Abstract: The present disclosure relates to a network device that determines a persistent network identity for a networked device. Specifically, the network device receives a service request that includes an identifier for a second network device in a sub-network among a plurality of sub-networks. The identifier uniquely corresponds to the second network device during a limited period of time. At least one sub-networks are unreachable by the service request. The network device aggregates partial networked device profiles corresponding to the second network device received from other network devices in at least the at least one sub-networks to generate a networked device profile. Moreover, the network device searches at least one caches to obtain the networked device profile based on the identifier in the service request, and correlates the identifier to a persistent network identity corresponding to the second network device based on the networked device profile.

Abstract: Examples relate to handling network threats. In one example, a computing device may: receive, from a threat detector, threat data associated with a particular network device included in a plurality of network devices; identify, based on the threat data, a particular analytics operation for assisting with remediation of a threat associated with the threat data; identify, based on the threat data, additional data for performing the particular analytics operation; cause reconfiguration of at least one of the plurality of network devices, the reconfiguration causing each of the reconfigured network devices to i) collect the additional data, and ii) provide the additional data to an analytics device; and receive, from the analytics device, particular analytics results of the particular analytics operation.

Abstract: Examples relate to detecting network anomalies. In one example, a computing device may: receive, from each of a plurality of packet capture devices of a private network, domain name system (DNS) query packets that were sent by a particular client computing device operating on the private network, each DNS query packet specifying i) a destination DNS server, ii) a query domain name, and iii) a source address that specifies the particular client computing device; provide at least one of the DNS query packets to a DNS traffic analyzer that is trained to identify DNS anomalies based on characteristics of the DNS query packets; receive anomaly output from the DNS traffic analyzer, the anomaly output indicating a DNS anomaly that was identified for the DNS query packets; and in response to receiving the anomaly output, provide a user device with data specifying the identified DNS anomaly.

Abstract: Examples relate to collecting domain name system traffic. In one example, a computing device may: receive, from a first intermediary network device, a DNS query packet that was sent by a client computing device operating on a private network, the DNS query packet specifying i) a query domain name, and ii) a source address that specifies the client computing device; store, in a data storage device, a query record specifying the query domain name and the source address specified by the DNS query packet; receive, from a second intermediary network device, a DNS response packet; determine that the DNS response packet specifies a response domain name that matches the query domain name; in response to the determination, extract, from the DNS response packet, a resolved address that corresponds to the response domain name; and store, in the query record, the resolved address specified by the DNS response packet.

Abstract: Examples relate to dynamically adjusting a model for a security operations center (“SOC”). As such, the examples disclosed herein enable constructing a customer storage model over a set of time periods for a customer based on a set of resources of the SOC, a storage distribution model received from the customer related to expected usage of the set of resources, and a threat landscape for the customer. The customer storage model may be revised for a second time period based on actual storage use of the customer during a first time period, and a projection of an amount of data to be consumed in the second time period based on the threat landscape. Allocation of the resources in the SOC may be revised for the second time period based on the revision to the customer storage model.

Abstract: Remediating a security threat to a network includes obtaining, from a network, security information about the network to determine traffic patterns of the network, identifying, based on the traffic patterns of the network, a security threat to the network, determining, from a playbook library and a workflow library, a workflow template and at least one software-defined networking (SDN) flow rule template to remediate the security threat, and deploying, via a SDN controller, a SDN flow rule based on the at least one SDN flow rule template in the network to remediate the security threat by altering a control path of the network.

Abstract: Examples relate to handling network threats. In one example, a computing device may: receive, from a threat detector, threat data associated with a particular network device included in a plurality of network devices; identify, based on the threat data, a particular analytics operation for assisting with remediation of a threat associated with the threat data; identify, based on the threat data, additional data for performing the particular analytics operation; cause reconfiguration of at least one of the plurality of network devices, the reconfiguration causing each of the reconfigured network devices to i) collect the additional data, and ii) provide the additional data to an analytics device; and receive, from the analytics device, particular analytics results of the particular analytics operation.

Abstract: Examples relate to collecting domain name system traffic. In one example, a computing device may: receive, from a first intermediary network device, a DNS query packet that was sent by a client computing device operating on a private network, the DNS query packet specifying i) a query domain name, and ii) a source address that specifies the client computing device; store, in a data storage device, a query record specifying the query domain name and the source address specified by the DNS query packet; receive, from a second intermediary network device, a DNS response packet; determine that the DNS response packet specifies a response domain name that matches the query domain name; in response to the determination, extract, from the DNS response packet, a resolved address that corresponds to the response domain name; and store, in the query record, the resolved address specified by the DNS response packet.

Abstract: Examples relate to detecting network anomalies. In one example, a computing device may: receive, from each of a plurality of packet capture devices of a private network, domain name system (DNS) query packets that were sent by a particular client computing device operating on the private network, each DNS query packet specifying i) a destination DNS server, ii) a query domain name, and iii) a source address that specifies the particular client computing device; provide at least one of the DNS query packets to a DNS traffic analyzer that is trained to identify DNS anomalies based on characteristics of the DNS query packets; receive anomaly output from the DNS traffic analyzer, the anomaly output indicating a DNS anomaly that was identified for the DNS query packets; and in response to receiving the anomaly output, provide a user device with data specifying the identified DNS anomaly.

Abstract: Examples relate to dynamically adjusting a model for a security operations center (“SOC”). As such, the examples disclosed herein enable constructing a customer storage model over a set of time periods for a customer based on a set of resources of the SOC, a storage distribution model received from the customer related to expected usage of the set of resources, and a threat landscape for the customer. The customer storage model may be revised for a second time period based on actual storage use of the customer during a first time period, and a projection of an amount of data to be consumed in the second time period based on the threat landscape. Allocation of the resources in the SOC may be revised for the second time period based on the revision to the customer storage model.

Abstract: Remediating a security threat to a network includes obtaining, from a network, security information about the network to determine traffic patterns of the network, identifying, based on the traffic patterns of the network, a security threat to the network, determining, from a playbook library and a workflow library, a workflow template and at least one software-defined networking (SDN) flow rule template to remediate the security threat, and deploying, via a SDN controller, a SDN flow rule based on the at least one SDN flow rule template in the network to remediate the security threat by altering a control path of the network.

Abstract: Creating a security report for a customer network includes obtaining from a customer network, security information about the customer network, preparing, based on modification rules, the security information to create modified security information, analyzing, based on big data threat analytics, the security threats to create a number of metrics, refining the number of metrics using a refining model, creating, based on the refined number of metrics used as an input for model-based predictive analytics and the security threats, a security report representing security intelligence for the customer network in which the number of metrics are refined by a refining model and used as an input for the model-based predictive analytics.