A method of detecting command and control behavior of malware on a client computer, the method comprising: monitoring, by one or more data processors, one or more domain name system, DNS, messages from one or more client computers to a DNS server to determine a risk that one or more client computers is communicating with a botnet, each of the one or more client computers having an IP address; characterized in further comprising: generating, by one or more data processors, real-time entity profiles for at least one of each of the one or more client computers, the real-time entity profiles including: DNS domain query names, resolved IP addresses of query domain names, client computer-query domain name pairs, pairs of query domain name and corresponding resolved IP address, and query domain name-IP address cliques based on each of the one or more DNS messages; determining, by one or more data processors using the real-time entity profiles, a risk that any of the one or more client computers is infected by malware that utilizes DNS messages for command and control or illegitimate data transmission purposes; and generating, by one or more data processors using real-time calibration profiles to determine the risk, one or more scores representing probabilities that one or more client computers is infected by malware associated with the botnet, aggregating the monitoring from two or more monitoring systems to generate aggregated entity profiles, the aggregating including aggregating one or more of transaction histories associated with the one or more DNS messages, real-time entity profiles and one or more generated scores; and generating aggregated scores based on the aggregated entity profiles. monitoring, by one or more data processors, one or more domain name system, DNS, messages from one or more client computers to a DNS server to determine a risk that one or more client computers is communicating with a botnet, each of the one or more client computers having an IP address; characterized in further comprising: generating, by one or more data processors, real-time entity profiles for at least one of each of the one or more client computers, the real-time entity profiles including: DNS domain query names, resolved IP addresses of query domain names, client computer-query domain name pairs, pairs of query domain name and corresponding resolved IP address, and query domain name-IP address cliques based on each of the one or more DNS messages; determining, by one or more data processors using the real-time entity profiles, a risk that any of the one or more client computers is infected by malware that utilizes DNS messages for command and control or illegitimate data transmission purposes; and generating, by one or more data processors using real-time calibration profiles to determine the risk, one or more scores representing probabilities that one or more client computers is infected by malware associated with the botnet, aggregating the monitoring from two or more monitoring systems to generate aggregated entity profiles, the aggregating including aggregating one or more of transaction histories associated with the one or more DNS messages, real-time entity profiles and one or more generated scores; and generating aggregated scores based on the aggregated entity profiles. generating, by one or more data processors, real-time entity profiles for at least one of each of the one or more client computers, the real-time entity profiles including: DNS domain query names, resolved IP addresses of query domain names, client computer-query domain name pairs, pairs of query domain name and corresponding resolved IP address, and query domain name-IP address cliques based on each of the one or more DNS messages; determining, by one or more data processors using the real-time entity profiles, a risk that any of the one or more client computers is infected by malware that utilizes DNS messages for command and control or illegitimate data transmission purposes; and generating, by one or more data processors using real-time calibration profiles to determine the risk, one or more scores representing probabilities that one or more client computers is infected by malware associated with the botnet, aggregating the monitoring from two or more monitoring systems to generate aggregated entity profiles, the aggregating including aggregating one or more of transaction histories associated with the one or more DNS messages, real-time entity profiles and one or more generated scores; and generating aggregated scores based on the aggregated entity profiles.