Abstract: The filtering of activities generated by nodes of a network while interacting with a device may be performed by evaluating the desirability of the activities (e.g., a spam or not-spam determination of email messages sent by the node) and assigning a trust rating to the node. However, nodes are often identified by network address, and an operator of a node sending undesirable activities may reassign the network address of the node in order to avoid heavy filtering. Instead, nodes may be identified as being controlled by a network entity (e.g., an autonomous system identified in a border gateway protocol routing table.) The network entity is assigned a network entity trust rating based on the trust ratings of the nodes controlled thereby, and an appropriate level of activity filtering based on the network entity trust rating may be selected for subsequent activities received from all nodes controlled by the network entity.

Abstract: Network entities controlling a set of nodes may vary by trustworthiness, such as tolerance for nodes that send spam, distribute malware, or perform denial-of-service attacks. A device receiving such activities may identify a trust rating of the network entity and apply appropriately stringent filtering (such as spam evaluation) to activities received from nodes controlled by the network entity. However, a poor trust rating of a network entity may subject a legitimate node controlled by the network entity to inefficiently or unfairly stringent activity filtering. Instead, the device may evaluate the activities of a particular node, assign a trust rating to the node, and if the trust rating of the node is higher than the trust rating of the network entity, apply less stringent activity filtering to the activities of the node, thereby “rescuing” the node from the more stringent activity filtering applied to the other nodes of the network entity.

Abstract: One or more techniques and/or systems are provided for identifying abusive message objects (e.g., URLs, email addresses, etc.), abusive infrastructure components and/or abusive users of a message communication medium(s). In particular, abusive message objects may be identified by aggregating abuse reports to assign abuse values to message objects used within messages by reported users identified within the abuse reports. Abusive users may be identified based upon (e.g., unreported) users that have sent messages comprising message objects identified as abusive. Users may also be identified as abusive users based upon account usage patterns within the message communication medium(s) (e.g., a broadcast usage pattern where a user sends a large number of messages, but receives few responses). Additionally, infrastructure components associated with abusive users may be identified as abusive infrastructure components.

Abstract: The filtering of activities generated by nodes of a network while interacting with a device may be performed by evaluating the desirability of the activities (e.g., a spam or not-spam determination of email messages sent by the node) and assigning a trust rating to the node. However, nodes are often identified by network address, and an operator of a node sending undesirable activities may reassign the network address of the node in order to avoid heavy filtering. Instead, nodes may be identified as being controlled by a network entity (e.g., an autonomous system identified in a border gateway protocol routing table.) The network entity is assigned a network entity trust rating based on the trust ratings of the nodes controlled thereby, and an appropriate level of activity filtering based on the network entity trust rating may be selected for subsequent activities received from all nodes controlled by the network entity.

Abstract: Network entities controlling a set of nodes may vary by trustworthiness, such as tolerance for nodes that send spam, distribute malware, or perform denial-of-service attacks. A device receiving such activities may identify a trust rating of the network entity and apply appropriately stringent filtering (such as spam evaluation) to activities received from nodes controlled by the network entity. However, a poor trust rating of a network entity may subject a legitimate node controlled by the network entity to inefficiently or unfairly stringent activity filtering. Instead, the device may evaluate the activities of a particular node, assign a trust rating to the node, and if the trust rating of the node is higher than the trust rating of the network entity, apply less stringent activity filtering to the activities of the node, thereby “rescuing” the node from the more stringent activity filtering applied to the other nodes of the network entity.