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InternetPerils delivers Intelligence Streams in a variety of forms for several types of customers, using multiple sources, data fusion, and deep analysis with pattern recognition to reveal the big picture of Internet anomalies. The most distinctive features of the core technologies are intertwined among data collection, analysis, and visualization, enabling pattern recognition at all three levels.


Data collection via a traceroute-like probing mechanism enables direct, constantly updated, simultaneous observation of Internet topology and Internet performance. The basic patterns of topology are inherent in the collected data.

Availability of combined topology and performance data permits automated selection of critical nodes, both baseline and during perils. This form of pattern recognition enables both presentation of results and tuning of focus sets for further results.

Selection of important nodes permits abstraction, making it possible to visualize important features of massive datasets. Visualization presents automated results of analysis, permits manual investigation and interpretation of those results. Visualization enables manual pattern recognition, which facilitates tuning analysis and data collection.


InternetPerils' specific graphing, selection, and probing techniques enable several advantages at the three levels of collection, analysis, and visualization. Most importantly, their use together provides the lightweight, automated, yet manually tunable methods which produce the frequent, ongoing, detailed representation of patterns of Internet perils.

InternetPerils enables companies to manage Internet business risk.


InternetPerils' Gap Analysis of Internet Networks (GAIN) creates a living topology of the Internet, examining various depths, different parts, and different functions of the Internet. InternetPerils uses all-source data fusion to understand the complete picture, by integrating data from hundreds of feeds from dozens of sources. This must be done constantly with a full understanding of the interrelationships among the pieces. InternetPerils collects its own Internet measurements from sensors and combines it with news feeds and human intelligence. The result is a current, constantly-updated, map of the entire fabric and framework of the Internet.

Then InternetPerils uses deep analysis to make sense of the data by pattern recognition and event detection, in order to identify weak points in the Internet, recommend redundancy strategies as well as conduct survivability modeling, bottleneck and peering failure analysis. This combination of all-source data fusion and deep analysis provides a timely, holistic, synoptic view of the Internet. For insurance customers, InternetPerils aggregates this Internet Intelligence into tables for actuarial use. InternetPerils also provides visualizations of perils and anomalies for use by insurance brokers, security assessors, and enterprises.


PerilScope™ makes devices and data pathways, as well as their performance qualities, as immediately apparent as a railway diagram. It can analyze and display logical topologies and performance of the Internet from any number of abstraction levels, revealing perils as small as a nonredundant link and anomalies as large as cyber-hurricanes. PerilScope™ can select subjects of interest from the cloud, which can be used to build actuarial matrices based on performance histories over time. Fused with other data, such as information about ownership and operational specifics of nodes, a quantitative picture of very high resolution can be drawn of a topological space in which commercial data is resident. At the high levels of abstraction PerilScope™ can provide the kind of structured performance intelligence that gives risk managers insight into the global aggregated risks that should inform the pricing of all Internet business risk management products.