Abstract: An analyzer module may identify a plurality of users and a plurality of files that have been accessed by at least one of the users. Pairs of users may be identified where each user of a pair has accessed at least one same file. A weight value may be calculated for each of the identified pairs. The weight value may be calculated based on a number of same files that each of the users of an identified pair have accessed. Collaboration information associated with the users may be determined based on the weight values.

Abstract: A control point module may receive information associated with a plurality of users accessing a plurality of files. Each of the files may be stored in a folder of the plurality of folders. Users who have accessed one or more files stored in a folder may be assigned to each corresponding folder. Users who have been assigned to each folder of a plurality of pairs of the folders may be compared to identify one or more differences of assigned users between each folder of each pair of the folders. Furthermore, a recommended control point may be determined based on the identified one or more differences of the assigned users.

Abstract: A counter module may identify a number of files operations that have accessed files of a network file system. A folder comprising a first file associated with a file operation may be identified. A file activity count for the folder may be incremented based on the file operation to the first file located in the folder. A second folder that comprises the first folder may also be identified. A file activity count for the second folder may also be incremented in response to the incrementing of the file activity count for the first folder.

Abstract: The present disclosure provides for determining whether object accesses that occur in a file system qualify as relevant events, and displaying information about relevant events in a social file storage interface. A social file storage interface can provide a news feed of recent relevant events, a subscription list that displays information about relevant events performed by colleagues, and an access map that displays a visual representation of relevant events and relevant objects in the file system. An object access qualifies as a relevant event if an attribute of the object access satisfies relevance criteria defined by a user. If a user is not authorized to access an object, a relevant event pertaining to that object will not be displayed to the user in the social file storage interface. An object can also be accessed and opened from within the social file storage interface.

Abstract: The present disclosure provides for determining whether object accesses that occur in a file system qualify as relevant events, and displaying information about relevant events in a social file storage interface. A social file storage interface can provide a news feed of recent relevant events, a subscription list that displays information about relevant events performed by colleagues, and an access map that displays a visual representation of relevant events and relevant objects in the file system. An object access qualifies as a relevant event if an attribute of the object access satisfies relevance criteria defined by a user. If a user is not authorized to access an object, a relevant event pertaining to that object will not be displayed to the user in the social file storage interface. An object can also be accessed and opened from within the social file storage interface.

Abstract: Techniques for identifying potential malware domain names are disclosed. In one particular exemplary embodiment, the techniques may be realized as a system for identifying potential malware domain names. The system may comprise one or more processors communicatively coupled to a network. The one or more processors may be configured to receive a request for network data, where the request for network data may comprise a domain name. The one or more processors may also be configured to apply a lexical and linguistic analysis to the domain name. The one or more processors may also be configured to identify whether the domain name is a potential malware domain name based on the lexical and linguistic analysis.