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US 7,406,503 B1Granted
Dictionary attack e-mail identification
AssigneeMicrosoft Corporation
InventorsCharles Reeves Little, II, Eric L. Eilebrecht
Life of this patent
Estimating the term…
Abstract
User IDs in addresses to which an e-mail is addressed are logically ordered into a 2D matrix of rows each having one user ID. For each column in the 2D matrix, a column count is found by counting the highest number of matching characters in the column. A column quotient is calculated for each column by dividing the column count by the total number of rows in the 2D matrix. A weighted column quotient is calculated for each column by multiplying the column quotient by a weight that is based on the left-to-right order of the column in the 2D matrix. A numerical assessment is made of the similarity of the user IDs in the addresses to which the e-mail is addressed by adding up the weighted column quotients for the columns in the 2D matrix.
Claims58
A method comprising:
- assessing the similarity of addresses to which an e-mail is addressed wherein the assessment comprises assessing the similarity of the user IDs of the addresses wherein the assessment of the similarity of the user IDs is weighted heavier for the leftmost characters of the User IDs than for the rightmost characters of the User IDs, the weight decreasing from left to right for each character of the user IDs wherein differences in weight between the character positions is non-linear;
- and
- deriving a spam value from the assessment.
A method comprising:
- columnizing, in left-to-right order, the characters in the respective user IDs in a plurality of addresses to which an electronic mail (e-mail) is addressed;
- for each said column:
- counting the highest number of identical characters to arrive at a repeat total for the column;
- dividing the repeat total by the number of addresses to which the e-mail is addressed to arrive at a quotient;
- and
- weighting the quotient by a factor according to the relative left-to-right order of the column to arrive at a weighted quotient;
- summing the weighted quotients for the columns to arrive at a first spam value.
4 more elements
A method comprising, for each of a plurality of untransmitted e-mails, the steps of:
- (a) columnizing, in left-to-right order, the characters in the respective user IDs in a plurality of addresses to which the untransmitted e-mail is addressed;
- (b) for each said column:
- counting the highest number of identical characters to arrive at a repeat total for the column;
- dividing the repeat total by the number of addresses to which the untransmitted e-mail is addressed to arrive at a quotient;
- and
- weighting the quotient by a factor according to the relative left-to-right order of the column to arrive at a weighted quotient;
- (c) summing the weighted quotients for the columns to arrive at a first spam value;
- (d) altering one or more of the user IDs in the addresses to which the untransmitted e-mail is addressed;
- and
- (e) repeating the steps (a) through (d) until the first spam value is outside of a predetermined range of values.
7 more elements
A method comprising:
- columnizing, in left-to-right order, the characters in the respective user IDs in a plurality of addresses to which an e-mail is addressed;
- for each said column:
- counting the highest number of identical characters to arrive at a repeat total for the column;
- dividing the repeat total by the number of addresses to which the e-mail is addressed to arrive at a quotient;
- and
- weighting the quotient by a factor according to the relative left-to-right order of the column to arrive at a weighted quotient;
- summing the weighted quotients for the columns to arrive at a first confidence level assessment as to whether the e-mail is spam;
- performing one or more other confidence level assessments that each assess whether the e-mail is spam;
- using each of the first and other confidence level assessments to arrive at a final spam value;
- and
- determining, based upon the final spam value, whether to deliver the e-mail to any said address.
8 more elements
For the user IDs in a plurality of addresses to which an e-mail is addressed, the user IDs being logically ordered into a two dimensional (2D) matrix of rows each having one said user ID, a method comprising:
- for each column in the 2D matrix:
- finding a column count by counting the highest number of matching characters in the column;
- calculating a column quotient by dividing the column count by the total number of rows in the 2D matrix;
- and
- calculating a weighted column quotient by multiplying the column quotient by a weight that is based on the left-to-right order of the column in the 2D matrix;
- calculating a numerical assessment of the similarity of the user IDs in the plurality of addresses to which the e-mail is addressed by adding up the weighted column quotients for the columns in the 2D matrix.
3 more elements
A method comprising, for each of a plurality of untransmitted e-mails, the steps of:
- for the user IDs in a plurality of addresses to which the untransmitted e-mail is addressed, the user IDs being logically ordered into a two dimensional (2D) matrix of rows each having one said user ID, for each column in the 2D matrix:
- (i) finding a column count by counting the highest number of matching characters in the column;
- (ii) calculating a column quotient by dividing the column count by the total number of rows in the 2D matrix;
- (iii) calculating a weighted column quotient by multiplying the column quotient by a weight that is based on the left-to-right order of the column in the 2D matrix;
- (iv) calculating a numerical assessment of the similarity of the user IDs in the plurality of addresses to which the e-mail is addressed by adding up the weighted column quotients for the columns in the 2D matrix,
- (v) altering one or more of the user IDs in the addresses to which the untransmitted e-mail is addressed;
- and
- (vi) repeating the steps (i) through (v) until the numerical assessment is outside of a predetermined range of values.
5 more elements
For the user IDs in a plurality of addresses to which an e-mail is addressed, the user IDs being logically ordered into a two dimensional (2D) matrix of rows each having one said user ID, a method comprising:
- for each column in the 2D matrix:
- finding a column count by counting the highest number of matching characters in the column;
- calculating a column quotient by dividing the column count by the total number of rows in the 2D matrix;
- and
- calculating a weighted column quotient by multiplying the column quotient by a weight that is based on the left-to-right order of the column in the 2D matrix;
- calculating a first confidence level assessment as to whether the e-mail is spam by adding up the weighted column quotients for the columns in the 2D matrix;
- performing one or more other confidence level assessments that each assess whether the e-mail is spam;
- using each of the first and other confidence level assessments to arrive at a final spam assessment;
- and
- determining, based upon the final spam assessment, whether to deliver the e-mail to any said address.
7 more elements
A method comprising:
- for the respective user IDs in a plurality of addresses to which an e-mail is addressed, where the characters of the respective user IDs are logically and collectively columnized, deriving a numerical expression of the degree of repetition of the most common character for each column;
- and
- weighting the numerical expression for each column by a respective weight for each column to obtain respective weighted column values, wherein the respective weight for each column is selected such that the sum of the weighted column values is equal to a confidence level of about 100 percent (100%) when the user IDs in the plurality of addresses are identical.
A method comprising:
- generating logically columnized user IDs;
- deriving a numerical expression of the degree of repetition of the most common character for each column;
- weighting the numerical expression for each column by a respective weight for each column to obtain respective weighted column values, wherein the respective weight for each column is selected such that the sum of the weighted column values is equal to a confidence level of about 100 percent (100%) when the user IDs are identical;
- if the confidence level is above a predetermined percentage, repeating the deriving and weighting using an alteration of the user IDs until the confidence level is below the predetermined percentage;
- dividing the user IDs into respective groups;
- and
- for each group, forming an e-mail and a respective e-mail address for each user ID in the group.
4 more elements
Dependencies are inferred from the claim text.