Determining a reputation of a network entity
An example method can include monitoring a network to identify flows between nodes in the network. Once flows have been identified, the flows can be tagged and labelled according to the type of traffic they represent. If a flow represents malicious or otherwise undesirable traffic, it can be tagged accordingly. A request can then be made for a reputation score of an entity which can identify one or more nodes of the network.
1. A computer-implemented method, comprising:
identifying a type of traffic for one or more flows associated with one or more nodes;
determining a reputation score of one or more nodes based on the type of traffic through the one or more nodes; and
blocking a node of the one or more nodes from sending traffic in response to the reputation score for that node being below a predetermined threshold;
wherein the reputation score is calculated by:
Reputation Score=Σ i= 1 n Value i +(Recovery i *[TimecurrentTime i ])
where:
n is the number of events identified during the identifying;
Value i is an initial relative impact of the type of traffic of an ith event on the reputation score, where Value i is different for at least two different values of i;
Recovery i is a constant for the type of traffic of the ith event, wherein the Recovery for at least one event is non-zero, and the recovery for at least one other event is zero;
TiMe current is a time value based on a current time;
Time i is a time value based on a time of the ith event.
2. The computer-implemented method of claim 1 , further comprising, before the determining, analyzing network traffic data to classify a type of traffic for each flow of a plurality of flows.
3. The computer-implemented method of claim 2 , wherein analyzing the network traffic data to classify a type of traffic for each flow includes:
matching the flow to a known pattern of traffic.
4. The computer-implemented method of claim 3 , wherein the known pattern of traffic corresponds to at least one of a DDOS attack, a FIN scan, or a port knock.
5. The computer-implemented method of claim 2 , wherein analyzing the network traffic data to classify a type of traffic for each flow includes:
identifying one or more network policies associated with the flow; and
determining whether the flow complies with the one or more network policies.
6. The computer-implemented method of claim 1 , wherein the reputation score is associated with at least one of an endpoint, an endpoint group, a pair of endpoints, a pair of endpoint groups, an endpoint and an endpoint group, a user name for a process, a process, or a path for a process of a network.
7. The computer-implemented method of claim 1 , wherein determining the reputation score includes:
determining at least one of the one or more flows is tagged as malicious or misconfigured; and
decreasing the reputation score.
8. A non-transitory computer readable media storing instructions which when executed by a system cause the system to perform operations comprising:
identifying a type of traffic for one or more flows associated with one or more nodes;
determining a reputation score of one or more nodes based on the type of traffic through the one or more nodes; and
blocking a node of the one or more nodes from sending traffic in response to the reputation score for that node being below a predetermined threshold;
wherein the reputation score is calculated by:
Reputation Score=Σ i= 1 n Value i +(Recovery i *[Timecurrent−Time i ])
where:
n is the number of events identified during the identifying;
Value i is an initial relative impact of the type of traffic of an ith event on the reputation score, where Value i is different for at least two different values of i;
Recovery i is a constant for the type of traffic of the ith event, wherein the Recovery for at least one event is non-zero, and the recovery for at least one other event is zero;
Time current is a time value based on a current time; Time i is a time value based on a time of the ith event.
9. The media of claim 8 , the operations further comprising, before the determining, analyzing network traffic data to classify a type of traffic for each flow of a plurality of flows.
10. The media of claim 9 , wherein analyzing network traffic data to classify a type of traffic for each flow includes: matching the flow to a known pattern of traffic.
11. The media of claim 10 , wherein the known pattern of traffic corresponds to at least one of a DDOS attack, a FIN scan, or a port knock.
12. The media of claim 8 , wherein analyzing network traffic data to classify a type of traffic for each flow includes:
identifying one or more network policies associated with the flow; and
determining whether the flow complies with the one or more network policies.
13. The media of claim 8 , wherein the reputation score is associated with at least one of an endpoint, an endpoint group, a pair of endpoints, a pair of endpoint groups, an endpoint and an endpoint group, a user name for a process, a process, or a path for a process of a network.
14. The media of claim 8 , wherein determining the reputation score includes:
determining at least one of the one or more flows is tagged as malicious or misconfigured; and
decreasing the reputation score.
15. A system, comprising:
a non-transitory computer readable media storing instructions;
a processor programmed to execute the instructions to perform operations comprising:
identifying a type of traffic for one or more flows associated with one or more;
determining a reputation score of one or more nodes based on the type of traffic through the one or more nodes; and
blocking a node of the one or more nodes from sending traffic in response to the reputation score for that node being below a predetermined threshold;
wherein the reputation score is calculated by:
Reputation Score=Σ i= 1 n Value i +(Recovery i *[Timecurrent−Time i ])
where:
n is the number of events identified during the identifying;
Value i is an initial relative impact of the type of traffic of an ith event on the reputation score, where Value i is different for at least two different values of i;
Recovery i is a constant for the type of traffic of the ith event, wherein the Recovery for at least one event is non-zero, and the recovery for at least one other event is zero;
Time current is a time value based on a current time;
Time i is a time value based on a time of the ith event.
16. The system of claim 15 , the operations further comprising, before the determining, analyzing network traffic data to classify a type of traffic for each flow of a plurality of flows.
17. The system of claim 16 , wherein analyzing the network traffic data to classify a type of traffic for each flow includes:
matching the flow to a known pattern of traffic.
18. The system of claim 17 , wherein the known pattern of traffic corresponds to at least one of a DDOS attack, a FIN scan, or a port knock.
19. The system of claim 16 , wherein analyzing the network traffic data to classify a type of traffic for each flow includes:
identifying one or more network policies associated with the flow; and
determining whether the flow complies with the one or more network policies.
20. The system of claim 15 , wherein the reputation score is associated with at least one of an endpoint, an endpoint group, a pair of endpoints, a pair of endpoint groups, an endpoint and an endpoint group, a user name for a process, a process, or a path for a process of a network.