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公开(公告)号:US20070209073A1
公开(公告)日:2007-09-06
申请号:US11364359
申请日:2006-02-28
申请人: Karen Corby , Mark Alcazar , Viresh Ramdatmisier , Ariel Kirsman , Andre Needham , Akhilesh Kaza , Raja Krishnaswamy , Jeff Cooperstein , Charles Kaufman , Chris Anderson , Venkata Prasad , Aaron Goldfeder , John Hawkins
发明人: Karen Corby , Mark Alcazar , Viresh Ramdatmisier , Ariel Kirsman , Andre Needham , Akhilesh Kaza , Raja Krishnaswamy , Jeff Cooperstein , Charles Kaufman , Chris Anderson , Venkata Prasad , Aaron Goldfeder , John Hawkins
IPC分类号: G06F12/14
CPC分类号: G06F21/62 , G06F21/51 , G06F21/53 , G06F21/577
摘要: Described is a technology including an evaluation methodology by which a set of privileged code such as a platform's API method may be marked as being security critical and/or safe for being called by untrusted code. The set of code is evaluated to determine whether the code is security critical code, and if so, it is identified as security critical. Such code is further evaluated to determine whether the code is safe with respect to being called by untrusted code, and if so, is marked as safe. To determine whether the code is safe, a determination is made as to whether the first set of code leaks criticality, including by evaluating one or more code paths corresponding to one or more callers of the first set of code, and by evaluating one or more code paths corresponding to one or more callees of the first set of code.
摘要翻译: 描述了一种技术,其包括评估方法,通过该评估方法,可以将一组特权代码(例如平台的API方法)标记为由不受信任的代码调用的安全关键和/或安全。 评估代码集以确定代码是否是安全关键代码,如果是,则将其标识为安全关键。 进一步评估这些代码以确定代码是否对于被不受信任的代码调用是安全的,如果是,则将其标记为安全的。 为了确定代码是否安全,确定第一组代码是否泄漏关键性,包括通过评估与第一组代码的一个或多个调用者相对应的一个或多个代码路径,以及通过评估一个或多个 对应于第一组代码的一个或多个被调用者的代码路径。
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公开(公告)号:US20220086466A1
公开(公告)日:2022-03-17
申请号:US17457062
申请日:2021-12-01
IPC分类号: H04N19/196 , H04N19/172 , H04N19/176 , H04N19/159 , H04N19/146
摘要: This disclosure describes systems, methods, and devices related to generating visual quality metrics for encoded video frames. A method may include generating respective first visual quality metrics for pixels of an encoded video frame; generating respective second visual quality metrics for the pixels, the respective first visual quality metrics and the respective second visual quality metrics indicative of estimated human perceptions of the encoded video frame; generating a pixel block-based weight for the respective first visual quality metrics; generating a frame-based weight for the respective second visual quality metrics; and generating, based on the respective first visual quality metrics, the pixel block-based weight, the respective second visual quality metrics, and the frame-based weight, a human visual score indicative of a visual quality of the encoded video frame.
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