Neon: system support for derived data management

  • Authors:

  • Qing Zhang;John McCullough;Justin Ma;Nabil Schear;Michael Vrable;Amin Vahdat;Alex C. Snoeren;Geoffrey M. Voelker;Stefan Savage

  • Affiliations:

  • UCSD, San Diego, CA, USA;UCSD, San Diego, CA, USA;UCSD, San Diego, CA, USA;UIUC, Champaign, IL, USA;UCSD, San Diego, CA, USA;UCSD, San Diego, CA, USA;UCSD, San Diego, CA, USA;UCSD, San Diego, CA, USA;UCSD, San Diego, CA, USA

  • Venue:
  • Proceedings of the 6th ACM SIGPLAN/SIGOPS international conference on Virtual execution environments
  • Year:
  • 2010

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Abstract

Modern organizations face increasingly complex information management requirements. A combination of commercial needs, legal liability and regulatory imperatives has created a patchwork of mandated policies. Among these, personally identifying customer records must be carefully access-controlled, sensitive files must be encrypted on mobile computers to guard against physical theft, and intellectual property must be protected from both exposure and "poisoning." However, enforcing such policies can be quite difficult in practice since users routinely share data over networks and derive new files from these inputs--incidentally laundering any policy restrictions. In this paper, we describe a virtual machine monitor system called Neon that transparently labels derived data using byte-level "tints" and tracks these labels end to end across commodity applications, operating systems and networks. Our goal with Neon is to explore the viability and utility of transparent information flow tracking within conventional networked systems when used in the manner in which they were intended. We demonstrate that this mechanism allows the enforcement of a variety of data management policies, including data-dependent confinement, mandatory I/O encryption, and intellectual property management.