Akamai Technologies, Inc.

Wisconsin Alumni Research Foundation

David John Plonka

Arthur Wagner Berger

Paul Robert Barford

Pawel J Foremski

Kyle R Rose

Laura M Roberts

Vinod Yegneswaran

Amos Ron

Jeffery Thomas Kline

Sangnam Nam

An analysis system automates IP address structure discovery by deep analysis of sample IPv6 addresses using a set of computational methods, namely, information-theoretic analysis, machine learning, and statistical modeling. The system receives a sample set of IP addresses, computes entropies, discovers and mines address segments, builds a network model of address segment inter-dependencies, and provides a graphical display with various plots and tools to enable a network analyst to navigate and explore the exposed IPv6 address structure. The structural information is then applied as input to applications that include: (a) identifying homogeneous groups of client addresses, e.g., to assist in mapping clients to content in a CDN; (b) supporting network situational awareness efforts, e.g., in cyber defense; (c) selecting candidate targets for active measurements, e.g., traceroutes campaigns, vulnerability assessments, or reachability surveys; and (d) remotely assessing a network's addressing plan and address assignment policy.

Internet address structure analysis, and applications thereof

An entity can disseminate nonces by introducing them into various aspects of network traffic, and then listening for them, thereby detecting eavesdroppers on the Internet. A nonce may be numeric, alphanumeric, or otherwise; nonces are contextually appropriate to how they are disseminated. Preferably, a nonce is disseminated by incorporating it into some aspect of network traffic. For example, a nonce can be placed in a network identifier such as an IP address or domain name label. Correlating the circumstances under which the nonce was disseminated and under which it was observed to 'propagate', intelligence about who is eavesdropping on what portions of the Internet can be derived. Such intelligence can be put to many uses, including reporting on eavesdroppers, routing traffic around eavesdroppers, developing reputation scores, and adopting enhanced obfuscation/privacy/security techniques.

Nonce injection and observation system for detecting eavesdroppers

A network anomaly detector evaluates two complementary measurements of network statistics, a time variation and correlation among those statistics, to provide an extremely robust detection of network anomalies. In one embodiment, the variability and correspondence are compared against historically derived thresholds to provide for a system that accommodates to local network conditions and evolving network qualities.

Method and apparatus for network anomaly detection

A monitor of malicious network traffic attaches to unused addresses and monitors communications with an active responder that has constrained-state awareness to be highly scalable. In a preferred embodiment, the active responder provides a response based only on the previous statement from the malicious source, which in most cases is sufficient to promote additional communication with the malicious source, presenting a complete record of the transaction for analysis and possible signature extraction.

Scalable monitor of malicious network traffic

A network monitor provides improved understanding of the type of data being transmitted by packets by capturing rendezvous packets, such as domain name server queries and responses, to extract text domain names that may then be associated with later packets using a common numeric addresses. Text domain names intended for human understanding and recollection provide a unique insight into the content of the packets not readily obtained by analysis of the packet data itself.

Growing community of inventors

Madison, WI, United States of America

David John Plonka