Invention Grant
- Patent Title: Systems and methods configuring a unified threat machine learning model for joint content and user threat detection
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Application No.: US17347653Application Date: 2021-06-15
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Publication No.: US11303665B2Publication Date: 2022-04-12
- Inventor: Wei Liu , Fred Sadaghiani
- Applicant: Sift Science, Inc.
- Applicant Address: US CA San Francisco
- Assignee: Sift Science, Inc.
- Current Assignee: Sift Science, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Alee PLLC
- Agent Padowithz Aice; Chandler Scheitlin
- Main IPC: H04L9/40
- IPC: H04L9/40 ; H04L29/06 ; G06N5/04 ; G06N20/00

Abstract:
A machine learning-based system and method for identifying digital threats includes a threat service that: implements a unified threat model that produces a unified threat score that predicts both of: a level of threat of a piece of online content, and a level of threat that a target user will create a harmful piece of online content; wherein: implementing the unified threat model includes: receiving event data comprising historical content data for the target user and content data of the pending piece of online content and historical user digital activity data and real-time user activity data; and providing input of content feature data and user digital activity feature data to the unified threat model; and the unified threat model produces the unified threat score based on the content and the user digital activity data; and computes a threat mitigation action based on an evaluation of the threat score.
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