Abstract: An Automated Teller Machine (ATM) terminal receives a transaction request from a user. The ATM terminal triggers a camera to capture a first image of the authentication media item presented by the user, where the first image of the authentication media item is embedded with a first unique code. The ATM terminal compares the first image of the authentication media item with a second image of the authentication media item that is associated with the user, where the second image of the authentication media item is embedded with a second unique code for verifying the user. The ATM terminal determines whether the first unique code corresponds to the second unique code. The ATM terminal conducts the transaction request if it is determined that the first unique code corresponds to the second unique code.

Abstract: A lift apparatus having a support assembly that supports a slide panel assembly and an actuator that selectively adjusts the height or vertical position of the support assembly to thereby adjust the vertical position of the slide panel assembly. The support assembly is movably coupled to a bed of a vehicle (e.g., a truck). Vehicles including the lift apparatus and a slide assembly are also disclosed.

Abstract: An application program interface (API) analyzer that determines protocols and formats to interact with a service provider or smart device. The API analyzer identifies an API endpoint or websites for the service provider or smart device, determines a service category or device category, selects a category-specific corpus, forms a service-specific or device-specific corpus by appending information regarding the service provider or smart device to the category-specific corpus, and parses API documentation or the websites.

Abstract: Techniques for using honeypots to lure attackers and gather data about attackers and attack patterns on Infrastructure-as-a-Service (IaaS) instances. The gathered data may then be analyzed and used to proactively prevent such attacks.

Abstract: Techniques for using honeypots to lure attackers and gather data about attackers and attack patterns on Infrastructure-as-a-Service (IaaS) instances. The gathered data may then be analyzed and used to proactively prevent such attacks.

Abstract: An application program interface (API) analyzer that determines protocols and formats to interact with a service provider or smart device. The API analyzer identifies an API endpoint or web sites for the service provider or smart device, determines a service category or device category, selects a category-specific corpus, forms a service-specific or device-specific corpus by appending information regarding the service provider or smart device to the category-specific corpus, and parses API documentation or the websites.

Abstract: This disclosure relates to personalized and dynamic server-side searching techniques for encrypted data. Current so-called ‘zero-knowledge’ privacy systems (i.e., systems where the server has ‘zero-knowledge’ about the client data that it is storing) utilize servers that hold encrypted data without the decryption keys necessary to decrypt, index, and/or re-encrypt the data. As such, the servers are not able to perform any kind of meaningful server-side search process, as it would require access to the underlying decrypted data. Therefore, such prior art ‘zero-knowledge’ privacy systems provide a limited ability for a user to search through a large dataset of encrypted documents to find critical information.

Abstract: This disclosure relates to personalized and dynamic server-side searching techniques for encrypted data. Current so-called ‘zero-knowledge’ privacy systems (i.e., systems where the server has ‘zero-knowledge’ about the client data that it is storing) utilize servers that hold encrypted data without the decryption keys necessary to decrypt, index, and/or re-encrypt the data. As such, the servers are not able to perform any kind of meaningful server-side search process, as it would require access to the underlying decrypted data. Therefore, such prior art ‘zero-knowledge’ privacy systems provide a limited ability for a user to search through a large dataset of encrypted documents to find critical information.

Abstract: This disclosure relates to personalized and dynamic server-side searching techniques for encrypted data. Current so-called ‘zero-knowledge’ privacy systems (i.e., systems where the server has ‘zero-knowledge’ about the client data that it is storing) utilize servers that hold encrypted data without the decryption keys necessary to decrypt, index, and/or re-encrypt the data. As such, the servers are not able to perform any kind of meaningful server-side search process, as it would require access to the underlying decrypted data. Therefore, such prior art ‘zero-knowledge’ privacy systems provide a limited ability for a user to search through a large dataset of encrypted documents to find critical information.

Abstract: An application program interface (API) analyzer that determines protocols and formats to interact with a service provider or smart device. The API analyzer identifies an API endpoint or web sites for the service provider or smart device, determines a service category or device category, selects a category-specific corpus, forms a service-specific or device-specific corpus by appending information regarding the service provider or smart device to the category-specific corpus, and parses API documentation or the websites.

Abstract: Techniques for using honeypots to lure attackers and gather data about attackers and attack patterns on Infrastructure-as-a-Service (IaaS) instances. The gathered data may then be analyzed and used to proactively prevent such attacks.

Abstract: An application program interface (API) analyzer that determines protocols and formats to interact with a service provider or smart device. The API analyzer identifies an API endpoint or websites for the service provider or smart device, determines a service category or device category, selects a category-specific corpus, forms a service-specific or device-specific corpus by appending information regarding the service provider or smart device to the category-specific corpus, and parses API documentation or the websites.

