Abstract: A data management platform for Autonomous Vehicles (AVs) is provided. An AV can partition raw data into ingestion objects. The AV can transform the ingestion objects and generate associated manifests. The AV can offload first copies of the manifests in real-time to a data center. At a later time, the AV can offload second copies of the manifests to an AV servicing station. The station can upload the second copies to the data center. If the manifests match, then the station can notify the AV that it is safe to erase the manifests and transformed objects from local storage after offloading completes. If the manifests do not match and a Service Level Agreement (SLA) is violated, then the AV can be docked for further diagnosis. If no SLA is applicable, then the error can be annotated and the transformed objects can be discarded.

Abstract: A data management platform for Autonomous Vehicles (AVs) is provided. The data management platform can receive, from an AV at a first time, a first copy of a manifest including a creation history of a transformed object generated by the AV and a data integrity value corresponding to the transformed object. The data management platform can receive, from a second computing system at a second time, a second copy of the manifest. The data management platform can reconcile the first copy and the second copy. The data management platform can receive, from the second computing system at a third time, a request to upload the transformed object. The data management platform can validate the transformed object stored in storage of the first computing system based on the data integrity value included in the manifest.

Abstract: A data management platform for Autonomous Vehicles (AVs) is provided. The data management platform can receive, from an AV at a first time, a first copy of a manifest including a creation history of a transformed object generated by the AV and a data integrity value corresponding to the transformed object. The data management platform can receive, from a second computing system at a second time, a second copy of the manifest. The data management platform can reconcile the first copy and the second copy. The data management platform can receive, from the second computing system at a third time, a request to upload the transformed object. The data management platform can validate the transformed object stored in storage of the first computing system based on the data integrity value included in the manifest.

Abstract: A data management platform for Autonomous Vehicles (AVs) is provided. The data management platform can receive, from an AV at a first time, a first copy of a manifest including a creation history of a transformed object generated by the AV and a data integrity value corresponding to the transformed object. The data management platform can receive, from a second computing system at a second time, a second copy of the manifest. The data management platform can reconcile the first copy and the second copy. The data management platform can receive, from the second computing system at a third time, a request to upload the transformed object. The data management platform can validate the transformed object stored in storage of the first computing system based on the data integrity value included in the manifest.

Abstract: A data management platform for Autonomous Vehicles (AVs) is provided. An AV can partition raw data into ingestion objects. The AV can transform the ingestion objects and generate associated manifests. The AV can offload first copies of the manifests in real-time to a data center. At a later time, the AV can offload second copies of the manifests to an AV servicing station. The station can upload the second copies to the data center. If the manifests match, then the station can notify the AV that it is safe to erase the manifests and transformed objects from local storage after offloading completes. If the manifests do not match and a Service Level Agreement (SLA) is violated, then the AV can be docked for further diagnosis. If no SLA is applicable, then the error can be annotated and the transformed objects can be discarded.

Abstract: A data management platform for Autonomous Vehicles (AVs) is provided. The data management platform can receive, from an AV at a first time, a first copy of a manifest including a creation history of a transformed object generated by the AV and a data integrity value corresponding to the transformed object. The data management platform can receive, from a second computing system at a second time, a second copy of the manifest. The data management platform can reconcile the first copy and the second copy. The data management platform can receive, from the second computing system at a third time, a request to upload the transformed object. The data management platform can validate the transformed object stored in storage of the first computing system based on the data integrity value included in the manifest.

Abstract: A data management platform for Autonomous Vehicles (AVs) is provided. An AV can partition raw data into ingestion objects. The AV can transform the ingestion objects and generate associated manifests. The AV can offload first copies of the manifests in real-time to a data center. At a later time, the AV can offload second copies of the manifests to an AV servicing station. The station can upload the second copies to the data center. If the manifests match, then the station can notify the AV that it is safe to erase the manifests and transformed objects from local storage after offloading completes. If the manifests do not match and a Service Level Agreement (SLA) is violated, then the AV can be docked for further diagnosis. If no SLA is applicable, then the error can be annotated and the transformed objects can be discarded.

Abstract: A system, apparatus, and method for managing data storage and data access for semi-structured data systems.

Abstract: A system, apparatus, and method for managing data storage and data access for semi-structured data systems.

