US 12,314,821 B2
Techniques for actively identifying parameters of computing interfaces based on requests and for active testing using such parameters
Netanel Maman, Mazkeret Batya (IL); Samuel Elgozi, Gan Yavne (IL); Tomer Semo, Tel Aviv-Jaffa (IL); Tomer Roizman, Tel Aviv-Jaffa (IL); and Ofir Manzur, Tel Aviv-Jaffa (IL)
Assigned to Akamai Technologies, Inc., Cambridge, MA (US)
Filed by Akamai Technologies, Inc., Cambridge, MA (US)
Filed on May 3, 2022, as Appl. No. 17/661,821.
Prior Publication US 2023/0359924 A1, Nov. 9, 2023
Int. Cl. G06F 21/00 (2013.01); G06F 9/54 (2006.01); G06F 21/57 (2013.01); G06N 20/00 (2019.01)
CPC G06N 20/00 (2019.01) [G06F 9/543 (2013.01); G06F 21/577 (2013.01); G06F 2221/034 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A method for active parameter identification, comprising:
applying a machine learning model to features extracted from each of at least one request to a computing interface, wherein the machine learning model is trained per value using a training set including a plurality of training values of a plurality of training requests, wherein the machine learning model is trained to output an indicator as to whether each portion of a request containing a respective value indicates a parameter when applied to the request; and
identifying at least one parameter-indicating portion of each request to the computing interface based on outputs of the machine learning model.