NDLI: Resource-aware multi-format network security data storage

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Resource-aware multi-format network security data storage

Resource-aware multi-format network security data storage

Content Provider	ACM Digital Library
Author	Cooke, Evan Rusek, David Jahanian, Farnam Myrick, Andrew
Abstract	Internet security systems like intrusion detection and intrusion prevention systems are based on a simple input-output principle: they receive a high-bandwidth stream of input data and produce summaries of suspicious events. This simple model has serious drawbacks, including the inability to attach context to security alerts, a lack of detailed historical information for anomaly detection baselines, and a lack of detailed forensics information. Together these problems highlight a need for fine-grained security data in the shortterm, and coarse-grained security data in the long-term. To address these limitations we propose resource-aware multi-format security data storage. Our approach is to develop an architecture for recording different granularities of security data simultaneously. To explore this idea we present a novel framework for analyzing security data as a spectrum of information and a set of algorithms for collecting and storing multi-format data. We construct a prototype system and deploy it on darknets at academic, Fortune 100 enterprise, and ISP networks. We demonstrate how a hybrid algorithm that provides guarantees on time and space satisfies the short and long-term goals across a four month deployment period and during a series of large-scale denial of service attacks.
Starting Page	177
Ending Page	184
Page Count	8
File Format	PDF
ISBN	1595935711
DOI	10.1145/1162666.1162677
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2006-09-11
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Darknet Network-wide traffic analysis Anomaly classification Anomaly detection
Content Type	Text
Resource Type	Article

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