Patents by Inventor Cheng-Lin Yeh
Cheng-Lin Yeh has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11973772Abstract: Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.Type: GrantFiled: February 22, 2022Date of Patent: April 30, 2024Assignee: Abnormal Security CorporationInventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan Reiser, Sanny Xiao Lang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
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Publication number: 20240113262Abstract: A light-emitting device includes: a semiconductor stack, including a first semiconductor layer, an active region and a second semiconductor layer; a first contact electrode and a second contact electrode formed on the semiconductor stack, wherein the first contact electrode includes a first contact part formed on the first semiconductor layer and the second contact electrode includes a second contact part formed on the second semiconductor layer; an insulating stack formed on the semiconductor stack, including an opening on the second contact part; a first electrode pad and a second electrode pad formed on the insulating stack, wherein the second electrode pad filled in the opening and connecting the second contact part; wherein the second electrode pad includes an upper surface, and the upper surface includes a platform area and a depression area on the second contact part; wherein the platform area has a maximum height relative to other areas of the upper surface; wherein an area of a projection of the platType: ApplicationFiled: September 1, 2023Publication date: April 4, 2024Inventors: Hsin-Ying WANG, Hui-Chun YEH, Jhih-Yong YANG, Chen OU, Cheng-Lin LU
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Patent number: 11949713Abstract: Introduced here are computer programs and computer-implemented techniques for discovering malicious emails and then remediating the threat posed by those malicious emails in an automated manner. A threat detection platform may monitor a mailbox to which employees of an enterprise are able to forward emails deemed to be suspicious for analysis. This mailbox may be referred to as an “abuse mailbox” or “phishing mailbox.” The threat detection platform can examine emails contained in the abuse mailbox and then determine whether any of those emails represent threats to the security of the enterprise. For example, the threat detection platform may classify each email contained in the abuse mailbox as being malicious or non-malicious. Thereafter, the threat detection platform may determine what remediation actions, if any, are appropriate for addressing the threat posed by those emails determined to be malicious.Type: GrantFiled: December 14, 2021Date of Patent: April 2, 2024Assignee: Abnormal Security CorporationInventors: Evan Reiser, Jeremy Kao, Cheng-Lin Yeh, Yea So Jung, Kai Jing Jiang, Abhijit Bagri, Su Li Debbie Tan, Venkatram Kishnamoorthi, Feng Shuo Deng
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Patent number: 11831661Abstract: A plurality of features associated with a message are determined. At least one feature included in the plurality of features is associated with a payload of the message. A determination is made that supplemental analysis should be performed on the message. The determination is based at least in part on performing behavioral analysis using at least some of the features included in the plurality of features. Supplemental analysis is performed.Type: GrantFiled: June 2, 2022Date of Patent: November 28, 2023Assignee: Abnormal Security CorporationInventors: Yu Zhou Lee, Micah J. Zirn, Umut Gultepe, Jeshua Alexis Bratman, Michael Douglas Kralka, Cheng-Lin Yeh, Dmitry Chechik, Sanjay Jeyakumar
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Patent number: 11824870Abstract: Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.Type: GrantFiled: November 4, 2019Date of Patent: November 21, 2023Assignee: Abnormal Security CorporationInventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan James Reiser, Sanny Xiao Yang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
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Patent number: 11743294Abstract: Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.Type: GrantFiled: June 28, 2021Date of Patent: August 29, 2023Assignee: Abnormal Security CorporationInventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan James Reiser, Sanny Xiao Yang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
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Patent number: 11704406Abstract: Deriving and surfacing insights regarding security threats is disclosed. A plurality of features associated with a message is determined. A plurality of facet models is used to analyze the determined features. Based at least in part on the analysis, it is determined that the message poses a security threat. A prioritized set of information is determined to be provided as output that is representative of why the message was determined to pose a security threat. At least a portion of the prioritized set of information is provided as output.Type: GrantFiled: September 12, 2022Date of Patent: July 18, 2023Assignee: Abnormal Security CorporationInventors: Yu Zhou Lee, Kai Jiang, Su Li Debbie Tan, Geng Sng, Cheng-Lin Yeh, Lawrence Stockton Moore, Sanny Xiao Lang Liao, Joey Esteban Cerquera, Jeshua Alexis Bratman, Sanjay Jeyakumar, Nishant Bhalchandra Karandikar
