Method of Obtaining Data from Open Scientific Sources and Social Engineering Attack Simulation

Anti-spam software is constantly being improved. User behavior algorithms—the ability to recognize and correctly respond phishing messages are widely known. The task of our research elaborate a way effective dataset preparation from open scientific sources test the efficacy attacks on sample respondents who represent community, as well cybersecurity specialists. We developed tested method mining data necessary for sources. Authors suggest automated scripts check legitimacy gathered before use automate mailing bypassing spam detection algorithms. Elaborated can be used not only simulated but legitimate datasets cleaning mass mailing. experiment results confirm that successful possible. Both scholars specialists vulnerable this type attack based solely data. study shows testing existing filters in “black box” mode without knowledge their Even though these well-known studied psychological perspective, we show community and, particular, demonstrates no difference vulnerability level between other scholars. conclude do prevent messages’ delivery require further improvement. degree users still trust emails an unknown source masquerading ones sending return caution remains relatively high particularly academic