CAN-D: Controller Area Network Decoder and Intrusion Detection System Available for Licensing

Oak Ridge National Laboratory (ORNL) is seeking a commercialization partner for a technical business opportunity entitled, “CAN-D: Controller Area Network Decoder.”Modern vehicles rely on controller area networks (CANs) to internally communicate information about vehicular functions, such as accelerator pedal angle, brakes, and wheel speeds. Monitoring and improving the efficiency, performance, safety, and security of vehicles depends on decoding the CAN data, but decoding these signals requires proprietary definitions that vary drastically across makes, models, years, and trims. Thus, decoding efforts are per-vehicle endeavors that are manual, tedious, and inadequate for many signals that relay information from latent sensors. This poses a major obstacle for after-market modifications like performance tuning and in-vehicle network security measures. Without available signal definitions, vehicles are dramatically exposed to cyberattacks with potentially disastrous consequences.ORNL’s

Controller Area Network Decoder (CAN-D) technology is a data-driven vehicle agnostic-method for reverse engineering CAN message definitions. This innovation creates an ecosystem of monitoring that allows for improved vehicle performance, efficiency, safety, and security. CAN-D is universally applicable, designed to be used in vehicles across manufacturers. It is also the only known technology that can reverse engineer all four parts of a signal definition. CAN-D is prototyped as a plug-in technology for in-situ use or post-drive analysis and promises greater vehicle safety, efficiency, and security for fleet management, cybersecurity, electrification, automated driving, and V2X tech companies. In this manner, CAN-D can be used for decoding CAN communications without access to CAN data mapping. Moreover, the decoded CAN communications can be used for detecting intrusion of the underlying CAN data.CAN-D enables an ecosystem of technologies that interact with each other on the CAN bus in real time, creating opportunities for enhanced performance, efficiency, safety, and security of vehicles on the road regardless of manufacturer.The global automotive cybersecurity market is expected to grow from $6.2 Billion in 2021 to $28.7 billion by 2030, at a CAGR of 18.6% during the forecast period 2022-2030.Applications:Cybersecurity in the transportation industryFleet managementVehicle fault diagnosisFuel efficiency monitoringPost-accident forensicsAdvantages:Provides access to real-time measurements of vehicle subsystemsUniversally applicableCan process and identify raw signals within nearly any CANNo prior knowledge of specific signal definitions requiredTechnology Innovation Program:This promising technology was originally developed using federal funds and selected for further development under the ORNL’s Technology Innovation Program (TIP). TIP supports technology development using royalties from existing technology licenses to accelerate the market readiness of high-potential technologies. Prospective licensees are invited to attend the ORNL TIP Showcase on June 6, 2022, which will feature technical presentations and laboratory tours to learn more about this technology opportunity.If your organization is interested in licensing this technology, we encourage you to submit a license application through July 1, 2022. License applications will be competitively reviewed and evaluated based on prospective partners’ ability and commitment to successfully commercialize the technology. Candidates with promising applications will be selected to negotiate licensing agreements. If a license is executed, the ORNL researchers developing the technology will be eligible to compete for additional TIP funding to assist in transferring the technology to any licensees.For additional information and license application, contact Andreana Leskovjan, Commercialization Manager, Oak Ridge National Laboratory, 865-341-0433, leskovjanac@ornl.gov.Intellectual Property:U.S. 17/117,535: “Controller Area Network Decoder (CAN-D),” K.E. Verma, R.A. Bridges, S.C. Hollifield. (ORNL ID 202004299)U.S. 17/725,774: “Universally Applicable Signal-Based Controller Area Network (CAN) Intrusion Detection System,” R.A. Bridges, K.E. Verma, M. Iannacone, S.C. Hollifield, J. Sosnowski, P.M. Salazar.  (ORNL ID 202004640)ORNL Copyright 90000140: CAN-D: Controller Area Network Decoder CodebaseOak Ridge National Laboratory:Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security.  Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the U.S. Department of Energy (DOE) under its Prime Contract No. DE-AC05-00OR22725.Additional Information:Publications:M. E. Verma, R. A. Bridges, J. J. Sosnowski, S. C. Hollifield, and M. D. Iannacone, “CAN-D: A Modular Four-Step Pipeline for Comprehensively Decoding Controller Area Network Data,” IEEE Trans. Veh. Technol., 2021. DOI: 10.1109/TVT.2021.3092354.P. Moriano, R. A. Bridges, and M. D. Iannacone, “Detecting CAN Masquerade Attacks with Signal Clustering Similarity,” Workshop on Automotive and Autonomous Vehicle Security (AutoSec) 2022, https://doi.org/10.48550/arXiv.2201.02665.Demos:https://www.youtube.com/watch?v=7KiEUVF_oWshttps://www.youtube.com/watch?v=TWIfMKr3gncAnnouncements June 6, 2022 – TIP Day at Oak Ridge National Laboratory interested parties can come to ORNL for a conference wherein presentations are given by all inventors further highlighting the licensing opportunities; laboratory visits will be possible demonstrating the technologies, and breakout sessions will be available with commercialization/licensing associates.