BEC Defender: QR Code-Based Methodology for Prevention of Business Email Compromise (BEC) Attacks.

In an era of ever-evolving and increasingly sophisticated cyber threats, protecting sensitive information from cyberattacks such as business email compromise (BEC) attacks has become a top priority for individuals and enterprises. Existing methods used to counteract the risks linked to BEC attacks frequently prove ineffective because of the continuous development and evolution of these malicious schemes. This research introduces a novel methodology for safeguarding against BEC attacks called the BEC Defender. The methodology implemented in this paper augments the authentication mechanisms within business emails by employing a multi-layered validation process, which includes a MAC address as an identity token, QR code generation, and the integration of timestamps as unique identifiers. The BEC-Defender algorithm was implemented and evaluated in a laboratory environment, exhibiting promising results against BEC attacks by adding an extra layer of authentication.

A New MAC Address Spoofing Detection Technique Based on Random Forests.

Media access control (MAC) addresses in wireless networks can be trivially spoofed using off-the-shelf devices. The aim of this research is to detect MAC address spoofing in wireless networks using a hard-to-spoof measurement that is correlated to the location of the wireless device, namely the received signal strength (RSS). We developed a passive solution that does not require modification for standards or protocols. The solution was tested in a live test-bed (i.e., a wireless local area network with the aid of two air monitors acting as sensors) and achieved 99.77%, 93.16% and 88.38% accuracy when the attacker is 8-13 m, 4-8 m and less than 4 m away from the victim device, respectively. We implemented three previous methods on the same test-bed and found that our solution outperforms existing solutions. Our solution is based on an ensemble method known as random forests.