CROSAug 18, 2018

Runtime Analysis of Whole-System Provenance

arXiv:1808.06049v2112 citations
Originality Highly original
AI Analysis

This addresses the problem of timely intrusion detection and forensic analysis for computer security systems, representing a novel method for a known bottleneck.

The paper tackles the challenge of real-time security analysis by introducing CamQuery, a Linux Security Module that enables inline, real-time provenance analysis, reducing latency for query mechanisms with minimal system overhead.

Identifying the root cause and impact of a system intrusion remains a foundational challenge in computer security. Digital provenance provides a detailed history of the flow of information within a computing system, connecting suspicious events to their root causes. Although existing provenance-based auditing techniques provide value in forensic analysis, they assume that such analysis takes place only retrospectively. Such post-hoc analysis is insufficient for realtime security applications, moreover, even for forensic tasks, prior provenance collection systems exhibited poor performance and scalability, jeopardizing the timeliness of query responses. We present CamQuery, which provides inline, realtime provenance analysis, making it suitable for implementing security applications. CamQuery is a Linux Security Module that offers support for both userspace and in-kernel execution of analysis applications. We demonstrate the applicability of CamQuery to a variety of runtime security applications including data loss prevention, intrusion detection, and regulatory compliance. In evaluation, we demonstrate that CamQuery reduces the latency of realtime query mechanisms, while imposing minimal overheads on system execution. CamQuery thus enables the further deployment of provenance-based technologies to address central challenges in computer security.

Code Implementations1 repo
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