Abstract: A computer-implemented method for generating a first set of longest common sequences from a plurality of known malicious webpages, the first set of longest common sequences representing input data from which a human generates a set of regular expressions for detecting phishing webpages. There is included obtaining HTML source strings from the plurality of known malicious webpages and transforming the HTML source strings to reduce the number of at least one of stop words and repeated tags, thereby obtaining a set of transformed source strings. There is further included performing string alignment on the set of transformed source strings, thereby obtaining at least a scoring matrix. There is additionally included obtaining a second set of longest common sequences responsive to the performing the string alignment. There is further included filtering the second set of longest common sequences, thereby obtaining the first set of longest common sequences.

Abstract: A computer-implemented method for generating a first set of longest common sequences from a plurality of known malicious webpages, the first set of longest common sequences representing input data from which a human generates a set of regular expressions for detecting phishing webpages. There is included obtaining HTML source strings from the plurality of known malicious webpages and transforming the HTML source strings to reduce the number of at least one of stop words and repeated tags, thereby obtaining a set of transformed source strings. There is further included performing string alignment on the set of transformed source strings, thereby obtaining at least a scoring matrix. There is additionally included obtaining a second set of longest common sequences responsive to the performing the string alignment. There is further included filtering the second set of longest common sequences, thereby obtaining the first set of longest common sequences.

Abstract: Protecting computer users from online frauds, such as phishing and pharming. A client computer may include a page signature extractor and a policy enforcer. The page signature extractor may encode a web page to generate its signature, which may be provided to a remote server computer for comparison with signatures of phishing pages. The client computer and the server computer may communicate using the DNS protocol. The policy enforcer may perform one or more predetermined actions when a match is found. Examples of such actions include replacing the web page with a blocking page, displaying a warning message, or both. The policy enforcer may be configured to determine if the web page is part of a phishing or pharming attack by comparing the URL of the web page to URLs of legitimate web pages.