Systems and methods for detecting anomalies in siloed networks
AssigneeDark Watch
InventorsNoel Thomas, James Snay
Life of this patent
Estimating the term…
Abstract
Systems and methods for uses and/or improvements to data scraping and/or data collection applications. As one example, systems and methods for web scraping applications that overcome multi-layered encryptions, content nesting, and/or other techniques for frustrating web scraping systems. For example, some websites, particularly those used in human trafficking, fraud, and/or other criminal enterprises, employ various encryption and/or encoding techniques to obstruct and frustrate web scraping systems, aiming to hide their data.
Claims20
A system for detecting anomalies in siloed networks featuring extreme signal-to-noise imbalances using point-of-contact based filtering criteria for data processing and data retrieval the system comprising:
- one or more processors;
- and one or more non-transitory, computer-readable mediums comprising instructions that when executed by the one or more processors cause operations comprising:
- receiving, via a user terminal, point-of-contact data at a first location, wherein the first location corresponds to a first geographic position and a first location type;
- selecting a potential threat vector from a plurality of potential threat vectors for the first location, wherein the potential threat vector has an initial severity characteristic calculated based on the first geographic position and the first location type;
- calculating a point-of-contact characteristic in the point-of-contact data;
- based on the point-of-contact characteristic, selecting one or more processing routines, from a plurality of processing routines, or one or more data retrieval routines, from a plurality of data retrieval routines, for the point-of-contact data;
- processing the point-of-contact data using the one or more processing routines or the one or more data retrieval routines to generate one or more outputs;
- generating a final severity characteristic for the potential threat vector by modifying the initial severity characteristic by weighting the one or more outputs;
- and generating for display, at the user terminal, a dynamic threat identifier for the potential threat vector, wherein the dynamic threat identifier is generated for display with the final severity characteristic.
A method for detecting anomalies in siloed networks featuring extreme signal-to-noise imbalances using point-of-contact based filtering criteria for data processing and data retrieval, the method comprising:receiving point-of-contact data at a first location;calculating a potential threat vector based on the first location, wherein the potential threat vector has a first characteristic;calculating a point-of-contact characteristic in the point-of-contact data;based on the point-of-contact characteristic, selecting a first processing routine, from a plurality of processing routines, or a first data retrieval routine, from a plurality of data retrieval routines, for the point-of-contact data;processing the point-of-contact data using the first processing routine or the first data retrieval routine;generating a second characteristic for the potential threat vector by modifying the first characteristic based on processing the point-of-contact data using the first processing routine or the first data retrieval routine;
- andgenerating for display, on a user interface, the potential threat vector with the second characteristic.
One or more non-transitory, computer-readable media comprising instructions that when executed by one or more processors cause operations comprising:
- receiving point-of-contact data at a first location;
- calculating a point-of-contact characteristic in the point-of-contact data;
- based on the point-of-contact characteristic, selecting a first processing routine, from a plurality of processing routines, or a first data retrieval routine, from a plurality of data retrieval routines, for the point-of-contact data;
- processing the point-of-contact data using the first processing routine or the first data retrieval routine;
- calculating a dynamic threat identifier for a potential threat vector based on processing the point-of-contact data using the first processing routine or the first data retrieval routine;
- and generating for display, on a user interface, the dynamic threat identifier for the potential threat vector.
Dependencies are inferred from the claim text.