Automated Teller Machine Ethernet Traffic Identification to Target Forensics Detection of IP Packets
Date of Award
5-2019
Culminating Project Type
Starred Paper
Degree Name
Information Assurance: M.S.
Department
Information Assurance and Information Systems
College
Herberger School of Business
First Advisor
Abdullah Abu Hussein
Second Advisor
Lynn Collen
Third Advisor
Balasubramanian Kasi
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Keywords and Subject Headings
ATM, SSL, TLS Ethernet, Forensics
Abstract
Over the last few decades, consumers have become accustom to the convenience of Automatic Teller Machines (ATMs) to transfer funds between accounts, provide account balance information and to withdraw cash from savings, checking, and other account types. Along with the convenience and ease of locating an ATM through mobile bank apps, there has been a significant increase in ATM fraud across the globe. Consumer confidence in the ATM, bank and credit card issuer is greatly impacted by the perceived level of security in ATM transactions and the technology behind them. Confronting the risk associated with ATM fraud and limiting its impact is an important issue that face financial institutions as the sophistication of fraud techniques have advanced. Largely the process behind the verification of these transactions has moved from Plain Old Telephone System (POTS) to Ethernet connections to the processors, banks and card issuers. The attack surface has grown, both in size and complexity. These security risks should be prompting the industry to research all attack surfaces, and this research looks specifically the Ethernet packets that make up these types of transactions. In this research, I investigate the packet structure and predictability within ATM Ethernet traffic. Even with the proliferation of retail ATMs in the most common of retail spaces, this attack vector has received little attention.
Recommended Citation
Volkmuth, Brian, "Automated Teller Machine Ethernet Traffic Identification to Target Forensics Detection of IP Packets" (2019). Culminating Projects in Information Assurance. 87.
https://repository.stcloudstate.edu/msia_etds/87
Comments/Acknowledgements
I would like to thank Dr. Abdullah Abu Hussein for his patient help, guidance, and encouragement and Dr. Collen Lynn and Dr. Balasubramanian Kasi for their thoughtful participation on the committee and excellent feedback and of course my wife, Alicia Volkmuth MBA, MA.