Abstract: A computer-implemented method for managing malware signatures. The method may include maintaining a set of active malware signatures and maintaining a set of dormant malware signatures. The method may also include providing the set of active malware signatures for use in malware detection more frequently than the set of dormant malware signatures and determining that a first malware signature from the set of dormant malware signatures triggers one or more positive malware detection responses. The method may further include, in response to the determination, moving the first malware signature from the set of dormant malware signatures to the set of active malware signatures. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Reputations of objects are determined by a reputation system using reports from clients identifying the objects. Confidence metrics for the clients are generated using information determined from the reports. Confidence metrics indicate the amounts of confidence in the veracity of the reports. Reputation scores of objects are calculated using the reports from the clients and the confidence metrics for the clients. Confidence metrics and reputation scores are stored in correlation with identifiers for the objects. An object's reputation score is provided to a client in response to a request.

Abstract: A system, apparatus, and method for managing data storage and data access for semi-structured data systems.

Abstract: A system, apparatus, and method for managing data storage and data access for semi-structured data systems.

Abstract: Reputations of objects are determined by a reputation system using reports from clients identifying the objects. Confidence metrics for the clients are generated using information determined from the reports. Confidence metrics indicate the amounts of confidence in the veracity of the reports. Reputation scores of objects are calculated using the reports from the clients and the confidence metrics for the clients. Confidence metrics and reputation scores are stored in correlation with identifiers for the objects. An object's reputation score is provided to a client in response to a request.

Abstract: A computer-implemented method for managing malware signatures. The method may include maintaining a set of active malware signatures and maintaining a set of dormant malware signatures. The method may also include providing the set of active malware signatures for use in malware detection more frequently than the set of dormant malware signatures and determining that a first malware signature from the set of dormant malware signatures triggers one or more positive malware detection responses. The method may further include, in response to the determination, moving the first malware signature from the set of dormant malware signatures to the set of active malware signatures. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A mechanism is provided for determining a safety reputation for a network site in a manner that provides both wide coverage of potentially malicious sites as well as improves the freshness of information from which the safety reputation is derived. Community-based information, such as reports from users related to recently-visited network sites, malware detected by reporting network nodes, non-specific information such as unusual CPU usage and network activity of visiting nodes, and information received from other types of external feeds is used in determining the safety reputation and updating the safety reputation. Such information is analyzed in order to determine network sites that are potential sources of malware, which can then be subjected to more detailed analysis.

Abstract: A computer-implemented method for detecting infected files may include identifying a set of known-clean files. The method may also include identifying a set of characteristics of an unchecked file. The method may further include determine that the unchecked file is related to a clean file in the set of known-clean files. The determination may be based on the set of characteristics of the unchecked file. The method may additionally include determining whether the unchecked file is functionally equivalent to the clean file. This determination may be based on the set of characteristics of the unchecked file. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Attempts to communicate telephonically by a mobile phone are detected. When an attempt is detected, an associated phone number is identified and transmitted to a server in order to glean corresponding security information. On the server, a database is maintained containing 1) phone numbers known to present potential security concerns and 2) descriptive security information concerning each of these phone numbers. The server receives phone numbers from mobile phones to check for security information, searches the database for received phone numbers, and transmits corresponding security information to the originating mobile phones. Security information concerning identified telephone numbers is received from the server by mobile phones. Responsive to the contents of the received security information, detected attempts to communicate telephonically are allowed to processed, blocked or otherwise processed.

Abstract: A computer-implemented method for authenticating requests from a client running trialware through a proof of work protocol is described. A request received from a client running trialware is analyzed. A cryptographic puzzle is generated if an authentication token is not included with the request. The cryptographic puzzle is transmitted to the client. A solution to the cryptographic puzzle received from the client is analyzed. A response to the request is generated if the received solution to the puzzle is validated.

Abstract: A mechanism is provided for determining a safety reputation for a network site in a manner that provides both wide coverage of potentially malicious sites as well as improves the freshness of information from which the safety reputation is derived. Community-based information, such as reports from users related to recently-visited network sites, malware detected by reporting network nodes, non-specific information such as unusual CPU usage and network activity of visiting nodes, and information received from other types of external feeds is used in determining the safety reputation and updating the safety reputation. Such information is analyzed in order to determine network sites that are potential sources of malware, which can then be subjected to more detailed analysis.