Covert Cognizance: A Novel Predictive Modeling Paradigm for Securing Unattended High-Valued Systems

Research on the development of secure operational technology (OT) networks which support the operation of high-valued critical systems, including smart manufacturing, industrial energy delivery, military, and other critical infrastructure, has grown exponentially in the past two decades, responding to the notable increase in frequency and sophistication of state-sponsored and insider attacks. This project proposes a paradigm shift for embedding security in the various industrial internet of things (IIoT) components of the OT network of smart factories. This is to address extreme adversarial scenarios in which the attackers are assumed to have gained foothold in the system, often achievable via an Advanced Persistent Threat (APT) campaign and social engineering, allowing them to bypass all existing IT security measures, and introduce surgical disruptions to the system’s function through shadow IIoT devices or hijacking existing devices with privileged access. To our knowledge, there currently exists no security technology in the open literature that does not require placing some level of faith in a number of key individuals, i.e., programmers, system admins, etc., with technical know-how and/or privileged access to the system and its associated software; a strategy that renders systems prone to insider threats. The proposed technology offers a transformational solution to this problem, by offering a human-free security paradigm, that allows a system’s digital brain to repair itself under the extreme adversarial scenario in which the threat comes from within. The key value proposition of the technology to owners in the smart manufacturing industry is the automated intrusion detection and data recovery capabilities that allows for 100% system uptime even if the system is compromised by insiders. In response to the APT challenges, the project’s objective is to develop a prototypic implementation of a new security paradigm for digitally-controlled systems, denoted by covert cognizance (C2 ), designed to develop cognizance, i.e., self-awareness, for the system’s digital brain, to be implemented in a covert manner in order to ensure that it cannot be reverse-engineered if the system network is hacked by adversaries. The proposed Phase I SBIR project requests funds to mature the C2 technology by demonstrating its functionality to a representative system in the smart manufacturing industry. Specifically, a plug-and-play embedded device will be created and tested against a variety of cyberthreats, which may simply be affixed onto existing critical IIoT devices in a smart manufacturing plant to protect them from sophisticated cyberthreats by augmenting the digital brain of the system with automated intrusion detection and data recovery capabilities. It is expected that the MVP will provide the necessary proof of concept in support of its commercialization, which may be leveraged to find an industrial partner at the end of Phase I in the smart manufacturing industry. In subsequent phases, Covert Defenses will establish a footprint in the market via a beachhead strategy starting with the smart manufacturing industry, followed by partnership with IIoT vendors that will allow us to enter the more conservative electric power industry.