Fabric

Abstract

Fabric is a new system and language for building secure distributed information systems. It is a decentralized system that allows heterogeneous network nodes to securely share both information and computation resources despite mutual distrust. Its high-level programming language makes distribution and persistence largely transparent to programmers. Fabric supports data-shipping and functionshipping styles of computation: both computation and information can move between nodes to meet security requirements or to improve performance. Fabric provides a rich, Java-like object model, but data resources are labeled with confidentiality and integrity policies that are enforced through a combination of compile-time and run-time mechanisms. Optimistic, nested transactions ensure consistency across all objects and nodes. A peer-to-peer dissemination layer helps to increase availability and to balance load. Results from applications built using Fabric suggest that Fabric has a clean, concise programming model, offers good performance, and enforces security.

Practical Fine-Grained Information Flow Control Using Laminar

“…A number of solutions have been explored in the literature, surveyed by Kashyap et al [2011]. One option is to use static analysis to identify the labels of all variables used to make control flow decisions and only permit the code to execute if it can declassify these labels [Chandra and Franz 2007;Liu et al 2009] or to restrict the programming model to forbid using a secret value as a conditional variable [Volpano and Smith 1999]. Another option is to partition and schedule the code based on labels [Kashyap et al 2011].…”

“…Purely dynamic systems generally cannot effectively regulate implicit flows. As a result, a number of primarily dynamic JVM systems have augmented [Arden et al 2012;Chandra and Franz 2007;Liu et al 2009;Simonet and Rocquencourt 2003] Asbestos [Efstathopoulos 2008;Vandebogart et al 2007], HiStar [Zeldovich et al 2006 dynamic enforcement of explicit flows with static analysis for implicit flows (thus called a Hybrid DIFC system). Chandra and Franz develop a version of the JVM that enforces information flow control policies on unmodified Java programs [Chandra and Franz 2007].…”

“…Implicit information flows can leak secret data based on program control flow, as when a conditional statement is based on the value of a secret 4:46 D. E. Porter et al variable. DIFC systems based on static analysis can identify when labeled variables can influence control flow and use this information to label the program counter of the function [Chandra and Franz 2007;Liu et al 2009]. In other words, a function with a secret program counter label may not be called by a function with an unlabeled program counter.…”

“…Fabric and Mobile Fabric add additional checks, both static and dynamic, to prevent additional implicit flows in distributed and federated systems, respectively [Arden et al 2012;Liu et al 2009]. For example, loading a class from a remote server may indicate that a secret code took a certain execution path.…”

“…], Flume Static analysis, combined with dynamic checks in some cases[Arden et al 2012;Chandra and Franz 2007;Liu et al 2009]. Security method design restricts visibility into control flow from outside the security method.Laminar combines aspects of PL and OS solutions, and innovates in dynamic flow tracking.…”