Abstract: An architecture for receiving and responding to requests in a vehicle system may include transmitting requests to a remote processing system configured to verify the authenticity of requests and determine responsive actions. The action jobs may be maintained at a location remote from the vehicle, and the vehicle may be configured to retrieve action jobs from the remote location.

Abstract: A device for detecting a missing element on a circuit board comprising a positioning tray, a data processing assembly, a lifting control assembly, and a detecting assembly. The positioning tray supports and positions a circuit board to be tested. The data processing assembly is connected with the lifting control assembly and the detecting assembly, and sends a control signal to the lifting control assembly, receives detection data sent by the detecting assembly, and compares the detection data with preset reference data to obtain a detection result of a missing element. The detecting assembly moves up and down between an initial position and a preset position under the control of the lifting control assembly, and sends the detection data to the data processing assembly according to a contact state with elements on the circuit board to be tested at the preset position.

Abstract: A device for detecting a missing element on a circuit board comprising a positioning tray, a data processing assembly, a lifting control assembly, and a detecting assembly. The positioning tray supports and positions a circuit board to be tested. The data processing assembly is connected with the lifting control assembly and the detecting assembly, and sends a control signal to the lifting control assembly, receives detection data sent by the detecting assembly, and compares the detection data with preset reference data to obtain a detection result of a missing element. The detecting assembly moves up and down between an initial position and a preset position under the control of the lifting control assembly, and sends the detection data to the data processing assembly according to a contact state with elements on the circuit board to be tested at the preset position.

Abstract: Techniques for malware detection using clustering with malware source information are disclosed. In some embodiments, malware detection using clustering with malware source information includes generating a first cluster of source information associated with a first malware sample, in which the first malware sample was determined to be malware, and the first malware sample was determined to be downloaded from a first source; and determining that a second source is associated with malware based on the first cluster.

Abstract: An architecture for receiving and responding to requests in a vehicle system may include transmitting requests to a remote processing system configured to verify the authenticity of requests and determine responsive actions. The action jobs may be maintained at a location remote from the vehicle, and the vehicle may be configured to retrieve action jobs from the remote location.

Abstract: An architecture for receiving and responding to requests in a vehicle system may include transmitting requests to a remote processing system configured to verify the authenticity of requests and determine responsive actions. The action jobs may be maintained at a location remote from the vehicle, and the vehicle may be configured to retrieve action jobs from the remote location.

Abstract: An architecture for receiving and responding to requests in a vehicle system may include transmitting requests to a remote processing system configured to verify the authenticity of requests and determine responsive actions. The action jobs may be maintained at a location remote from the vehicle, and the vehicle may be configured to retrieve action jobs from the remote location.

Abstract: Techniques for malware domain detection using passive Domain Name Service (DNS) are disclosed. In some embodiments, malware domain detection using passive DNS includes generating a malware association graph that associates a plurality of malware samples with malware source information, in which the malware source information includes a first domain; generating a reputation score for the first domain using the malware association graph and passive DNS information; and determining whether the first domain is a malware domain based on the reputation score for the first domain.

Abstract: Techniques for malware detection using clustering with malware source information are disclosed. In some embodiments, malware detection using clustering with malware source information includes generating a first cluster of source information associated with a first malware sample, in which the first malware sample was determined to be malware, and the first malware sample was determined to be downloaded from a first source; and determining that a second source is associated with malware based on the first cluster.

Abstract: Techniques for malware detection using clustering with malware source information are disclosed. In some embodiments, malware detection using clustering with malware source information includes generating a first cluster of source information associated with a first malware sample, in which the first malware sample was determined to be malware, and the first malware sample was determined to be downloaded from a first source; and determining that a second source is associated with malware based on the first cluster.

Abstract: Detecting malicious PDF documents is disclosed. A PDF document is received. The PDF is classified using a classifier. The classifier is trained at least in part by using one of the following: (1) a feature associated with embedded script code; (2) a feature associated with a PDF action; and (3) a feature associated with a PDF structure.

Abstract: Techniques for malware domain detection using passive Domain Name Service (DNS) are disclosed. In some embodiments, malware domain detection using passive DNS includes generating a malware association graph that associates a plurality of malware samples with malware source information, in which the malware source information includes a first domain; generating a reputation score for the first domain using the malware association graph and passive DNS information; and determining whether the first domain is a malware domain based on the reputation score for the first domain.

Abstract: Techniques for malware detection using clustering with malware source information are disclosed. In some embodiments, malware detection using clustering with malware source information includes generating a first cluster of source information associated with a first malware sample, in which the first malware sample was determined to be malware, and the first malware sample was determined to be downloaded from a first source; and determining that a second source is associated with malware based on the first cluster.

Abstract: Techniques for malware domain detection using passive Domain Name Service (DNS) are disclosed. In some embodiments, malware domain detection using passive DNS includes generating a malware association graph that associates a plurality of malware samples with malware source information, in which the malware source information includes a first domain; generating a reputation score for the first domain using the malware association graph and passive DNS information; and determining whether the first domain is a malware domain based on the reputation score for the first domain.

Abstract: Techniques for malware detection using clustering with malware source information are disclosed. In some embodiments, malware detection using clustering with malware source information includes generating a first cluster of source information associated with a first malware sample, in which the first malware sample was determined to be malware, and the first malware sample was determined to be downloaded from a first source; and determining that a second source is associated with malware based on the first cluster.