Network security monitoring is currently challenged by its reliance on human analysts and the inability for tools to
generate indications and warnings for previously unknown attacks. We propose a reputation system based on IP address
set membership within the Autonomous System Number (ASN) system. Essentially, a metric generated based on the
historic behavior, or misbehavior, of nodes within a given ASN can be used to predict future behavior and provide a
mechanism to locate network activity requiring inspection. This will provide reinforcement of notifications and warnings
and lead to inspection for ASNs known to be problematic even if initial inspection leads to interpretation of the event as
innocuous. We developed proof of concept capabilities to generate the IP address to ASN set membership and analyze
the impact of the results. These results clearly show that while some ASNs are one-offs with individual or small numbers
of misbehaving IP addresses, there are definitive ASNs with a history of long term and wide spread misbehaving IP
addresses. These ASNs with long histories are what we are especially interested in and will provide an additional
correlation metric for the human analyst and lead to new tools to aid remediation of these IP address blocks.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.