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TRUST Research on Physical Infrastructure Control, Monitoring, and Security

TRUST Research on Physical Infrastructure Control, Monitoring, and Security. Prof. Stephen Wicker Cornell University. Physical Infrastructure. Power Grid, Telecom Infrastructure, Water Transport System, Interstate Highways Immense Investment

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TRUST Research on Physical Infrastructure Control, Monitoring, and Security

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  1. TRUST Research on Physical Infrastructure Control, Monitoring, and Security Prof. Stephen Wicker Cornell University

  2. Physical Infrastructure • Power Grid, Telecom Infrastructure, Water Transport System, Interstate Highways • Immense Investment • Financial: Sunk costs and ongoing development and maintenance • Human: Established development, maintenance, and regulatory organizations at state and federal level • Critical to National Economy • National modes of production depend on functionality of critical infrastructures with embedded sensing and control • Multiple positive externalities have created secondary and tertiary dependencies (e.g. air traffic control dependence on power and telecom infrastructure) • Increasing complexity and 21st century security requirements demand new approaches to control, security, and long-term maintenance.

  3. TRUST Infrastructure Research • Science and Technology • Low-power processors • Self-configuration algorithms • Taxonomy of network attacks • Information theory of privacy • Testbeds • Sensor networking and privacy • SCADA/plant security • Policy • Smart meters and privacy intrusion • Privacy-aware design

  4. Nugget:TRUST Sensor Platform Technologies • CU Asynchronous Processor • Event-driven execution is ideal for sensor platforms • Low power consumption useful for large-scale and/or long-term deploment • Clockless logic • Spurious signal transitions (wasted power) eliminated • Hardware only active if it is used for the computation • MIPS: high-performance • 24pJ/ins and 28 MIPS @ 0.6V

  5. Nugget: Smart Metering Provides Data Equivalent to a Search • Algorithm Performs well in determining presence and sleep cycles. • Over 90% of total interval length was correctly classified. • Power consumption data falls within the ambit of EU Directive 2002/58/EC • concerning the processing of personal data.

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