US 12,388,870 B2
Systems and methods for intelligent identification and automated disposal of non-malicious electronic communications
Elisabeth Weber, Herndon, VA (US); and Jane Hung, Raleigh, NC (US)
Assigned to Expel, Inc., Herndon, VA (US)
Filed by Expel, Inc., Herndon, VA (US)
Filed on Sep. 13, 2024, as Appl. No. 18/885,207.
Application 18/885,207 is a continuation of application No. 18/607,463, filed on Mar. 16, 2024, granted, now 12,120,147.
Application 18/607,463 is a continuation in part of application No. 17/970,069, filed on Oct. 20, 2022, granted, now 12,107,886, issued on Oct. 1, 2024.
Application 17/970,069 is a continuation of application No. 17/696,151, filed on Mar. 16, 2022, granted, now 11,509,689, issued on Nov. 22, 2022.
Application 17/696,151 is a continuation of application No. 17/501,708, filed on Oct. 14, 2021, granted, now 11,310,270, issued on Apr. 19, 2022.
Claims priority of provisional application 63/463,195, filed on May 1, 2023.
Claims priority of provisional application 63/454,078, filed on Mar. 23, 2023.
Claims priority of provisional application 63/129,836, filed on Dec. 23, 2020.
Claims priority of provisional application 63/092,307, filed on Oct. 15, 2020.
Claims priority of provisional application 63/091,409, filed on Oct. 14, 2020.
Prior Publication US 2025/0088534 A1, Mar. 13, 2025
This patent is subject to a terminal disclaimer.
Int. Cl. H04L 9/40 (2022.01); G06N 20/00 (2019.01)
CPC H04L 63/1483 (2013.01) [G06N 20/00 (2019.01); H04L 63/1425 (2013.01); H04L 63/1433 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method comprising:
extracting one or more corpora of feature vectors from electronic communication data associated with an electronic communication, wherein extracting the one or more corpora of feature vectors includes:
(i) extracting a first corpus of feature vectors comprising feature data indicative of whether the electronic communication is of a target type, wherein:
the target type refers to a class of electronic communications that promotes one or more products, one or more services, or one or more events, and
(ii) extracting a second corpus of feature vectors comprising feature data indicative of whether the electronic communication is a malicious electronic communication;
computing, by an electronic communication classification model, a classification inference that includes a probability of the electronic communication being of the target type based on the electronic communication classification model receiving the first corpus of feature vectors and the second corpus of feature vectors; and
automatically closing a security alert associated with the electronic communication based on the probability satisfying a predetermined minimum classification threshold.