Hierarchical framework for runtime intrusion detection in embedded systems

Existing intrusion detection systems typically rely on one or a few features to detect anomalies or intrusion in a system. Their ability to successfully detect intrusion largely hinges on these limited features, which often do not provide for a comprehensive and runtime detection, especially necessitated in multitude of embedded devices used in critical systems. To overcome this limitation of existing intrusion detection systems, this paper proposes a lightweight runtime hierarchical multimodal intrusion detection framework that can be realized on resource-constrained embedded systems. This work relies on various features such as power trace, System Call (SYSCALL) trace and Hardware Performance Counter (HPC) by leveraging the strengths of the individual features and combining them intelligently to overcome their individual limitations. Using a number of case studies, the proposed framework has been shown to reliably detect intrusion of different types at runtime, while still being sufficiently lightweight to be deployed in resource- constrained embedded systems

Energy-Optimal Trajectory Planning of Hybrid Ultra-Long Endurance UAV in Time-Varying Energy Fields

The article of record as published may be found at https://doi.org/10.2514/6.2020-229The paper addresses the problem of calculating energy optimal trajectory for a novel class of hybrid unmanned aircraft equipped with hydrogen fuel cell and solar photovoltaic energy production technologies. The goal of the design is to minimize the energy (fuel) used in flight by optimally using the finite energy stored in the hydrogen fuel cell and routing the aircraft through the dynamic energy fields of solar irradiance and wind. The optimization task is formulated as a two-point boundary value problem for an aircraft traveling in time-varying atmospheric fields with an objective of finding the minimum energy route and the associated controls. The task is solved by applying the Pontryagin maximum principle to the resulting 2D kinematics of a UAV along with the associated energy models that characterize its energy efficiency. Utilizing the necessary conditions of optimality allows to synthesize the optimal control laws of the bank angle and airspeed. The problem of initial guess is solved by designing a continuation algorithm that is based on scaling the wind magnitude. As a result, the initial guess becomes precisely known as the arc of a great circle that is well-defined by its states and the costates. Not only it initializes the next step of the continuation algorithm, but it also serves as a reference for the comparison of energy expenditures along with the energy optimal and the shortest routes