Techniques for scam detection and prevention
First Claim
1. A computer-implemented method, comprising:
- generating a scam message example repository;
submitting the scam message example repository to a natural-language machine learning component, the natural-language machine learning component to generate a scam message model from the example repository using a message content reuse measure, the content reuse measure to compare a user'"'"'s reuse of a phrase to the reuse of the phrase in a random message sample;
receiving a scam message model from the natural-language machine learning component in response to submitting the scam message example repository;
monitoring a plurality of messaging interactions with a messaging system based on the scam message model;
determining a suspected scam messaging interaction of the plurality of messaging interactions; and
performing a suspected scam messaging action with the messaging system in response to determining the suspected scam messaging interaction.
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Abstract
Techniques for scam detection and prevention are described. In one embodiment, an apparatus may comprise an interaction processing component operative to generate a scam message example repository; submit the scam message example repository to a natural-language machine learning component; and receive a scam message model from the natural-language machine learning component in response to submitting the scam message example repository; an interaction monitoring component operative to monitor a plurality of messaging interactions with a messaging system based on the scam message model; and determine a suspected scam messaging interaction of the plurality of messaging interactions; and a scam action component operative to perform a suspected scam messaging action with the messaging system in response to determining the suspected scam messaging interaction. Other embodiments are described and claimed.
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Citations
20 Claims
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1. A computer-implemented method, comprising:
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generating a scam message example repository; submitting the scam message example repository to a natural-language machine learning component, the natural-language machine learning component to generate a scam message model from the example repository using a message content reuse measure, the content reuse measure to compare a user'"'"'s reuse of a phrase to the reuse of the phrase in a random message sample; receiving a scam message model from the natural-language machine learning component in response to submitting the scam message example repository; monitoring a plurality of messaging interactions with a messaging system based on the scam message model; determining a suspected scam messaging interaction of the plurality of messaging interactions; and performing a suspected scam messaging action with the messaging system in response to determining the suspected scam messaging interaction. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. An apparatus, comprising:
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an interaction processing component operative to generate a scam message example repository;
submit the scam message example repository to a natural-language machine learning component, the natural-language machine learning component to generate a scam message model from the example repository using a message content reuse measure, the content reuse measure to compare a user'"'"'s reuse of a phrase to the reuse of the phrase in a random message sample; and
receive a scam message model from the natural-language machine learning component in response to submitting the scam message example repository;an interaction monitoring component operative to monitor a plurality of messaging interactions with a messaging system based on the scam message model; and
determine a suspected scam messaging interaction of the plurality of messaging interactions; anda scam action component operative to perform a suspected scam messaging action with the messaging system in response to determining the suspected scam messaging interaction. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. At least one non-transitory computer-readable storage medium comprising instructions that, when executed, cause a system to:
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generate a scam message example repository; submit the scam message example repository to a natural-language machine learning component, the natural-language machine learning component to generate a scam message model from the example repository using a message content reuse measure, the content reuse measure to compare a user'"'"'s reuse of a phrase to the reuse of the phrase in a random message sample; receive a scam message model from the natural-language machine learning component in response to submitting the scam message example repository; monitor a plurality of messaging interactions with a messaging system based on the scam message model; determine a suspected scam messaging interaction of the plurality of messaging interactions; and perform a suspected scam messaging action with the messaging system in response to determining the suspected scam messaging interaction. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification