SYSTEM FOR RECLASSIFICATION OF ELECTRONIC MESSAGES IN A SPAM FILTERING SYSTEM
2 Assignments
0 Petitions
Accused Products
Abstract
A method for indicating probability of spam for email comprises tracking network traffic characteristics for the email, and comparing the tracked characteristics for the email to characteristics for email from trusted or known spam sources.
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Citations
25 Claims
- 1. (canceled)
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2. A computer implemented method for filtering emails on a server system having one or more processors and memory storing one or more programs for execution by the one or more processors, comprising:
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receiving an email to a recipient from a sender; identifying a spam probability of the email based at least in part on historical interactions between the recipient and the sender, wherein the historical interactions include interactions from an email application and one or more non-email applications including at least one of;
a file-sharing application and a collaboration application; andclassifying the email according the identified spam probability. - View Dependent Claims (3)
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7. A system, for filtering emails, comprising:
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at least one processor; and memory storing one or more programs to be executed by the at least one processor; the one or more programs comprising instructions for; receiving an email to a recipient from a sender; identifying a spam probability of the email based at least in part on historical interactions between the recipient and the sender, wherein the historical interactions include interactions from an email application and one or more non-email applications including at least one of;
a file-sharing application and a collaboration application; andclassifying the email according the identified spam probability. - View Dependent Claims (8, 9, 10, 11)
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12. A computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for:
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receiving an email to a recipient from a sender; identifying a spam probability of the email based at least in part on historical interactions between the recipient and the sender, wherein the historical interactions include interactions from an email application and one or more non-email applications including at least one of;
a file-sharing application and a collaboration application; andclassifying the email according the identified spam probability. - View Dependent Claims (13, 14, 15, 16)
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17. A computer implemented method for filtering emails on a server system having one or more processors and memory storing one or more programs for execution by the one or more processors, comprising:
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receiving an email to a recipient from a sender; tracking network traffic burstiness from the network associated with the sender, wherein network traffic burstiness corresponds to variations in email volume relative to time for the network; identifying a burstiness spam probability of the email based by comparing the network traffic burstiness to the burstiness of known trusted sources and the burstiness of known spam sources; and classifying the email at least in part based on the burstiness spam probability. - View Dependent Claims (18, 19)
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20. A system, for filtering emails, comprising:
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at least one processor; and memory storing one or more programs to be executed by the at least one processor; the one or more programs comprising instructions for; receiving an email to a recipient from a sender; tracking network traffic burstiness from the network associated with the sender, wherein network traffic burstiness corresponds to variations in email volume relative to time for the network; identifying a burstiness spam probability of the email based by comparing the network traffic burstiness to the burstiness of known trusted sources and the burstiness of known spam sources; and classifying the email at least in part based on the burstiness spam probability. - View Dependent Claims (21, 22)
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23. A computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for:
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receiving an email to a recipient from a sender; tracking network traffic burstiness from the network associated with the sender, wherein network traffic burstiness corresponds to variations in email volume relative to time for the network; identifying a burstiness spam probability of the email based by comparing the network traffic burstiness to the burstiness of known trusted sources and the burstiness of known spam sources; and classifying the email at least in part based on the burstiness spam probability. - View Dependent Claims (24, 25)
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Specification