Thwarting an impersonation attack using online decoy text
Thwarting an impersonation attack using online decoy text. In one embodiment, a method may include intercepting first actual text submitted online by a first user, generating decoy text to replace the first actual text, sending the decoy text for posting online, training a machine learning model using the decoy text to make the machine learning model capable of recognizing a decoy language pattern in the decoy text, intercepting second actual text submitted to a web server by a second user purporting to be the first user, determining, using the machine learning model, that a language pattern in the second actual text matches the decoy language pattern in the decoy text, and, in response, determining that the second user is impersonating the first user in an impersonation attack and thwarting the impersonation attack by performing a remedial action at the web server to protect the web server from the impersonation attack.
1. A computer-implemented method for thwarting an impersonation attack using online decoy text, at least a portion of the method being performed by a computer device comprising at least one processor, the method comprising:
intercepting first actual text submitted online by a first user;
generating decoy text to replace the first actual text;
sending the decoy text for posting online;
training a machine learning model using the decoy text to make the machine learning model capable of recognizing a decoy language pattern in the decoy text;
intercepting second actual text submitted to a web server by a second user purporting to be the first user;
determining, using the machine learning model, that a language pattern in the second actual text matches the decoy language pattern in the decoy text;
in response to determining that the language pattern in the second actual text matches the decoy language pattern in the decoy text:
determining that the second user is impersonating the first user in an impersonation attack; and
thwarting the impersonation attack by performing a remedial action at the web server to protect the web server from the impersonation attack.
2. The method of claim 1 , wherein the performing of the remedial action at the web server comprises one or more of blocking the second user from accessing the web server, rolling back one or more changes at the web server that were made during the impersonation attack, or temporarily freezing an account of the first user at the web server, or some combination thereof.
3. The method of claim 1 , wherein the sending of the decoy text for posting online further comprises preventing the first actual text from being sent for posting online.
4. The method of claim 1 , wherein the second user is a human user.
5. The method of claim 1 , wherein the second user is a computer conversational agent.
6. The method of claim 1 , wherein the second actual text was generated based on the decoy text that was posted online.
7. The method of claim 1 , wherein the second actual text is submitted to the web server in a chat conversation in an attempt by the second user to impersonate the first user and thereby gain access to non-public personal information of the first user.
8. One or more non-transitory computer-readable media comprising one or more computer-readable instructions that, when executed by one or more processors of a computer device, cause the computer device to perform a method for thwarting an impersonation attack using online decoy text, the method comprising:
intercepting first actual text submitted online by a first user;
generating decoy text to replace the first actual text;
sending the decoy text for posting online;
training a machine learning model using the decoy text to make the machine learning model capable of recognizing a decoy language pattern in the decoy text;
intercepting second actual text submitted to a web server by a second user purporting to be the first user;
determining, using the machine learning model, that a language pattern in the second actual text matches the decoy language pattern in the decoy text;
in response to determining that the language pattern in the second actual text matches the decoy language pattern in the decoy text:
determining that the second user is impersonating the first user in an impersonation attack; and
thwarting the impersonation attack by performing a remedial action at the web server to protect the web server from the impersonation attack.
9. The one or more non-transitory computer-readable media of claim 8 , wherein the performing of the remedial action at the web server comprises one or more of blocking the second user from accessing the web server, rolling back one or more changes at the web server that were made during the impersonation attack, or temporarily freezing an account of the first user at the web server, or some combination thereof.
10. The one or more non-transitory computer-readable media of claim 8 , wherein the sending of the decoy text for posting online further comprises preventing the first actual text from being sent for posting online.
11. The one or more non-transitory computer-readable media of claim 8 , wherein the second user is a human user.
12. The one or more non-transitory computer-readable media of claim 8 , wherein the second user is a computer conversational agent.
13. The one or more non-transitory computer-readable media of claim 8 , wherein the second actual text was generated based on the decoy text that was posted online.
14. The one or more non-transitory computer-readable media of claim 8 , wherein the second actual text is submitted to the web server in a chat conversation in an attempt by the second user to impersonate the first user and thereby gain access to non-public personal information of the first user.
15. A server comprising:
one or more processors; and
one or more non-transitory computer-readable media comprising one or more computer-readable instructions that, when executed by the one or more processors, cause the server to perform a method comprising:
receiving decoy text, the decoy text having been generated to replace first actual text that was intercepted after having been submitted online by a first user, the decoy text further having been sent for posting online;
training a machine learning model using the decoy text to make the machine learning model capable of recognizing a decoy language pattern in the decoy text;
receiving second actual text, the second actual text having been intercepted after having been submitted to a web server by a second user purporting to be the first user;
determining, using the machine learning model, that a language pattern in the second actual text matches the decoy language pattern in the decoy text;
in response to determining that the language pattern in the second actual text matches the decoy language pattern in the decoy text:
determining that the second user is impersonating the first user in an impersonation attack; and
thwarting the impersonation attack by performing a remedial action at the web server to protect the web server from the impersonation attack.
16. The server of claim 15 , wherein the performing of the remedial action at the web server comprises one or more of blocking the second user from accessing the web server, rolling back one or more changes at the web server that were made during the impersonation attack, or temporarily freezing an account of the first user at the web server, or some combination thereof.
17. The server of claim 15 , wherein the second user is a human user.
18. The server of claim 15 , wherein the second user is a computer conversational agent.
19. The server of claim 15 , wherein the second actual text was generated based on the decoy text that was posted online.
20. The server of claim 15 , wherein the second actual text is submitted to the web server in a chat conversation in an attempt by the second user to impersonate the first user and thereby gain access to non-public personal information of the first user.