公开(公告)号：US09910646B2

公开(公告)日：2018-03-06

申请号：US14998274

申请日：2015-12-26

Applicant: Intel Corporation

Inventor： Abhay S. Kanhere ,  Haitao Feng ,  Paul H Hohensee ,  Aravind Subramanian

IPC: G06F9/45

CPC classification number: G06F8/433 ,  G06F8/53

Abstract: Technologies for native code invocation using binary analysis are described. A computing device for invoking native code from managed code using binary analysis receives a call from a thread executing a managed code segment to execute a native code segment. The computing device performs a binary analysis of the native code segment and generates, from the binary analysis, a complexity indicator that indicates a level of complexity of the native code segment by comparing the native code segment to at least one predefined complexity rule. Additionally, the computing device stores a status of the thread based on the complexity indicator and executes the native code segment. Other embodiments are described and claimed.

公开(公告)号：US20200175166A1

公开(公告)日：2020-06-04

申请号：US16780218

申请日：2020-02-03

Applicant: Intel Corporation

Inventor： Mingwei Zhang ,  Xiaoning Li ,  Ravi L. Sahita ,  Aravind Subramanian ,  Abhay S. Kanhere ,  Chih-Yuan Yang ,  Yi Gai

IPC: G06F21/56 ,  G06N20/00 ,  H04L29/06

Abstract: A malicious object detection system for use in managed runtime environments includes a check circuit to receive call information generated by an application, such as an Android application. A machine learning circuit coupled to the check circuit applies a machine learning model to assess the information and/or data included in the call and detect the presence of a malicious object, such as malware or a virus, in the application generating the call. The machine learning model may include a global machine learning model distributed across a number of devices, a local machine learning model based on use patterns of a particular device, or combinations thereof. A graphical user interface management circuit halts execution of applications containing malicious objects and generates a user perceptible output.

公开(公告)号：US11568051B2

公开(公告)日：2023-01-31

申请号：US16780218

申请日：2020-02-03

Applicant: Intel Corporation

Inventor： Mingwei Zhang ,  Xiaoning Li ,  Ravi L. Sahita ,  Aravind Subramanian ,  Abhay S. Kanhere ,  Chih-Yuan Yang ,  Yi Gai

IPC: G06F21/56 ,  G06N20/00 ,  H04L29/06 ,  H04L9/40

Abstract: A malicious object detection system for use in managed runtime environments includes a check circuit to receive call information generated by an application, such as an Android application. A machine learning circuit coupled to the check circuit applies a machine learning model to assess the information and/or data included in the call and detect the presence of a malicious object, such as malware or a virus, in the application generating the call. The machine learning model may include a global machine learning model distributed across a number of devices, a local machine learning model based on use patterns of a particular device, or combinations thereof. A graphical user interface management circuit halts execution of applications containing malicious objects and generates a user perceptible output.

公开(公告)号：US10552609B2

公开(公告)日：2020-02-04

申请号：US15395053

申请日：2016-12-30

Applicant: INTEL CORPORATION

Inventor： Mingwei Zhang ,  Xiaoning Li ,  Ravi L. Sahita ,  Aravind Subramanian ,  Abhay S. Kanhere ,  Chih-Yuan Yang ,  Yi Gai

IPC: G06F21/56 ,  H04L29/06 ,  G06N99/00 ,  G06N20/00

Abstract: A malicious object detection system for use in managed runtime environments includes a check circuit to receive call information generated by an application, such as an Android application. A machine learning circuit coupled to the check circuit applies a machine learning model to assess the information and/or data included in the call and detect the presence of a malicious object, such as malware or a virus, in the application generating the call. The machine learning model may include a global machine learning model distributed across a number of devices, a local machine learning model based on use patterns of a particular device, or combinations thereof. A graphical user interface management circuit halts execution of applications containing malicious objects and generates a user perceptible output.