Abstract: A computer-implemented method for determining security reputations of wireless network access points may include (1) receiving a unique identifier for a wireless network access point to which a mobile device has connected and security information that identifies the security posture of the mobile device after connecting to the wireless network access point, (2) adding the unique identifier and the security information to a security database, (3) correlating the security information with an additional set of security information that identifies the security posture of an additional mobile device after connecting to the wireless network access point, (4) assigning a security reputation to the wireless network access point, and (5) enabling a requesting mobile device to determine whether to connect to the wireless network access point by providing the security reputation of the wireless network access point to the requesting mobile device.

Abstract: Techniques for classifying and labeling data are disclosed. In one embodiment, the techniques may be realized as a system for classifying and labeling data comprising one or more processors. The one or more processors may be configured to distribute training data across a plurality of hosts. Each of the hosts may be assigned a random subset of the training data, and configured to cluster its own subset independently. The one or more processors may be further configured to label each cluster of the training data. The one or more processors may be further configured to receive new data, associate the new data with a plurality of the clusters of the training data, and assign the new data a label. The label may be chosen from labels of the plurality of the clusters. And the label may have a maximum associative factor of the new data.

Abstract: A computer-implemented method for determining security reputations of wireless network access points may include (1) receiving a unique identifier for a wireless network access point to which a mobile device has connected and security information that identifies the security posture of the mobile device after connecting to the wireless network access point, (2) adding the unique identifier and the security information to a security database, (3) correlating the security information with an additional set of security information that identifies the security posture of an additional mobile device after connecting to the wireless network access point, (4) assigning a security reputation to the wireless network access point, and (5) enabling a requesting mobile device to determine whether to connect to the wireless network access point by providing the security reputation of the wireless network access point to the requesting mobile device.

Abstract: The disclosed computer-implemented method for automated generation of generic signatures used to detect polymorphic malware may include (1) clustering a set of polymorphic file samples that share a set of static attributes in common with one another, (2) computing a distance of the polymorphic file samples from a centroid that represents a reference data point with respect to the set of polymorphic file samples, (3) determining that the distance of the polymorphic file samples from the centroid is below a certain threshold, and then upon determining that the distance is below the certain threshold, (4) identifying, within the set of static attributes shared in common by the polymorphic file samples, a subset of static attributes whose values are identical across all of the polymorphic file samples and (5) generating a generic file-classification signature from the subset of static attributes. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method for automated generation of generic signatures used to detect polymorphic malware may include (1) clustering a set of polymorphic file samples that share a set of static attributes in common with one another, (2) computing a distance of the polymorphic file samples from a centroid that represents a reference data point with respect to the set of polymorphic file samples, (3) determining that the distance of the polymorphic file samples from the centroid is below a certain threshold, and then upon determining that the distance is below the certain threshold, (4) identifying, within the set of static attributes shared in common by the polymorphic file samples, a subset of static attributes whose values are identical across all of the polymorphic file samples and (5) generating a generic file-classification signature from the subset of static attributes. Various other methods, systems, and computer-readable media are also disclosed.