FUZZY HASH OF BEHAVIORAL RESULTS
First Claim
1. A computerized method for classifying objects in a malware system, comprising:
- receiving, by a malicious content detection (MCD) system, an object to be classified;
detecting behaviors of the received object, wherein the behaviors are detected after processing the received object;
generating a fuzzy hash for the received object based on the detected behaviors;
comparing the fuzzy hash for the received object with a fuzzy hash of an object in a preexisting cluster to generate a similarity measure;
associating the received object with the preexisting cluster in response to determining that the similarity measure is above a predefined threshold value; and
reporting, via a communications interface, results of the association to a client device.
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Accused Products
Abstract
A computerized method is described in which a received object is analyzed by a malicious content detection (MCD) system to determine whether the object is malware or non-malware. The analysis may include the generation of a fuzzy hash based on a collection of behaviors for the received object. The fuzzy hash may be used by the MCD system to determine the similarity of the received object with one or more objects in previously classified/analyzed clusters. Upon detection of a “similar” object, the suspect object may be associated with the cluster and classified based on information attached to the cluster. This similarity matching provides 1) greater flexibility in analyzing potential malware objects, which may share multiple characteristics and behaviors but are also slightly different from previously classified objects and 2) a more efficient technique for classifying/assigning attributes to objects.
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Citations
24 Claims
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1. A computerized method for classifying objects in a malware system, comprising:
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receiving, by a malicious content detection (MCD) system, an object to be classified; detecting behaviors of the received object, wherein the behaviors are detected after processing the received object; generating a fuzzy hash for the received object based on the detected behaviors; comparing the fuzzy hash for the received object with a fuzzy hash of an object in a preexisting cluster to generate a similarity measure; associating the received object with the preexisting cluster in response to determining that the similarity measure is above a predefined threshold value; and reporting, via a communications interface, results of the association to a client device. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 14)
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11. A non-transitory storage medium including instructions that, when executed by one or more hardware processors, performs a plurality of operations, comprising:
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detecting behaviors of a received object, wherein the behaviors are detected after processing the received object; generating a fuzzy hash for the received object based on the detected behaviors; comparing the fuzzy hash for the received object with a fuzzy hash of an object in a preexisting cluster to generate a similarity measure; and associating the received object with the preexisting cluster in response to determining that the similarity measure is above a predefined threshold value. - View Dependent Claims (12, 13, 15, 16, 17, 18, 19)
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20. A system comprising:
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one or more hardware processors; a memory including one or more software modules that, when executed by the one or more hardware processors; detect behaviors of a received object, wherein the behaviors are detected after processing the received object; generate a fuzzy hash for the received object based on the detected behaviors; compare the fuzzy hash for the received object with a fuzzy hash of an object in a preexisting cluster to generate a similarity measure; and associate the received object with the preexisting cluster in response to determining that the similarity measure is above a predefined threshold value. - View Dependent Claims (21, 22, 23, 24)
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Specification