NDLI: Neon: system support for derived data management

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Neon: system support for derived data management

Content Provider	ACM Digital Library
Author	Vahdat, Amin Voelker, Geoffrey M. Savage, Stefan Zhang, Qing Ma, Justin Vrable, Michael Schear, Nabil McCullough, John Snoeren, Alex C.
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.
Starting Page	63
Ending Page	74
Page Count	12
File Format	PDF
ISBN	9781605589107
DOI	10.1145/1735997.1736008
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-03-17
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Xen Difc Qemu Virtualization Memory tainting
Content Type	Text
Resource Type	Article

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