US 12,170,677 B2
Cybersecurity predictive detection using computer input device patterns
Bertrand Milot, Prevost (CA)
Assigned to BRADLEY & ROLLINS, Prevost (CA)
Filed by Bradley & Rollins, Prévost (CA)
Filed on Nov. 30, 2021, as Appl. No. 17/538,195.
Claims priority of provisional application 63/119,113, filed on Nov. 30, 2020.
Prior Publication US 2022/0174079 A1, Jun. 2, 2022
Int. Cl. H04L 9/40 (2022.01); G06N 20/00 (2019.01); H04L 9/32 (2006.01)
CPC H04L 63/1416 (2013.01) [G06N 20/00 (2019.01); H04L 9/3247 (2013.01); H04L 63/1425 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method for determining a risk of a cybersecurity event related to a user, the method executable by a system comprising a processor coupled to a first risk processing engine and a second risk processing engine, the system being communicatively coupled to a user device having peripheral devices configured to interact with a user, and a storage for storing a unique user profile and a digital identity,
the method comprising:
collecting, by the processor, an initial user-related data associated with user interactions, the user-related data comprising user-device interaction data generated in response to user interactions with the peripheral devices, user-network interaction data generated in response to user-network interactions, and user-resource interaction data generated in response to user-resource interactions;
determining, by the processor, the unique user profile and generating the digital identity of the user based on the initial user-related data;
collecting, by the first risk processing engine, in real time and repeatedly, a real-time user-related data associated with real-time user interactions during a first period of time, and detecting, by the first risk processing engine, an anomaly in user's behavior based on the collected real-time user-related data and the digital identity of the user;
collecting, by the second risk processing engine, a complementary data associated with the user and determining a cartography of a risk profile of the user based on the complementary data, the complementary data comprising neuroscience testing results of a neuroscience exercise performed by the user, a dark web data, and a digital exposure data; and
determining, by the second risk processing engine, the risk of the cybersecurity event based on the anomaly in the user's behavior in combination with neuroscience testing results, a value of the risk of victimization determined based on the dark web data and a value of a digital exposure risk determined based on the digital exposure data, in real-time over a complete period of use of resources, and updating the unique user profile and the digital identity of the user based on the anomaly in user's behavior and the risk of the cybersecurity event,
wherein the neuroscience testing results are collected by a neuroscience testing prior to determining the risk of the cybersecurity event.