Abstract:
Methods, apparatus, systems and articles of manufacture are disclosed to learn malicious activity. An example method includes assigning weights of a distance function to respective statistical features; iteratively calculating, with a processor, the distance function to adjust the weights (1) to cause a reduction in a first distance calculated according to the distance function for a first pair of entities in a reference group associated with malicious activity and (2) to cause an increase in a second distance calculated according to the distance function for a first one of the entities included in the reference group and a second entity not included in the reference group; and determining whether a first statistical feature is indicative of malicious activity based on a respective adjusted weight of the first statistical feature determined after calculating the distance function for a number of iterations.
Abstract:
Methods and apparatus to configure virtual private mobile networks are disclosed. Example methods include provisioning a virtual private mobile network within a wireless network, and, after provisioning the virtual private mobile network, determining whether a first communication from a user equipment matches a security event profile. When the first communication matches the profile, the example methods include transmitting, from the wireless network via a first base transceiver station, an instruction to cause the user equipment to be communicatively coupled to the virtual private mobile network. The example methods further include instructing the user equipment to transmit a second communication through a second base transceiver station that is physically separate from the first base transceiver station and through the virtual private mobile network. In the example methods, the virtual private mobile network is isolated in a wireless spectrum from other portions of the network.
Abstract:
Example network monitoring methods disclosed herein include iteratively adjusting respective weights assigned to respective types of network activity features for devices monitored in a network, the iterative adjusting to determine an output set of weights corresponding to ones of the types of network activity features indicative of malicious network activity. For example, the iterative adjusting is to (1) reduce a first distance calculated between a first pair of reference devices previously classified as being associated with malicious network activity, and (2) increase a second distance calculated between a first one of the pair of the reference devices and a first unclassified device. Disclosed example network monitoring methods also include determining whether a second unclassified device is associated with malicious network activity based on the output set of weights.
Abstract:
A method, non-transitory computer readable medium and apparatus for deriving trustful metadata for an application are disclosed. For example, the method crawls online for the application, analyzes the application to determine a function of the application, and generates trustful meta-data for the application based upon the function of the application.
Abstract:
Methods, apparatus, systems and articles of manufacture are disclosed to identify an Internet protocol address blacklist boundary. An example method includes identifying a netblock associated with a malicious Internet protocol address, the netblock having a lower boundary and an upper boundary, collecting netflow data associated with a plurality of Internet protocol addresses in the netblock, establishing a first window associated with a lower portion of Internet protocol addresses numerically lower than a candidate Internet protocol address, establishing a second window associated with an upper portion of Internet protocol addresses numerically higher than a candidate Internet protocol address, calculating a breakpoint score based on a comparison between a behavioral profile of the first window and a behavioral profile of the second window, and identifying a first sub-netblock when the breakpoint score exceeds a threshold value.
Abstract:
A method of generating a signature for a group of electronic messages that each include a plurality of characters comprises extracting a plurality of blocks of characters from each of the electronic messages, mathematically processing each of the blocks of characters from each electronic message, and generating a signature for the group of electronic messages based at least in part on the mathematically processed blocks of characters. In some embodiments a counting Bloom filter may be used to generate the signature. The signatures generated by these methods may be used to identify spam.
Abstract:
Methods and apparatus to migrate a mobile device from a first virtual private mobile network to a second virtual private mobile network are disclosed. An example apparatus includes a processor and a memory including instructions that cause the processor to perform operations including determining, based on a set of latency routing rules, that a communication transmitted via the first virtual private mobile network is a latency sensitive communication. In response to determining the communication is a latency sensitive communication, the mobile device that originated the latency sensitive communication is identified. The mobile device is communicating via the first virtual private mobile network. Example operations also include migrating the mobile device from the first virtual private mobile network to the second virtual private mobile network wherein the second virtual private mobile network is configured to reduce the latency of the latency sensitive communication.
Abstract:
A method of generating a signature for a group of electronic messages that each include a plurality of characters comprises extracting a plurality of blocks of characters from each of the electronic messages, mathematically processing each of the blocks of characters from each electronic message, and generating a signature for the group of electronic messages based at least in part on the mathematically processed blocks of characters. In some embodiments a counting Bloom filter may be used to generate the signature. The signatures generated by these methods may be used to identify spam.
Abstract:
Methods and apparatus to configure virtual private mobile networks are disclosed. Example methods include provisioning a virtual private mobile network within a wireless network, and, after provisioning the virtual private mobile network, determining whether a first communication from a user equipment matches a security event profile. When the first communication matches the profile, the example methods include transmitting, from the wireless network via a first base transceiver station, an instruction to cause the user equipment to be communicatively coupled to the virtual private mobile network. The example methods further include instructing the user equipment to transmit a second communication through a second base transceiver station that is physically separate from the first base transceiver station and through the virtual private mobile network. In the example methods, the virtual private mobile network is isolated in a wireless spectrum from other portions of the network.
Abstract:
Methods and apparatus to migrate a mobile device from a first virtual private mobile network to a second virtual private mobile network are disclosed. An example apparatus includes a processor and a memory including instructions that cause the processor to perform operations including determining, based on a set of latency routing rules, that a communication transmitted via the first virtual private mobile network is a latency sensitive communication. In response to determining the communication is a latency sensitive communication, the mobile device that originated the latency sensitive communication is identified. The mobile device is communicating via the first virtual private mobile network. Example operations also include migrating the mobile device from the first virtual private mobile network to the second virtual private mobile network wherein the second virtual private mobile network is configured to reduce the latency of the latency sensitive communication.