Abstract: Embodiments relate to systems, devices, and computer-implemented methods for managing domain name space collisions by accessing information, such as a domain name string, corresponding to a domain name resolution request and response. Based on at least the domain name string, a type of use value associated with the request can be determined. Based on at least the type of use value, a name collision risk value for the request can be determined. If the name collision risk value indicates there is a specified risk of a domain name string collision, then a domain name collision mitigation strategy can be generated and/or implemented.

Abstract: The present invention generally relates to a system for, and method of, obtaining, from a first identifier in a first name space, a second identifier in a second name space. The disclosed technique involves obtaining the first identifier in the first name space from a source, applying a rule to the first identifier in the first name space, such that a second identifier in a second name space is obtained, and providing the second identifier, such that the source obtains the second identifier without resolving the first identifier using a domain name system (DNS).

Abstract: The present invention generally relates to systems and methods for classifying executable files as likely malware or likely benign. The techniques utilize temporally-ordered network behavioral artifacts together with machine learning techniques to perform the classification. Because they rely on network behavioral artifacts, the disclosed techniques may be applied to executable files with obfuscated code.

Abstract: The present invention generally relates to systems and methods for classifying executable files as likely malware or likely benign. The techniques utilize temporally-ordered network behavioral artifacts together with machine learning techniques to perform the classification. Because they rely on network behavioral artifacts, the disclosed techniques may be applied to executable files with obfuscated code.

Abstract: The present invention generally relates to systems and methods for classifying executable files as likely malware or likely benign. The techniques utilize temporally-ordered network behavioral artifacts together with machine learning techniques to perform the classification. Because they rely on network behavioral artifacts, the disclosed techniques may be applied to executable files with obfuscated code.

Abstract: Embodiments relate to systems, devices, and computer-implemented methods for managing domain name space collisions by accessing information, such as a domain name string, corresponding to a domain name resolution request and response. Based on at least the domain name string, a type of use value associated with the request can be determined. Based on at least the type of use value, a name collision risk value for the request can be determined. If the name collision risk value indicates there is a specified risk of a domain name string collision, then a domain name collision mitigation strategy can be generated and/or implemented.

Abstract: The present invention generally relates to a system for, and method of, obtaining, from a first identifier in a first name space, a second identifier in a second name space. The disclosed technique involves obtaining the first identifier in the first name space from a source, applying a rule to the first identifier in the first name space, such that a second identifier in a second name space is obtained, and providing the second identifier, such that the source obtains the second identifier without resolving the first identifier using a domain name system (DNS).

Abstract: The present invention generally relates to systems and methods for classifying executable files as likely malware or likely benign. The techniques utilize temporally-ordered network behavioral artifacts together with machine learning techniques to perform the classification. Because they rely on network behavioral artifacts, the disclosed techniques may be applied to executable files with obfuscated code.