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An Introspection-Based Memory Scraper Attack against Virtualized Point of Sale Systems

  • Jennia Hizver
  • Tzi-cker Chiueh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7126)

Abstract

Retail industry Point of Sale (POS) computer systems are frequently targeted by hackers for credit/debit card data. Faced with increasing security threats, new security standards requiring encryption for card data storage and transmission were introduced making harvesting card data more difficult. Encryption can be circumvented by extracting unencrypted card data from the volatile memory of POS systems. One scenario investigated in this empirical study is the introspection-based memory scraping attack. Vulnerability of nine commercial POS applications running on a virtual machine was assessed with a novel tool, which exploited the virtual machine state introspection capabilities supported by modern hypervisors to automatically extract card data from the POS virtual machines. The tool efficiently extracted 100% of the credit/debit card data from all POS applications. This is the first detailed description of an introspection-based memory scraping attack on virtualized POS systems.

Keywords

Virtual Machine Physical Memory Card Data Payment Card Window Memory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jennia Hizver
    • 1
  • Tzi-cker Chiueh
    • 1
  1. 1.Department of Computer ScienceStony Brook UniversityStony BrookUSA

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