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Patent number: 11687648Abstract: Deriving and surfacing insights regarding security threats is disclosed. A plurality of features associated with a message is determined. A plurality of facet models is used to analyze the determined features. Based at least in part on the analysis, it is determined that the message poses a security threat. A prioritized set of information is determined to be provided as output that is representative of why the message was determined to pose a security threat. At least a portion of the prioritized set of information is provided as output.Type: GrantFiled: December 9, 2021Date of Patent: June 27, 2023Assignee: Abnormal Security CorporationInventors: Yu Zhou Lee, Kai Jiang, Su Li Debbie Tan, Geng Sng, Cheng-Lin Yeh, Lawrence Stockton Moore, Sanny Xiao Lang Liao, Joey Esteban Cerquera, Jeshua Alexis Bratman, Sanjay Jeyakumar, Nishant Bhalchandra Karandikar
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Publication number: 20230020623Abstract: Deriving and surfacing insights regarding security threats is disclosed. A plurality of features associated with a message is determined. A plurality of facet models is used to analyze the determined features. Based at least in part on the analysis, it is determined that the message poses a security threat. A prioritized set of information is determined to be provided as output that is representative of why the message was determined to pose a security threat. At least a portion of the prioritized set of information is provided as output.Type: ApplicationFiled: September 12, 2022Publication date: January 19, 2023Inventors: Yu Zhou Lee, Kai Jiang, Su Li Debbie Tan, Geng Sng, Cheng-Lin Yeh, Lawrence Stockton Moore, Sanny Xiao Lang Liao, Joey Esteban Cerquera, Jeshua Alexis Bratman, Sanjay Jeyakumar, Nishant Bhalchandra Karandikar
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Patent number: 11552969Abstract: Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.Type: GrantFiled: October 11, 2021Date of Patent: January 10, 2023Assignee: Abnormal Security CorporationInventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan Reiser, Sanny Xiao Lang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
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Publication number: 20220394047Abstract: A plurality of features associated with a message are determined. At least one feature included in the plurality of features is associated with a payload of the message. A determination is made that supplemental analysis should be performed on the message. The determination is based at least in part on performing behavioral analysis using at least some of the features included in the plurality of features. Supplemental analysis is performed.Type: ApplicationFiled: June 2, 2022Publication date: December 8, 2022Inventors: Yu Zhou Lee, Micah J. Zirn, Umut Gultepe, Jeshua Alexis Bratman, Michael Douglas Kralka, Cheng-Lin Yeh, Dmitry Chechik, Sanjay Jeyakumar
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Patent number: 11470042Abstract: Introduced here are threat detection platforms designed to discover possible instances of email account compromise in order to identify threats to an enterprise. In particular, a threat detection platform can examine the digital activities performed with the email accounts associated with employees of the enterprise to determine whether any email accounts are exhibiting abnormal behavior. Examples of digital activities include the reception of an incoming email, transmission of an outgoing email, creation of a mail filter, and occurrence of a sign-in event (also referred to as a “login event”). Thus, the threat detection platform can monitor the digital activities performed with a given email account to determine the likelihood that the given email account has been compromised.Type: GrantFiled: November 10, 2020Date of Patent: October 11, 2022Assignee: Abnormal Security CorporationInventors: Dmitry Chechik, Umut Gultepe, Raphael Kargon, Jeshua Alexis Bratman, Cheng-Lin Yeh, Sanny Xiao Lang Liao, Erin Elisabeth Edkins Ludert, Sanjay Jeyakumar, Hariank Muthakana
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Publication number: 20220286432Abstract: Introduced here are threat detection platforms designed to discover possible instances of email account compromise in order to identify threats to an enterprise. In particular, a threat detection platform can examine the digital activities performed with the email accounts associated with employees of the enterprise to determine whether any email accounts are exhibiting abnormal behavior. Examples of digital activities include the reception of an incoming email, transmission of an outgoing email, creation of a mail filter, and occurrence of a sign-in event (also referred to as a “login event”). Thus, the threat detection platform can monitor the digital activities performed with a given email account to determine the likelihood that the given email account has been compromised.Type: ApplicationFiled: May 23, 2022Publication date: September 8, 2022Inventors: Dmitry Chechik, Umut Gultepe, Raphael Kargon, Jeshua Alexis Bratman, Cheng-Lin Yeh, Sanny Xiao Lang Liao, Erin Elisabeth Edkins Ludert, Sanjay Jeyakumar, Hariank Sagar Muthakana
