Retrofitting Applications with Provenance-Based Security Monitoring
release_4spvnliyz5avpakkh5wcpkxvhe
by
Adam Bates, Kevin Butler, Alin Dobra, Brad Reaves, Patrick Cable,
Thomas Moyer, Nabil Schear
2016
Abstract
Data provenance is a valuable tool for detecting and preventing cyber attack,
providing insight into the nature of suspicious events. For example, an
administrator can use provenance to identify the perpetrator of a data leak,
track an attacker's actions following an intrusion, or even control the flow of
outbound data within an organization. Unfortunately, providing relevant data
provenance for complex, heterogenous software deployments is challenging,
requiring both the tedious instrumentation of many application components as
well as a unified architecture for aggregating information between components.
In this work, we present a composition of techniques for bringing affordable
and holistic provenance capabilities to complex application workflows, with
particular consideration for the exemplar domain of web services. We present
DAP, a transparent architecture for capturing detailed data provenance for web
service components. Our approach leverages a key insight that minimal knowledge
of open protocols can be leveraged to extract precise and efficient provenance
information by interposing on application components' communications, granting
DAP compatibility with existing web services without requiring instrumentation
or developer cooperation. We show how our system can be used in real time to
monitor system intrusions or detect data exfiltration attacks while imposing
less than 5.1 ms end-to-end overhead on web requests. Through the introduction
of a garbage collection optimization, DAP is able to monitor system activity
without suffering from excessive storage overhead. DAP thus serves not only as
a provenance-aware web framework, but as a case study in the non-invasive
deployment of provenance capabilities for complex applications workflows.
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