as if the one or more immutable software nodes had been changed in memory, during a period of time where each of the one or more immutable software nodes is guaranteed to retain logical immutability; and output results of the one or more operations.

A computer-implemented method for collecting files transmitted on a network for subsequent malware analysis is disclosed.

A method of detecting and responding to anomalous activity within a system involves, based upon pivot feature information, for a snapshot interval, generating a frequency structure interrelating a pivot feature, a binning feature and counts, using the frequency structure, generating a graphical image of a pre-specified width and height in pixels, and wherein the pre-specified width corresponds to a cyclical repeating interval made up of multiple bins, the graphical image having been generated such that a bin of the multiple bins, is the bin having a highest count, and the bin is scaled to the pre-specified height, and counts of all other bins in the interval are scaled relative to that highest count, graphically comparing the generated graphical image to an immediately preceding graphical image for similarity, and if a result of the comparison fails to satisfy a pre-specified similarity threshold, automatically triggering an appropriate anomaly detection-based follow-on action.

Efficient, reusable, extensible light weight framework orchestrates discrete mainframe service calls as a single composite service call.