COMPUTER SOFTWARE WHICH MONITORS

Brand	Owner (click to sort)	Address	Description
@MAX	Honeywell International Inc.	855 S. Mint Street Charlotte NC 28202	COMPUTER SOFTWARE WHICH MONITORS, ANALYZES, SIGNALS AND DIAGNOSES EQUIPMENT IN PROCESS AUTOMATION, BUILDING CONTROL, SPACE, AVIATION AND TRANSPORTATION INDUSTRIES; HARDWARE CONSISTING OF RADIOS, ANTENNAS, GLOBAL SATELLITE TELEPHONES AND PAGERS, ALL FOR USE IN THE PROCESS AUTOMATION, BUILDING CONTROL, SPACE, AVIATION AND TRANSPORTATION INDUSTRIES;AT MAX;
HQ MONITOR	Health Quality Inc.	500 Boylston Street, Suite 550 Boston MA 02116	Computer software which monitors the quality of medical care and manages patient information;MONITOR;
PERFMAN 2020	ASG TECHNOLOGIES GROUP, INC.	77 4th Ave. Waltham MA 02451	Computer software which monitors, analyzes and manages information technology infrastructure by collecting, analyzing and reporting technology infrastructure performance and use data; Computer software which monitors, analyzes and manages information technology infrastructure by collecting, analyzing and reporting technology infrastructure performance and use data in real time over the Internet and on hand-held devices;
THE ARGENT DEFENDER	ARGENT SOFTWARE GROUP, INC.	2 BRIDGEWATER ROAD FARMINGTON CT 06032	Computer software which monitors, simulates and tests the capacity of websites and advises the operator of the website when traffic to the website changes;
VM:DB/MONITOR	STERLING SOFTWARE, INC.	300 Crescent Court, Suite 1200 Dallas TX 75201	computer software which monitors and reports on database performance and printed instructional manuals, therefor, sold as a unit;
	Where the owner name is not linked, that owner no longer owns the brand

Technical Examples

An intrusion detection system (IDS) that uses application monitors for detecting application-based attacks against computer systems. The IDS implements application monitors in the form of a software program to learn and monitor the behavior of system programs in order to detect attacks against computer hosts. The application monitors implement machine learning algorithms to provide a mechanism for learning from previously observed behavior in order to recognize future attacks that it has not seen before. The application monitors include temporal locality algorithms to increased the accuracy of the IDS. The IDS of the present invention may comprise a string-matching program, a neural network, or a time series prediction algorithm for learning normal application behavior and for detecting anomalies.