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IP Network Surveillance Using DeepSweep Learn more about how IP Fabrics’ DeepSweep is used in IP network surveillance applications.
Learn more about how IP Fabrics’ DeepSweep achieves its high performance. |
About IP FabricsIP Fabrics is a private, US-based and managed company that develops and supplies high-performance, intelligent IP intercept probes and stand-alone intercept systems for network surveillance. IP Fabrics has over 50 customers, including surveillance solution providers and integrators, service providers, law-enforcement agencies, and other government agencies. Our market is IP network surveillance. Included in this market are application areas such as intelligence gathering for national security, lawful interception for criminal investigations, internal network abuse/misuse detection and capture, and general cyber crime surveillance. IP Fabrics was founded in August 2002 with the goal of accelerating deep packet processing in IP networks. The vision stemmed from the premise that future networks will have three demands that are often at odds with one another:
Today, IP Fabrics is focused on using its multi-core network processor technology in network surveillance applications through its DeepProbe™ and DeepSweep™ network surveillance systems. DeepProbe is our latest product, and is the industry’s leading intelligent, full-decoding IP probe. DeepProbe is generally deployed under the control of a separate surveillance element such as a mediation system. It is commonly used in distributed surveillance environments, which are typically large, complex networks. DeepProbe excels in several areas. First, it operates at 1G and 10G data rates (with a roadmap to higher speeds), giving it the ability to be located in network aggregation points and thus providing the necessary visibility to a large amount of network traffic as the traffic traverses networks. Second, it has been organically designed as an IP intercept probe and offers many surveillance-specific features such as a well-defined, secure provisioning interface and a robust delivery interface with features including reliable and secure delivery, decoded application data, and options for IPDR, IRI, or full-content intercepts. Lastly, DeepProbe is application-aware and supports application-level intercept filters (e.g., based on criteria such as email/webmail addresses or login IDs) in addition to traditional network protocol-level filters. DeepProbe technology has two advantages over other products used for IP probes. First, it uses best-of-breed Deep Packet Inspection (DPI) and Deep Application Protocol Inspection (DAPI) technology, allowing it to not only inspect the packet content in addition to the basic packet header fields, but to also decode and interpret which applications are using the packets. This technology allows the DeepProbe to support sophisticated, application-level intercepts. Second, DeepProbe makes heavy use of parallelism and multi-core processors, allowing it so support high networking line rates and the ability to scale upward to higher lines rates as the underlying hardware platform increases in performance. DeepSweep is a stand-alone surveillance system which incorporates the intercept access point, mediation, and delivery functions. It is a particularly attractive solution for US-based service providers faced with complying with the FCC’s recent broadband CALEA requirements, and to law enforcement for use in tactical IP pen-register and Title III intercepts. IP Fabrics was originally venture funded from a collection of investors including Northwest Venture Associates and Intel Capital and is based in Beaverton, Oregon. IP Fabrics is led by Glen Myers, who was previously the founder and CEO of RadiSys Corp. (NASDAQ: RSYS). Glen is joined by other executives and technologists with extensive industry experience in companies such as RadiSys, Intel, Tektronix, and IBM. Learn more about IP Fabrics products and technology by visiting the Resource Center or Contact Us to have an IP Fabrics sales representative provide you further information.
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