21CT, INC. Patent applications |
Patent application number | Title | Published |
20150229662 | METHOD AND APPARATUS FOR IDENTIFYING A THREATENING NETWORK - A system and method for identifying a threatening network is provided. The system comprises a network movement before/after algorithm that provides a graphical plot of changes in networks' communications activity from before to after a key event occurs, so that an analyst is able to identify anomalous behavior; a network progression algorithm that provides a graphical plot to analyze behavior in small increments of time without specification or emphasis upon a particular event, so that the analyst is able to see a trend in behavioral changes; a statistical network anomaly ranking algorithm that provides as output a ranked list of the networks; and an anomaly trend graphs algorithm that analyzes and visualizes the networks' anomaly scores over time, so that the analyst is able to see which networks are consistently suspicious, which networks accumulate more suspiciousness in response to an event, and which networks are trending toward more suspiciousness. | 08-13-2015 |
20130226893 | SYSTEM AND METHOD FOR OPTIMIZING PATTERN QUERY SEARCHES ON A GRAPH DATABASE - An embodiment of the system and method for optimizing pattern query searches on a graph database uses a pattern query optimizer to optimize execution of the search plan for any sequence of SQL expressions by separating or breaking a pattern query into multiple subpattern queries before converting the subpattern queries into SQL expressions. An embodiment of the pattern query optimizer algorithmically, without intervention by an analyst, decomposes any pattern query into a set of subpattern queries by first identifying branches and cycles within a pattern query and then decomposing each identified branch and cycle into equivalent straight line paths, i.e., straight line nodes joined by edges. Cardinality may be used to improve the performance of pattern searches. | 08-29-2013 |
20130055404 | System And Method For Providing Impact Modeling And Prediction Of Attacks On Cyber Targets - Embodiments of a system and method are disclosed to provide impact modeling and prediction of attacks on cyber targets (IMPACT). An embodiment of the system and method creates a network model to describe the IT resources of an organization, creates a business model to describe the origination's mission, and creates a correlation model that correlates the network model and the business model to describe how the origination's mission relies on the IT resources. Proper analysis may show which cyber resources are of tactical importance in a cyber attack. Such analysis also reveals which IT resources contribute most to the organization's mission. These results may then be used to formulate IT security strategies and explore their trade-offs, which leads to better incident response. | 02-28-2013 |
20110225158 | Method and System for Abstracting Information for Use in Link Analysis - Observable data points are collected and organized into a link-oriented data set comprising nodes and links. Information is abstracted for use in link analysis by generating links between the collected data points, including deriving links and inducing links. A link can be induced by linking together a pair of nodes that satisfy a distance function. Exemplary distance functions that can be used to induce links include geo spatial proximity, attribute nearness, and name similarity. Paths can be identified between selected nodes of interest through a dataset operation, and nodes and/or links can be selectively included or excluded from the data set operation. The dataset can be augmented with pedigree information or one or more association nodes. Link information, including a trajectory and a connected path that selectively produces or excludes one or more intermediate nodes, can be displayed and/or produced in a specified format. | 09-15-2011 |
20110208521 | Hidden Markov Model for Speech Processing with Training Method - A method, system and apparatus are shown for identifying non-language speech sounds in a speech or audio signal. An audio signal is segmented and feature vectors are extracted from the segments of the audio signal. The segment is classified using a hidden Markov model (HMM) that has been trained on sequences of these feature vectors. Post-processing components can be utilized to enhance classification. An embodiment is described in which the hidden Markov model is used to classify a segment as a language speech sound or one of a variety of non-language speech sounds. Another embodiment is described in which the hidden Markov model is trained using discriminative learning. | 08-25-2011 |