Abstract: Disclosed herein are systems and methods for generating heuristic rules for identifying spam emails based on fields in headers of emails. In one aspect, an exemplary method comprises, collecting statistical data on contents of a plurality of emails; analyzing the statistical data to identify different types of content, including headers or hyperlinks in said emails; grouping the emails into clusters based on types of content identified in said emails, wherein at least one cluster group being based on fields in headers of said emails; generating a hash from the most frequent combination of group of data in each cluster; formulating regular expressions based on analysis of hyperlinks of emails corresponding to the generated hashes; and generating heuristic rule for identifying spam emails by combining the hashes and the corresponding regular expressions, wherein the hash is generated based on fields in the headers of said emails.

Abstract: Disclosed herein are systems and methods for generating heuristic rules for identifying spam emails based on fields in headers of emails. In one aspect, an exemplary method comprises, collecting statistical data on contents of a plurality of emails; analyzing the statistical data to identify different types of content, including headers or hyperlinks in said emails; grouping the emails into clusters based on types of content identified in said emails, wherein at least one cluster group being based on fields in headers of said emails; generating a hash from the most frequent combination of group of data in each cluster; formulating regular expressions based on analysis of hyperlinks of emails corresponding to the generated hashes; and generating heuristic rule for identifying spam emails by combining the hashes and the corresponding regular expressions, wherein the hash is generated based on fields in the headers of said emails.

Abstract: Disclosed herein are systems and methods for generating heuristic rules for identifying spam emails. In one aspect, an exemplary method comprises, collecting and analyzing statistical data on contents of a emails to identify different types of content, including headers or hyperlinks, grouping the emails into clusters based on identified types of content, at least one cluster including groups of fields in the headers of said emails, selecting at least one most frequent combination of groups of data in each cluster, generating a hash from the at least one most frequent combination of groups, formulating at least one regular expression based on an analysis of hyperlinks corresponding to the generated hashes, and generating at least one heuristic rule for identifying emails containing spam by combining at least one hash and the corresponding regular expression, wherein at least one hash is from sequences of fields in the headers of said emails.

Abstract: Disclosed herein are systems and methods for generating heuristic rules for identifying spam emails. In one aspect, an exemplary method comprises, collecting and analyzing statistical data on contents of a emails to identify different types of content, including headers or hyperlinks, grouping the emails into clusters based on identified types of content, at least one cluster including groups of fields in the headers of said emails, selecting at least one most frequent combination of groups of data in each cluster, generating a hash from the at least one most frequent combination of groups, formulating at least one regular expression based on an analysis of hyperlinks corresponding to the generated hashes, and generating at least one heuristic rule for identifying emails containing spam by combining at least one hash and the corresponding regular expression, wherein at least one hash is from sequences of fields in the headers of said emails.