1. A computerized method for performing behavioral clustering of malware samples, comprising: executing malware samples in a controlled computer environment for a predetermined time to obtain HTTP traffic; clustering, using at least one processing device, the malware samples into at least one coarse-grain cluster based on network behavioral information measured from content of the HTTP traffic; splitting, using the at least one processing device, the at least one coarse-grain cluster into at least two fine-grain cluster; clustering, using the at least one processing device, the at least two fine-grain cluster into merged clusters; and extracting, using the at least one processing device, network signatures from the HTTP traffic information for each merged cluster, the network signatures being indicative of malware infection.