Extended reality (XR) systems—including virtual, augmented, and mixed reality—are increasingly deployed across critical sectors such as healthcare, defense, manufacturing and energy. As these systems grow more cyber-critical, having access to structured and comprehensive information on attacks, vulnerabilities and defenses focusing on human cognition becomes essential for effectively assessing their security and resilience. Despite this, no centralized public resource currently exists that catalogs cognitive security threats specific to XR environments. To address this gap, this paper presents a public online knowledge base designed to facilitate the structured documentation, exploration, and sharing of XR-specific cognitive attacks, vulnerabilities, and mitigation strategies. The development of this resource followed a two-step methodology: first, identifying and defining the core entities involved in XR-related cognitive attacks; and second, modeling and implementing these entities into a relational database and user-friendly web interface. This platform is designed to aid XR product developers, researchers, and security professionals to report cognitive attack patterns and mitigations, and use knowledge base contents to analyze cognitive threats within XR systems.

With the proliferation of mixed-reality (MR) systems in aerospace and defense, there is increased potential for adversarial exploitation of system vulnerabilities and/or properties in the human cognitive process in order to reduce mission-effectiveness. This paper presents our preliminary work on the Modeling and Analysis Toolkit for Realizable Intrinsic Cognitive Security (MATRICS), a formal methods-based approach to provide a mathematically rigorous design and verification framework for protecting MR systems and operators in mission-critical applications from cognitive attacks. We describe our approach and present initial results, including formal models of the human operator, MR device, and mission environment, and apply existing formal methods tools to prove the holistic cognitive security of MR systems.

Security is paramount in all mission-critical domains, including the aerospace industry. Cyber-attacks are increasing both in number and sophistication. Zero-trust is an emerging initiative that has proven very effective for enterprise systems in the Information Technology domain; however, research is lacking on applicable zero-trust mechanisms and their assurance for cyber–physical systems (CPS). We have already identified various zero-trust mechanisms in our previous work. In this paper, we present our zero-trust architecture design patterns and provide a methodology for the assurance of these mechanisms. Towards this objective, we have identified an initial set of assurance patterns covering individual zero-trust components in a system design. Our design and assurance patterns are made available to system engineers in pattern libraries. Engineers can model system architectures and utilize one or more of these patterns to provide design assurance based on individual zero-trust security requirements to improve the overall system cyber-security. To demonstrate our approach, we apply our assurance patterns to an unmanned aerial vehicle surveillance application. We discuss how our framework leverages the use of these patterns to develop zero-trust-enabled systems with different security requirements. Furthermore, our assurance patterns enable engineers to identify any design flaws and correct them during the initial system design phase, thus saving development time, effort, and cost. As a result, the overall approach can be utilized to design system models with specific zero-trust security requirements to improve the security posture of a CPS.

Cyber-physical systems, such as avionics, must be tolerant to cyber-attacks in the same way they are tolerant to random faults: they either gracefully recover or safely shut down as requirements dictate. The DARPA Cyber Assured Systems Engineering program is developing tools for design, analysis, and verification that enable systems engineers to design-in cyber-resiliency in a Model-Based Systems Engineering environment. This paper describes automated model transformations that introduce high-assurance cyber-resiliency components into a system, in particular filters and monitors that prevent malicious input and detect supply chain attacks, respectively. A formal specification defines each high-assurance component, and is used to verify that the component addresses system level cyber requirements. Implementations for these high-assurance components are directly synthesized from their specifications, and are automatically proven to preserve the exact meaning of the specifications all the way down to the binary code level. The model transformations are integrated into the Open Source AADL Tool Environment (OSATE). The paper further reports on a case study applying security-enhancing model transformations to a UAV system that uses the Air Force Research Laboratory's OpenUxAS services for route planning. In the case study, the model transformations add filters to guard against malformed input, as well as monitors to guard against ground station spoofing and malicious flight plans from OpenUxAS.

Over the past decade, wireless sensor networks have advanced in terms of hardware design, communication protocols, resource efficiency, and other aspects. Recently, there has been growing interest in mobile wireless sensor networks, and several small-profile sensing devices that are able to control their own movement have already been developed. Unfortunately, resource constraints inhibit the use of traditional navigation methods, because these typically require bulky, expensive, and sophisticated sensors, substantial memory and processor allocation, and a generous power supply. Therefore, alternative navigation techniques are required. In this paper we present TripNav, a localization and navigation system that is implemented entirely on resource-constrained wireless sensor nodes. Localization is realized using radio interferometric angle of arrival estimation, in which bearings to a mobile node from a small number of infrastructure nodes are estimated based on the observed phase differences of an RF interference signal. The position of the mobile node is then determined using triangulation. A digital compass is also employed to keep the mobile node from deviating from the desired trajectory. We demonstrate using a real-world implementation that a resource-constrained mobile sensor node can accurately perform waypoint navigation with an average position error of 0.95 m.

Mobile wireless sensors require position updates for tracking and navigation. We present a localization technique that uses the Doppler shift in radio transmission frequency observed by stationary sensors. We consider two scenarios. In the first, the mobile node is carried by a person. In the second, the mobile node controls a robot. In both approaches the mobile node transmits an RF signal, and infrastructure nodes measure the Doppler-shifted frequency. Such measurements enable us to calculate the position and velocity of the mobile transmitter. Our experimental results demonstrate that this technique is viable and accurate for resource-constrained mobile sensor tracking and navigation.

The paper describes a target tracking system running on a heterogeneous sensor network (HSN) and presents results gathered from a realistic deployment. The system fuses audio direction of arrival data from mote class devices and object detection measurements from embedded PCs equipped with cameras. The acoustic sensor nodes perform beamforming and measure the energy as a function of the angle. The camera nodes detect moving objects and estimate their angle. The sensor detections are sent to a centralized sensor fusion node via a combination of two wireless networks. The novelty of our system is the unique combination of target tracking methods customized for the application at hand and their implementation on an actual HSN platform.

Sensor Webs are heterogeneous collections of sensor devices that collect information and interact with the environment. They consist of wireless sensor networks that are ensembles of small, smart, and cheap sensing and computing devices that permeate the environment as well as high-bandwidth rich sensors such as satellite imaging systems, meteorological stations, air quality stations, and security cameras. Emergency response, homeland security, and many other applications have a very real need to interconnect such diverse networks and access information in real-time. While Internet protocols and Web standards provide well-developed mechanisms for accessing this information, linking such mechanisms with resource-constrained sensor networks is very challenging because of the volatility of the communication links. This paper presents a service-oriented programming model for sensor networks which permits discovery and access of Web services. Sensor network applications are realized as graphs of modular and autonomous services with well-defined interfaces that allow them to be described, published, discovered, and invoked over the network providing a convenient way for integrating services from heterogeneous sensor systems. Our approach provides dynamic discovery, composition, and binding of services based on an efficient localized constraint satisfaction algorithm that can be used for developing ambient-aware applications that adapt to changes in the environment. A tracking application that employs many inexpensive sensor nodes, as well as a Web service, is used to illustrate the approach. Our results demonstrate the feasibility of ambient-aware applications that interconnect wireless sensor networks and Web services.