SBIR Phase I: Fiber Optic Polarization-based Intrusion Detection System

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The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project results from a new capability to detect eavesdropping on a fiber optic data communications link. Much of human society - commerce, social interaction, entertainment, etc. - is increasingly information-based. Technology related to the production and dissemination of information is developing at an exponential rate, with optical communications systems in particular forming the backbone of the internet and other high-capacity communications networks. It is little wonder, therefore, that the wealth of modern society is increasingly represented in the form of information. Protecting such information from access by unauthorized persons or entities is obviously of increasing importance across all sectors of society. This project is aimed at developing a technology to detect the leakage of information at the physical layer in an optical communications system, thus detecting intrusion by an unauthorized party.This Small Business Innovation Research (SBIR) Phase I project brings innovation in securing fiber optic physical transmission media by developing a novel polarization-based intrusion detection system and demonstrating its commercial value. Secure transmission of data is critical to governments, military organizations, financial institutions, health care providers and other enterprises. The proposed fiber optic polarization-based intrusion detection system utilizes the properties of light, as they are manifested in single mode fiber, as a means of ensuring the integrity and security of the physical layer of a fiber-optic based communication link. This technology breakthrough is expected to provide a low-cost means for operators of fiber optic systems to detect intrusion and take corrective measures. Since single mode optical fibers are the primary transmission media of high-capacity long distance telecommunications networks, the proposed technology will enable the detection and prevention of potentially one of the most damaging forms of information theft.