System and method for detecting synthetic activity in a network via use of interactive artificial intelligence

1 . A system for detecting synthetic activity in a network via use of interactive artificial intelligence, the system comprising:

at least one non-transitory storage device containing instructions; and

at least one processing device coupled to the at least one non-transitory storage device, wherein the at least one processing device, upon execution of the instructions, is configured to:

receive a first account communication from an end-point device, wherein the first account communication is associated with a user;

based on the first account communication, cause a transmission of a first reply communication to be provided to the end-point device;

receive a second account communication from the end-point device;

based on at least one of the first account communication or the second account communication, determine a synthetic likelihood value via a synthetic machine learning model, wherein the synthetic likelihood value indicates a likelihood that at least one of the first account communication or the second account communication are synthetic;

in an instance in which the synthetic likelihood value is above a synthetic threshold, cause a restriction in access to one or more accounts associated with the user, wherein the restriction in access comprises required additional authentication displayed on the end-point device and a waiting period of action execution;

transmit one or more honey-pot communications to the end-point device, wherein the one or more honey-pot communications are requests for information relating to at least one of the end-point device or the user associated with the end-point device;

transmit multiple additional reply communications after the one or more honey-pot communications directed to unintended topics for fatigue of a synthetic communication; and

update the synthetic machine learning model configured to determine the synthetic likelihood value of communications based on one or more responses to the one or more honey-pot communications.

2 . The system of claim 1 , wherein the at least one processing device, upon execution of the instructions, is configured to:

based on at least one of the first account communication or the second account communication, determine a malfeasance value, wherein the malfeasance value indicates the likelihood that at least one of the first account communication or the second account communication are being received from a malfeasant actor; and

in an instance in which the malfeasance value is above a malfeasance threshold, cause a transmission of one or more additional reply communications to be provided to the end-point device, wherein each of the one or more additional reply communications comprises a request for information relating to the user.

3 . The system of claim 2 , wherein the malfeasance value is determined based on a comparison of known user information to user information provided in at least one of the first account communication or the second account communication.

4 . The system of claim 1 , wherein the at least one processing device, upon execution of the instructions, is configured to cause one or more additional security actions to be required to access the one or more accounts associated with the user in an instance in which the synthetic likelihood value is above the synthetic threshold.

5 . The system of claim 1 , wherein the first reply communication is generated using artificial intelligence based on the first account communication.

6 . A computer program product for detecting synthetic activity in a network via use of interactive artificial intelligence, the computer program product comprising at least one non-transitory computer-readable medium having computer-readable program code portions embodied therein, the computer-readable program code portions comprising:

an executable portion configured to receive a first account communication from an end-point device, wherein the first account communication is associated with a user;

an executable portion configured to cause a transmission of a first reply communication based on the first account communication to be provided to the end-point device;

an executable portion configured to receive a second account communication from the end-point device;

an executable portion configured to determine a synthetic likelihood value via a synthetic machine learning model, wherein the synthetic likelihood value indicates a likelihood that at least one of the first account communication or the second account communication are synthetic;

an executable portion configured to cause a restriction in access to one or more accounts associated with the user in an instance in which the synthetic likelihood value is above a synthetic threshold, wherein the restriction in access comprises required additional authentication displayed on the end-point device and a waiting period of action execution;

an executable portion configured to transmit one or more honey-pot communications to the end-point device, wherein the one or more honey-pot communications are requests for information relating to at least one of the end-point device or the user associated with the end-point device;

an executable portion configured to transmit multiple additional reply communications after the one or more honey-pot communications directed to unintended topics for fatigue of a synthetic communication; and

an executable portion configured to update the synthetic machine learning model configured to determine the synthetic likelihood value of communications based on one or more responses to the one or more honey-pot communications.

7 . The computer program product of claim 6 , wherein the computer program product further comprises:

an executable portion configured to determine a malfeasance value based on at least one of the first account communication or the second account communication, wherein the malfeasance value indicates the likelihood that at least one of the first account communication or the second account communication are being received from a malfeasant actor; and

an executable portion configured to cause a transmission of one or more additional reply communications to be provided to the end-point device in an instance in which the malfeasance value is above a malfeasance threshold, wherein each of the one or more additional reply communications comprises a request for information relating to the user.

8 . The computer program product of claim 7 , wherein the malfeasance value is determined based on a comparison of known user information to user information provided in at least one of the first account communication or the second account communication.

9 . The computer program product of claim 6 , wherein the computer program product further comprises an executable portion configured to cause one or more additional security actions to be required to access the one or more accounts associated with the user in an instance in which the synthetic likelihood value is above the synthetic threshold.

10 . The computer program product of claim 6 , wherein the first reply communication is generated using artificial intelligence based on the first account communication.