-
公开(公告)号：US20170185386A1
公开(公告)日：2017-06-29
申请号：US14998274
申请日：2015-12-26
IPC分类号： G06F9/45
摘要： 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：US20180189489A1
公开(公告)日：2018-07-05
申请号：US15395053
申请日：2016-12-30
申请人： Mingwei Zhang , Xiaoning Li , Ravi L. Sahita , Aravind Subramanian , Abhay S. Kanhere , Chih-Yuan Yang , Yi Gai
发明人： Mingwei Zhang , Xiaoning Li , Ravi L. Sahita , Aravind Subramanian , Abhay S. Kanhere , Chih-Yuan Yang , Yi Gai
摘要： 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.
-
搜索结果
2 条记录 (耗时 0.018 秒)