Abstract: The present invention is directed to a see-through near eye optical module that in most cases is fabricated as a standalone unit. The see-through near eye optical module is in certain embodiments then placed in optical communication and alignment with an eyewear lens having appropriate optical power such that when a wearer thereof looks through the see-through near eye optical module he or she can see a real world image and virtual image clearly. In other embodiments the appropriate optical power is provided in the rear section of the see-through near eye optical module. Thus, the combination of both the see-through near eye optical module and the appropriate optical power provides the wearer with a clear augmented reality or mixed reality experience. The placement can be by way of positioning within an open notch, hole, groove, recess, or other section of an eyewear lens.

Abstract: The present invention is directed to a see-through near eye optical module that in most cases is fabricated as a standalone unit. The see-through near eye optical module is in certain embodiments then placed in optical communication and alignment with an eyewear lens having appropriate optical power such that when a wearer thereof looks through the see-through near eye optical module he or she can see a real world image and virtual image clearly. In other embodiments the appropriate optical power is provided in the rear section of the see-through near eye optical module. Thus, the combination of both the see-through near eye optical module and the appropriate optical power provides the wearer with a clear augmented reality or mixed reality experience. The placement can be by way of positioning within an open notch, hole, groove, recess, or other section of an eyewear lens.

Abstract: This disclosure relates to personalized and dynamic server-side searching techniques for encrypted data. Current so-called ‘zero-knowledge’ privacy systems (i.e., systems where the server has ‘zero-knowledge’ about the client data that it is storing) utilize servers that hold encrypted data without the decryption keys necessary to decrypt, index, and/or re-encrypt the data. As such, the servers are not able to perform any kind of meaningful server-side search process, as it would require access to the underlying decrypted data. Therefore, such prior art ‘zero-knowledge’ privacy systems provide a limited ability for a user to search through a large dataset of encrypted documents to find critical information.

Abstract: An application program interface (API) analyzer that determines protocols and formats to interact with a service provider or smart device. The API analyzer identifies an API endpoint or websites for the service provider or smart device, determines a service category or device category, selects a category-specific corpus, forms a service-specific or device-specific corpus by appending information regarding the service provider or smart device to the category-specific corpus, and parses API documentation or the websites.

Abstract: Users desire a communications system that allows the users to apply customized privacy settings (and, optionally, encryption keys) differently to particular portions of a document—even if the document is of a ‘lossy’ file type, e.g., a JPEG image. The custom access permission settings may be implemented by obfuscating portions of the original file and then embedding “secret,” e.g., hidden and/or encrypted, versions of the obfuscated portions in parts of the data structure of the original lossy file in the form of “layers” (e.g., the bit-equivalent of PNG layers). The individual encrypted layers may then be decrypted according to each recipient's permissions and layered on top of the original lossy file ‘in memory’ before being displayed to the recipient. The use of multiple encrypted layers allows for the visual revelation of the content of the original lossy file without modifying the actual underlying image content of the original lossy file.

Abstract: An application program interface (API) analyzer that determines protocols and formats to interact with a service provider or smart device. The API analyzer identifies an API endpoint or web sites for the service provider or smart device, determines a service category or device category, selects a category-specific corpus, forms a service-specific or device-specific corpus by appending information regarding the service provider or smart device to the category-specific corpus, and parses API documentation or the websites.

Abstract: A universal interaction platform that communicates with service providers and smart devices by receiving a message object that includes information indicative of a user intent for one of the service providers or smart devices to perform a function, determines the service provider or smart device that the user intends to perform the function, determines a protocol and format for communicating with the service provider or smart device, formats an instruction for the service provider or smart device, and outputs the instruction to the service provider or smart device.

Abstract: Users desire a communications system that allows the users to apply customized privacy settings (and, optionally, encryption keys) differently to particular portions of a document—even if the document is of a ‘lossy’ file type, e.g., a JPEG image. The custom access permission settings may be implemented by obfuscating portions of the original file and then embedding “secret,” e.g., hidden and/or encrypted, versions of the obfuscated portions in parts of the data structure of the original lossy file in the form of “layers” (e.g., the bit-equivalent of PNG layers). The individual encrypted layers may then be decrypted according to each recipient's permissions and layered on top of the original lossy file ‘in memory’ before being displayed to the recipient. The use of multiple encrypted layers allows for the visual revelation of the content of the original lossy file without modifying the actual underlying image content of the original lossy file.