Automated Teller Machine (ATM) Ethernet Traffic Analysis for Enhanced Forensic Detection of IP Packets

Over the past few decades, consumers have become increasingly reliant on the convenience of Automated Teller Machines (ATMs) for a variety of banking needs, including transferring funds between accounts, checking account balances, and withdrawing cash from savings, checking, and other account types. This convenience has been further enhanced by mobile banking apps, which allow users to easily locate nearby ATMs. Nevertheless, these advantages have been accompanied by a sharp increase in ATM fraud globally, which has negatively affected consumer trust in banks, credit card companies, and ATMs. The perceived level of security in ATM transactions and the technology that supports these transactions is crucial to maintaining trust. Tackling the risks associated with ATM fraud and reducing its impact is a pressing issue for financial institutions, particularly as fraud techniques have become more advanced and sophisticated. Historically, the verification process for ATM transactions utilized the Plain Old Telephone Service (POTS). However, there has been a shift towards using Ethernet connections to link ATMs with processors, banks, and card issuers. This transition has increased both the size and complexity of the attack surface, presenting new security challenges. Given these heightened security risks, it is imperative for the industry to thoroughly investigate all potential attack surfaces. This research focuses specifically on the Ethernet packets that facilitate these transactions. By examining the structure and predictability of ATM Ethernet traffic, this study aims to provide insights that can help in developing more robust forensic detection methods. Despite the proliferation of retail ATMs in everyday locations, such as shopping centers and convenience stores, this particular attack vector has received relatively little attention in the field of cybersecurity. In this research, we delve into the intricacies of ATM Ethernet traffic, analyzing packet structures to identify patterns and potential vulnerabilities. The goal is to enhance the understanding of this often-overlooked attack vector and to propose strategies for mitigating risks associated with Ethernet-based transactions. By doing so, this research aims to contribute to the development of more effective security measures that can protect both consumers and financial institutions from the evolving threat of ATM fraud. Through a detailed exploration of Ethernet traffic in ATM operations, this study seeks to support the creation of more secure and reliable banking environments, ultimately restoring and maintaining consumer confidence in the safety of ATM transactions.