Abstract:
Methods and systems for providing information associated with a location history of a mobile device to one or more applications are disclosed. A mobile device generates one or more location history records based on one or more locations of the mobile device, each location history record comprising one or more points of interest and a duration at the one or more points of interest, receives an information request from at least one application, determines a subset of the one or more location history records that meet criteria from the information request, determines a level of permission for the at least one application based on the information request and the subset of the one or more location history records, and provides information associated with the subset of the one or more location history records to the at least one application based on the level of permission.
Abstract:
Methods and systems for providing information associated with a location history of a mobile device to one or more applications are disclosed. A mobile device generates one or more location history records based on one or more locations of the mobile device, each location history record comprising one or more points of interest and a duration at the one or more points of interest, receives an information request from at least one application, determines a subset of the one or more location history records that meet criteria from the information request, determines a level of permission for the at least one application based on the information request and the subset of the one or more location history records, and provides information associated with the subset of the one or more location history records to the at least one application based on the level of permission.
Abstract:
Methods and systems for providing information associated with a location history of a mobile device to one or more applications are disclosed. A mobile device generates one or more location history records based on one or more locations of the mobile device, each location history record comprising one or more points of interest and a duration at the one or more points of interest, receives an information request from at least one application, determines a subset of the one or more location history records that meet criteria from the information request, determines a level of permission for the at least one application based on the information request and the subset of the one or more location history records, and provides information associated with the subset of the one or more location history records to the at least one application based on the level of permission.
Abstract:
Various embodiments provide methods, devices, and non-transitory processor-readable storage media enabling rogue access point detection with a communications device by sending multiple probes via different network connections to a remote server and receiving probe replies. Various embodiments may include a communication device transmitting a first probe addressed to a server via a first network connection and a second probe addressed to the server via a second network connection. Upon receiving a first probe reply from the server via the first network connection and a second probe reply from the server via the second network connection server, the communications device may analyze the received probe replies to determine whether an access point of either the first network or the second network is a rogue access point.
Abstract:
Embodiments provide methods of protecting computing devices from malicious activity. A processor of a networking device may monitor network traffic flows of network computing devices and identify applications that are a source of the first network traffic flow. The processor may observe network traffic flows of identified source applications over time to determine normal network traffic flows of the source applications. The processor may then observe network traffic flows to detect when a source application is behaving anomalously based on associated network traffic flow characteristics deviating from normal network traffic flows of the source applications.
Abstract:
Embodiments provide methods of protecting computing devices from malicious activity. A processor of a network device may receive a first network traffic flow of a monitoring computing device and a malicious activity tag identifying a malicious behavior of the first network traffic flow. The processor may determine a characteristic of the first network traffic flow based at least in part on information in the first network traffic flow and the malicious activity tag. The processor may receive a second network traffic flow from a non-monitoring computing device, and may associate the malicious activity tag and the second network traffic flow based on a characteristic of the second network traffic flow based at least in part on information in the second network traffic flow and the characteristic of the first network traffic flow.
Abstract:
A network and its devices may be protected from non-benign behavior, malware, and cyber attacks by configuring a server computing device to work in conjunction with a multitude of client computing devices in the network. The server computing device may be configured to receive data that was collected from independent executions of different instances of the same software application on different client computing devices. The server computing device may combine the received data, and use the combined data to identify unexplored code space or potential code paths for evaluation. The server computing device may then exercise the software application through the identified unexplored code space or identified potential code paths in a client computing device emulator to generate analysis results, and use the generated analysis results to determine whether the software application is non-benign.
Abstract:
A computing device may be protected from non-benign behavior, malware, and cyber attacks by using a combination of predictive and real-time behavior-based analysis techniques. A computing device may be configured to identify anticipated behaviors of a software application before runtime, analyze the anticipated behaviors before runtime to generate static analysis results, commencing execution of the software application, analyze behaviors of the software application during runtime via a behavior-based analysis system, and control operations of the behavior-based analysis system based on the static analysis results.
Abstract:
Methods, and computing devices implementing the methods, use application-based classifier models to improve the efficiency and performance of a comprehensive behavioral monitoring and analysis system predicting whether a software application is causing undesirable or performance depredating behavior. The application-based classifier models may include a reduced and more focused subset of the decision nodes that are included in a full or more complete classifier model that may be received or generated in the computing device. The application groups may be represented by application groups formed of computing device applications sharing related features, and may be generated using one or more clustering algorithms. Lean classifier models may be generated for each of the application group and may incorporate historical user input regarding execution permissions for features of applications within an application group.
Abstract:
Systems, apparatus and methods for selecting a base station or a set of base stations for RTT measurements, or other interactive radio localization technique, to determine a position fix of a device are presented. The method imposes a processing load on only inactive or less active base stations. Busy or busier base stations are not used in the interactive radio localization technique. By imposing a processing load on only less active base stations, transmitting devices may be under loaded and encounter a more uniform processing delay, and thus provide a more accurate measurement resulting in a more accurate position fix.