• DocumentCode
    1772676
  • Title

    Methodology to reverse engineer a scrambled Java card virtual machine using electromagnetic analysis

  • Author

    Kasmi, Mohammed Amine ; Mostafa, Atahar ; Lanet, Jean Louis

  • Author_Institution
    Lab. MATSI, Mohammed First Univ., Oujda, Morocco
  • fYear
    2014
  • fDate
    28-30 May 2014
  • Firstpage
    278
  • Lastpage
    281
  • Abstract
    ElectroMagnetic Analysis (EMA) of smart cards is a powerful technique that allows extracting information about the executed code as well as about the processed data. It´s why EMA could be exploited in a side channel attack to retrieve the encryption key. In our current work, we study the possibility to apply reverse engineering upon a java card application in which the virtual machine is scrambled. Even if this process of scrambling is an effective way to prevent execution of an arbitrary code written in any data structure, we believe that it can be systematically bypassed regardless the level of the platform encryption under the reverse engineering trails. In this paper, we present a methodology that could be used to find out the encryption key of the scrambling process.
  • Keywords
    Java; data structures; private key cryptography; reverse engineering; smart cards; virtual machines; EMA; Java card application; arbitrary code execution prevention; code execution; data processing; data structure; electromagnetic analysis; encryption key retrieval; information extraction; platform encryption level; reverse engineering; scrambled Java card virtual machine; side channel attack; smart cards; Correlation; Encryption; Java; Prefetching; Reverse engineering; Smart cards; Virtual machining; bytecode; electromagnetic analysis; logical attacks; power analysis; reverse engineering; scrambled Java Card platform; side-channel attack;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Next Generation Networks and Services (NGNS), 2014 Fifth International Conference on
  • Conference_Location
    Casablanca
  • Print_ISBN
    978-1-4799-6608-0
  • Type

    conf

  • DOI
    10.1109/NGNS.2014.6990264
  • Filename
    6990264