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Publication number: 20220278997Abstract: Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.Type: ApplicationFiled: February 22, 2022Publication date: September 1, 2022Inventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan Reiser, Sanny Xiao Lang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
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Patent number: 11431738Abstract: Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.Type: GrantFiled: July 13, 2020Date of Patent: August 30, 2022Assignee: Abnormal Security CorporationInventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan James Reiser, Sanny Xiao Yang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
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Publication number: 20220255961Abstract: Introduced here are computer programs and computer-implemented techniques for discovering malicious emails and then remediating the threat posed by those malicious emails in an automated manner. A threat detection platform may monitor a mailbox to which employees of an enterprise are able to forward emails deemed to be suspicious for analysis. This mailbox may be referred to as an “abuse mailbox” or “phishing mailbox.” The threat detection platform can examine emails contained in the abuse mailbox and then determine whether any of those emails represent threats to the security of the enterprise. For example, the threat detection platform may classify each email contained in the abuse mailbox as being malicious or non-malicious. Thereafter, the threat detection platform may determine what remediation actions, if any, are appropriate for addressing the threat posed by those emails determined to be malicious.Type: ApplicationFiled: December 14, 2021Publication date: August 11, 2022Inventors: Evan Reiser, Jeremy Kao, Cheng-Lin Yeh, Yea So Jung, Kai Jiang, Abhijit Bagri, Su Li Debbie Tan, Venkatram Kishnamoorthi, Feng Shuo Deng
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Patent number: 11381581Abstract: Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.Type: GrantFiled: July 13, 2020Date of Patent: July 5, 2022Assignee: Abnormal Security CorporationInventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan James Reiser, Sanny Xiao Yang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
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Publication number: 20220188411Abstract: Deriving and surfacing insights regarding security threats is disclosed. A plurality of features associated with a message is determined. A plurality of facet models is used to analyze the determined features. Based at least in part on the analysis, it is determined that the message poses a security threat. A prioritized set of information is determined to be provided as output that is representative of why the message was determined to pose a security threat. At least a portion of the prioritized set of information is provided as output.Type: ApplicationFiled: December 9, 2021Publication date: June 16, 2022Inventors: Yu Zhou Lee, Kai Jiang, Su Li Debbie Tan, Geng Sng, Cheng-Lin Yeh, Lawrence Stockton Moore, Sanny Xiao Lang Liao, Joey Esteban Cerquera, Jeshua Alexis Bratman, Sanjay Jeyakumar, Nishant Bhalchandra Karandikar
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Patent number: 11336666Abstract: Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.Type: GrantFiled: July 13, 2020Date of Patent: May 17, 2022Assignee: Abnormal Security CorporationInventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan James Reiser, Sanny Xiao Yang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
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Patent number: 11252189Abstract: Introduced here are computer programs and computer-implemented techniques for discovering malicious emails and then remediating the threat posed by those malicious emails in an automated manner. A threat detection platform may monitor a mailbox to which employees of an enterprise are able to forward emails deemed to be suspicious for analysis. This mailbox may be referred to as an “abuse mailbox” or “phishing mailbox.” The threat detection platform can examine emails contained in the abuse mailbox and then determine whether any of those emails represent threats to the security of the enterprise. For example, the threat detection platform may classify each email contained in the abuse mailbox as being malicious or non-malicious. Thereafter, the threat detection platform may determine what remediation actions, if any, are appropriate for addressing the threat posed by those emails determined to be malicious.Type: GrantFiled: January 22, 2021Date of Patent: February 15, 2022Assignee: Abnormal Security CorporationInventors: Evan James Reiser, Jeremy Kao, Cheng-Lin Yeh, Yea So Jung, Kai Jing Jiang, Abhijit Bagri, Su Li Debbie Tan, Venkatram Krishnamoorthi, Fang Shuo Deng