Invention Application
- Patent Title: ADVERSARIAL ATTACK PREVENTION AND MALWARE DETECTION SYSTEM
-
Application No.: US15700489Application Date: 2017-09-11
-
Publication No.: US20190080089A1Publication Date: 2019-03-14
- Inventor: Li Chen
- Applicant: Intel Corporation
- Main IPC: G06F21/56
- IPC: G06F21/56 ; G06N99/00

Abstract:
Systems and methods may be used to classify incoming testing data, such as binaries, function calls, an application package, or the like, to determine whether the testing data is contaminated using an adversarial attack or benign while training a machine learning system to detect malware. A method may include using a sparse coding technique or a semi-supervised learning technique to classify the testing data. Training data may be used to represent the testing data using the sparse coding technique or to train the supervised portion of the semi-supervised learning technique.
Public/Granted literature
- US10733294B2 Adversarial attack prevention and malware detection system Public/Granted day:2020-08-04
Information query