Abstract: The disclosed embodiments relate to a system for identifying member profiles containing disallowed content in an online social network. During operation, the system scans member profiles looking up words from one or more fields in “bad-word” and/or “good-word” dictionaries. These dictionaries were previously generated by examining member profiles that were judged by a human reviewer to be “good” profiles or “bad” profiles, and determining whether a word belongs in a specific dictionary based on frequencies of occurrence of the word in the good profiles and the bad profiles. Next, the system computes a score for each member profile based at least partially on occurrences of words from the dictionaries in the member profile. Finally, the system identifies a member profile as containing disallowed content based on the score.

Abstract: The disclosed embodiments provide a system for processing actions with a service. During operation, the system obtains a first attribute associated with a first cluster of entities identified as malicious to a service. Next, the system matches the first attribute to a second attribute of an entity in the first cluster. The system then uses the second attribute to identify a second cluster of entities as malicious to the service. Finally, the system uses cluster scores for identifying the first and second clusters of entities as malicious to the service to output responses to actions associated with entities in the first and second clusters of entities.

Abstract: Computerized methods enable automatic monitoring of requests to an online service and apply access restrictions, as appropriate, to servicing of requests in real-time or near real-time. For each request received by the online service, a plurality of parameters associated with the request are identified, and counters corresponding to the particular values of the plurality of parameters associated with the request are incremented to track the number of times a parameter value appears or occurs in connection with requests to the online service. A first level check or analysis is performed to determine whether a second level check or analysis is required. The first level check or analysis comprises an initial screening that is not computationally intensive. The second level check or analysis is more resource-intensive and is triggered depending on the outcome of the first level check or analysis.

Abstract: The disclosed embodiments relate to a system for identifying member profiles containing disallowed content in an online social network. During operation, the system scans member profiles looking up words from one or more fields in “bad-word” and/or “good-word” dictionaries. These dictionaries were previously generated by examining member profiles that were judged by a human reviewer to be “good” profiles or “bad” profiles, and determining whether a word belongs in a specific dictionary based on frequencies of occurrence of the word in the good profiles and the bad profiles. Next, the system computes a score for each member profile based at least partially on occurrences of words from the dictionaries in the member profile. Finally, the system identifies a member profile as containing disallowed content based on the score.