Abstract: A system and method comprising: receiving network flow data; identifying a peer to peer network flow within the network flow data comparing the peer to peer network flow to a known peer to peer application flow; labeling the peer to peer network flow as the known peer to peer application flow when the peer to peer network flow matches the known peer to peer application flow; and creating a data set to be associated with the labeled peer to flow.

Abstract: A method and system for detecting a malicious domain name, comprising: collecting domain name statistical information from a non-recursive domain name system name server (RDNS NS); and utilizing the collected domain name statistical information to determine if a domain name is malicious or benign.

Abstract: A system and method of analysis. NX domain names are collected from an asset in a real network. The NX domain names are domain names that are not registered. The real network NX domain names are utilized to create testing vectors. The testing vectors are classified as benign vectors or malicious vectors based on training vectors. The asset is then classified as infected if the NX testing vector created from the real network NX domain names is classified as a malicious vector.

Abstract: System and method for detecting a domain generation algorithm (DGA), comprising: performing processing associated with clustering, utilizing a name-based features clustering module accessing information from an electronic database of NX domain information, the randomly generated domain names based on the similarity in the make-up of the randomly generated domain names; performing processing associated with clustering, utilizing a graph clustering module, the randomly generated domain names based on the groups of assets that queried the randomly generated domain names; performing processing associated with determining, utilizing a daily clustering correlation module and a temporal clustering correlation module, which clustered randomly generated domain names are highly con-elated in daily use and in time; and performing processing associated with determining the DGA that generated the clustered randomly generated domain names.

Abstract: A computerized system and method for performing behavioral clustering of malware samples, comprising: executing malware samples in a controlled computer environment fbr a predetermined time to obtain HTTP traffic; clustering the malware samples into at least one cluster based on network behavioral information from the HTTP traffic; and extracting, using the at least one processor, network signatures from the HTTP traffic information for each cluster, the network signatures being indicative of malware infection.

Abstract: A system and method for detecting a first network of compromised computers in a second network of computers, comprising: collecting Domain Name System (DNS) data for the second network; examining the collected data relative to DNS data from known comprised and/or uncompromised computers in the second network; and determining the existence of the first network and/or the identity of compromised computers in the second network based on the examination.