Invention Grant
- Patent Title: Continuous malicious software identification through responsive machine learning
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Application No.: US15853795Application Date: 2017-12-23
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Publication No.: US10078752B2Publication Date: 2018-09-18
- Inventor: Ryan J. Berg , John J. Danahy , Kirk R. Swidowski , Stephen C. Carlucci , Christopher Baron
- Applicant: Barkly Protects, Inc.
- Applicant Address: US MA Boston
- Assignee: BARKLY PROTECTS, INC.
- Current Assignee: BARKLY PROTECTS, INC.
- Current Assignee Address: US MA Boston
- Agency: Davis, Malm & D'Agostine, P.C.
- Main IPC: G06F21/53
- IPC: G06F21/53 ; G06F21/56 ; G06F21/55 ; G06F9/455 ; H04L29/06 ; G06N99/00

Abstract:
A security system and method secures and responds to security threats in a computer having a CPU, a Kernel/OS, and software applications. A low-level data collector intercepts a selection of first tier calls between the CPU and Kernel/OS, and stores associated first tier call IDs. A Kernel module intercepts a selection of second tier calls between applications and the Kernel/OS, and stores associated second tier call IDs. An Analytic Engine maps the stored first and second tier call IDs to a rulebase containing patterns of security threats, to generate a threat analysis, and then responds to the threat analysis. The Analytic Engine enlarges or contracts the selection of first and second tier calls to increase or decrease specificity of the threat analysis. A Management Module generates user interfaces accessible remotely by a user device, to update the rulebase and configure the low-level collector, the Kernel module, and the Analytic Engine.
Public/Granted literature
- US20180189484A1 Continuous Malicious Software Identification Through Responsive Machine Learning Public/Granted day:2018-07-05
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