Spam filter
Detection of undesired electronic communication, such as spam emails, by comparing the email with a list of likely spam words and establishing the communication as undesired when the words in the list, are substantially present in the email, even if not completely present. For example, the match is close enough if the words have similar letters in similar orders, but with other letters separating them. Another aspect matches the words with a dictionary or rules defining spelling for the language. Emails with too high a percentage of garbage words are marked as undesirable.
1 . A system, comprising:
a first part for receiving an electronic communication; and
a second part for testing said electronic communication to determine if said electronic communication is undesired based on the presence of specified electronic content, wherein said electronic content includes specified words with letters in specified orders forming a specified letter order, wherein said testing comprises determining that specified undesired electronic content is present if 80% or more, but less than 100%, of the specified letter order is present within the electronic communication.
2 . A system as in claim 1 , wherein said testing comprises storing a list of undesired electronic content, and said determining comprises comparing the electronic communication with words in the list, and establishing undesired electronic content as present when only a portion of a word less than the entire word in the electronic communication matches with a corresponding portion of a word on the list.
3 . A system as in claim 2 , wherein said list of undesired electronic content is a list of content which is commonly present in undesired communication, where said content includes at least one of words or phrases, and said testing comprises determining if said content is substantially present in the electronic communication, and establishing said communication as undesirable when only a portion of said content less than the entire content is present and when the exact content is not present.
4 . A system as in claim 3 , wherein said establishing comprises establishing a word within the content as present even when there is a wrong character or missed character in the word.
5 . (canceled)
6 . (canceled)
7 . A system as in claim 2 , wherein said establishing comprises determining whether a word is present with a typographical error therein.
8 . A system as in claim 1 , wherein said second part operates to determine words within the electronic communication which are not within a language of the electronic communication, and to establish the communication as undesired when too high a percentage of said words which are not within the language are detected.
9 . A system as in claim 8 , wherein the second part detects the words that are not within the language by comparing it with a dictionary.
10 . A method, comprising:
receiving an electronic communication;
detecting the presence of words which are not in a language of the electronic communication; and
determining the electronic communication is undesirable by determining that there are words which are not in the language of the electronic communication, and using the existence of said words which are not in the language of the communication to establish that said communication is undesirable.
11 . (canceled)
12 . A method as in claim 10 , wherein said determining comprises comparing said words which are not in the language with words which represent likely undesired electronic communications, and determining substantial similarities therebetween.
13 . A method as in claim 12 , wherein said substantial similarities comprise determining whether specified letter order is present but separated
14 . A method as in claim 12 , wherein said substantial similarities comprise detecting a single wrong character or single missed character in each word.
15 . A method as in claim 10 , wherein said detecting comprises comparing the words with a dictionary.
16 . A method as in claim 10 , wherein said detecting comprises comparing the words with rules that are based on a spelling rule of the language.
17 . A method, comprising:
receiving an electronic communication;
comparing words within the electronic communication with a list of words that represent at least one of words or phrases that are likely to represent undesired electronic communication; and
establishing the electronic communication is likely being undesirable when either (a) the words match the list of words, or (b) when the words do not match the list of words but differ therefrom only by a specified percentage less than 100%.
18 . (canceled)
19 . A method as in claim 17 , wherein said establishing comprises using a specified percentage of substantially 80%.