Intelligent SPAM detection system using statistical analysis
First Claim
Patent Images
1. A method for detecting an unwanted message, comprising:
- (a) receiving an electronic mail message;
(b) decomposing text in the electronic mail message;
(c) gathering statistics associated with the text using a statistical analyzer; and
(d) analyzing the statistics for determining whether the electronic mail message is an unwanted message;
wherein the statistics gathered using the statistical analyzer include results of an analysis of a uniform resource locator (URL) in the electronic mail message text;
wherein the statistics gathered using the statistical analyzer include results of an analysis of e-mail addresses in the electronic mail message text;
wherein the statistics gathered using the statistical analyzer include results of a message header field analysis;
wherein the statistics are sent to a neural network engine, wherein the neural network engine compares the statistics to predetermined weights for determining whether the electronic mail message is an unwanted message;
wherein the neural network engine is taught to recognize unwanted messages;
wherein examples are provided to the neural network engine, wherein the examples are of wanted messages and unwanted messages, and each of the examples is associated with a desired output;
wherein each of the examples are processed by the neural network engine for generating the weights, wherein each of the weights is used to denote wanted and unwanted messages;
wherein the neural network engine utilizes an adaptive linear combination for adjusting the weights.
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Abstract
A system, method and computer program product are provided for detecting an unwanted message. First, an electronic mail message is received. Text in the electronic mail message is decomposed. Statistics associated with the text are gathered using a statistical analyzer. The statistics are analyzed for determining whether the electronic mail message is an unwanted message.
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Citations
31 Claims
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1. A method for detecting an unwanted message, comprising:
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(a) receiving an electronic mail message; (b) decomposing text in the electronic mail message; (c) gathering statistics associated with the text using a statistical analyzer; and (d) analyzing the statistics for determining whether the electronic mail message is an unwanted message; wherein the statistics gathered using the statistical analyzer include results of an analysis of a uniform resource locator (URL) in the electronic mail message text; wherein the statistics gathered using the statistical analyzer include results of an analysis of e-mail addresses in the electronic mail message text; wherein the statistics gathered using the statistical analyzer include results of a message header field analysis; wherein the statistics are sent to a neural network engine, wherein the neural network engine compares the statistics to predetermined weights for determining whether the electronic mail message is an unwanted message; wherein the neural network engine is taught to recognize unwanted messages; wherein examples are provided to the neural network engine, wherein the examples are of wanted messages and unwanted messages, and each of the examples is associated with a desired output; wherein each of the examples are processed by the neural network engine for generating the weights, wherein each of the weights is used to denote wanted and unwanted messages; wherein the neural network engine utilizes an adaptive linear combination for adjusting the weights. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A computer program product having computer-executable codes embodied in a computer-readable medium for detecting an unwanted message, comprising:
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(a) computer code for receiving an electronic mail message; (b) computer code for decomposing text in the electronic mail message; (c) computer code for gathering statistics associated with the text using a statistical analyzer; and (d) computer code for analyzing the statistics for determining whether the electronic mail message is an unwanted message; wherein the statistics gathered using the statistical analyzer include results of an analysis of a uniform resource locator (URL) in the electronic mail message text; wherein the statistics gathered using the statistical analyzer include results of an analysis of e-mail addresses in the electronic mail message text; wherein the statistics gathered using the statistical analyzer include results of a message header field analysis; wherein the statistics gathered using the statistical analyzer include results of an analysis of a uniform resource locator (URL) in the electronic mail message text; wherein the statistics gathered using the statistical analyzer include results of an analysis of e-mail addresses in the electronic mail message text; wherein the statistics gathered using the statistical analyzer include results of a message header field analysis; wherein the statistics are sent to a neural network engine, wherein the neural network engine compares the statistics to predetermined weights for determining whether the electronic mail message is an unwanted message; wherein the neural network engine is taught to recognize unwanted messages; wherein examples are provided to the neural network engine, wherein the examples are of wanted messages and unwanted messages, and each of the examples is associated with a desired output; wherein each of the examples are processed by the neural network engine for generating the weights, wherein each of the weights is used to denote wanted and unwanted messages; wherein the neural network engine utilizes an adaptive linear combination for adjusting the weights. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21)
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22. A system for detecting an unwanted message, comprising:
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(a) a statistical analyzer for gathering statistics associated with text retrieved from an electronic mail message; and (b) a neural network engine coupled to the statistical analyzer for analyzing the statistics; (c) wherein the neural network engine determines whether the electronic mail message is an unwanted message; wherein the statistics gathered using the statistical analyzer include results of an analysis of a uniform resource locator (URL) in the electronic mail message text; wherein the statistics gathered using the statistical analyzer include results of an analysis of e-mail addresses in the electronic mail message text; wherein the statistics gathered using the statistical analyzer include results of a message header field analysis; wherein the statistics gathered using the statistical analyzer include results of an analysis of a uniform resource locator (URL) in the electronic mail message text; wherein the statistics gathered using the statistical analyzer include results of an analysis of e-mail addresses in the electronic mail message text; wherein the statistics gathered using the statistical analyzer include results of a message header field analysis; wherein the statistics are sent to the neural network engine, wherein the neural network engine compares the statistics to predetermined weights for determining whether the electronic mail message is an unwanted message; wherein the neural network engine is taught to recognize unwanted messages; wherein examples are provided to the neural network engine, wherein the examples are of wanted messages and unwanted messages, and each of the examples is associated with a desired output; wherein each of the examples are processed by the neural network engine for generating the weights, wherein each of the weights is used to denote wanted and unwanted messages; wherein the neural network engine utilizes an adaptive linear combination for adjusting the weights. - View Dependent Claims (23, 24, 25, 26, 27, 28, 29, 30)
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31. A method for detecting an unwanted message, comprising:
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(a) receiving an electronic mail message; (b) decomposing text in the electronic mail message; (c) gathering statistics associated with the text using a statistical analyzer, wherein the statistics gathered using the statistical analyzer include at least three of a ratio of words capitalized to total number of words, a punctuation to word ratio, a number of URLs in the text, a telephone number in the text, results of an analysis of a uniform resource locator (URL) in the electronic mail message text, results of an analysis of e-mail addresses in the electronic mail message text, results of an analysis of character type, and results of a message header field analysis; and (d) analyzing the statistics for determining whether the electronic mail message is an unwanted message; wherein the statistics gathered using the statistical analyzer include results of an analysis of a uniform resource locator (URL) in the electronic mail message text; wherein the statistics gathered using the statistical analyzer include results of an analysis of e-mail addresses in the electronic mail message text; wherein the statistics gathered using the statistical analyzer include results of a message header field analysis; wherein the statistics are sent to a neural network engine, wherein the neural network engine compares the statistics to predetermined weights for determining whether the electronic mail message is an unwanted message; wherein the neural network engine is taught to recognize unwanted messages; wherein examples are provided to the neural network engine, wherein the examples are of wanted messages and unwanted messages, and each of the examples is associated with a desired output; wherein each of the examples are processed by the neural network engine for generating the weights, wherein each of the weights is used to denote wanted and unwanted messages; wherein the neural network engine utilizes an adaptive linear combination for adjusting the weights.
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Specification