NSF Award
2030611
The “smart living” vision aims to improve human quality of life. Cornerstone cyber-physical systems (CPS) like smart homes, smart grid, smart transportation, or smart healthcare generate voluminous amount of time series data through sensor-actuator devices, the so-called Internet of Things (IoT). Such data may be a target of low-profile stealthy attacks hiding behind high randomness of benign smart living IoT data trends, thereby thwarting the accuracy of analytics dependent operations of various applications. The intertwined dependence on data analytics, potential civilian impact of wrong decisions and competitive economic motivations (e.g., by nation adversaries) make the underlying IoT and CPS domains extremely vulnerable to data integrity and availability attacks as addressed in the innovative TAURUS project. This collaborative project will create a tremendous impact by developing a new science of security for emerging IoT-based applications in smart living. It addresses stealthy attacks from both cyber and physical exploits hiding behind high randomness due to human behavioral differences and codifies a unified model at community scale under various attack types and strengths. Thus, the TAURUS project will drastically reduce the number of concurrently running security solutions and corresponding cross coordination to secure IoT applications. Additionally, the project will recruit and mentor undergraduate and graduate students, including women and underrepresented minority students, as well as train K-12 students through various schemes at partner institutions.<br/><br/>The novelty of TAURUS project lies in the unified, lightweight, data-driven approaches towards security analytics across IoT domains in smart living. The invariant-based unified anomaly or intrusion detection theory is unique as it captures both linear and non-linear relationships in data from multiple IoT devices. It also ensures sharp deviations under various attacks yet remaining undisturbed under no attacks, while hiding differences in data skewness, symmetry, dynamics, and configuration across different IoT domains. The proposed response mechanism will gather evidence on the presence, type, severity, and strategies of threats. Finally, based on biological information theoretic concepts extracted from the evidence, the TAURUS project will develop a novel unified trust framework to identify compromised IoT devices with high accuracy under stealthy attacks. Validation of the developed solutions will use real datasets from smart meters and phasor measurement units in smart grid, and vehicle-to-vehicle and vehicle-to-infrastructure data in smart transportation. The proposed security framework is potentially applicable to other smart living IoT context such as smart homes and water distribution networks. A dedicated website will maintain codes, simulation and real-world datasets for two years beyond the project period. Instructions on data cleaning, preparation, and transformations will be available in a GitHub repository. Research findings and results will be disseminated via TAURUS website and publications in peer-reviewed high quality conferences and journals.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
