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New for 2022, AeroTech® will deliver even more robust programming by teaming up with AeroMat to deliver learning opportunities dedicated to: Additive Manufacturing and Materials, Environment and Sustainable Aviation (Sustainability), Autonomy and AI, Safety and Human Factors, Modeling, Simulation and Testing, Cybersecurity / Cyber-Physical Security, Industry 4.0 Smart Manufacturing and Assembly, IDEAL Summit (inclusion, diversity, equity, accessibility and leadership), Advanced Air Mobility (AAM) and Multimodal Mobility (M3)

New for 2022, AeroTech® will deliver even more robust programming by teaming up with AeroMat to deliver learning opportunities dedicated to: Additive Manufacturing and Materials, Environment and Sustainable Aviation (Sustainability), Autonomy and AI, Safety and Human Factors, Modeling, Simulation and Testing, Cybersecurity / Cyber-Physical Security, Industry 4.0 Smart Manufacturing and Assembly, IDEAL Summit (inclusion, diversity, equity, accessibility and leadership), Advanced Air Mobility (AAM) and Multimodal Mobility (M3)

New for 2022, AeroTech® will deliver even more robust programming by teaming up with AeroMat to deliver learning opportunities dedicated to: Additive Manufacturing and Materials, Environment and Sustainable Aviation (Sustainability), Autonomy and AI, Safety and Human Factors, Modeling, Simulation and Testing, Cybersecurity / Cyber-Physical Security, Industry 4.0 Smart Manufacturing and Assembly, IDEAL Summit (inclusion, diversity, equity, accessibility and leadership), Advanced Air Mobility (AAM) and Multimodal Mobility (M3)

New for 2022, AeroTech® will deliver even more robust programming by teaming up with AeroMat to deliver learning opportunities dedicated to: Additive Manufacturing and Materials, Environment and Sustainable Aviation (Sustainability), Autonomy and AI, Safety and Human Factors, Modeling, Simulation and Testing, Cybersecurity / Cyber-Physical Security, Industry 4.0 Smart Manufacturing and Assembly, IDEAL Summit (inclusion, diversity, equity, accessibility and leadership), Advanced Air Mobility (AAM) and Multimodal Mobility (M3)

The purpose of this SAE Aerospace Information Report (AIR) is to provide guidance for aircraft engine and propeller systems (hereafter referred to as propulsion systems) certification for cybersecurity. Compliance for cybersecurity requires that the engine control, propeller control, monitoring system, and all auxiliary equipment systems and networks associated with the propulsion system (such as nacelle systems, overspeed governors, and thrust reversers) be protected from intentional unauthorized electronic interactions (IUEI) that may result in an adverse effect on the safety of the propulsion system or the airplane.

Abstract Aircraft cybersecurity efforts have tended to focus at the strategic or tactical levels without a clear connection between the two. ...CSSEP’s process model postulates that security is best achieved by a balance of cybersecurity, cyber resiliency, defensibility, and recoverability and that control is best established by developing security constraints versus attempting to find every vulnerability. ...CSSEP identifies the major functions needed to do effective aircraft cybersecurity and provides a flexible framework as the “missing link” to connect the strategic and tactical levels of aircraft cybersecurity.

SAE EDGE Research Reports provide examinations significant topics facing mobility industry today including Connected Automated Vehicle Technologies Electrification Advanced Manufacturing

SAE EDGE Research Reports provide examinations significant topics facing mobility industry today including Connected Automated Vehicle Technologies Electrification Advanced Manufacturing

SAE EDGE Research Reports provide examinations significant topics facing mobility industry today including Connected Automated Vehicle Technologies Electrification Advanced Manufacturing

This SAE Aerospace Recommended Practice (ARP) provides insights on how to perform a Cost Benefit Analysis (CBA) to determine the Return on Investment (ROI) that would result from implementing a blockchain solution to a new or an existing business process. The word “blockchain” refers to a method of documenting when data transactions occur using a distributed ledger with desired immutable qualities. The scope of the current document is on enterprise blockchain which gives the benefit of standardized cryptography, legal enforceability and regulatory compliance. The document analyzes the complexity involved with this technology, lists some of the different approaches that can be used for conducting a CBA, and differentiates its analysis depending on whether the application uses a public or a private distributed network.

Abstract Threat identification and security analysis have become mandatory steps in the engineering design process of high-assurance systems, where successful cyberattacks can lead to hazardous property damage or loss of lives. This article describes a novel approach to perform security analysis on embedded systems modeled at the architectural level. The tool, called Security Threat Evaluation and Mitigation (STEM), associates threats from the Common Attack Pattern Enumeration and Classification (CAPEC) library with components and connections and suggests potential defense patterns from the National Institute of Standards and Technology (NIST) Special Publication (SP) 800-53 security standard. This article also provides an illustrative example based on a drone package delivery system modeled in AADL.

Upon their arrival, Unmanned Autonomous Systems (UAS) brought with them many benefits for those involved in a military campaign. They can use such systems to reconnoiter dangerous areas, provide 24-hr aerial security surveillance for force protection purposes or even attack enemy targets all the while avoiding friendly human losses in the process. Unfortunately, these platforms also carry the inherent risk of being built on innately vulnerable cybernetic systems. From software which can be tampered with to either steal data, damage or even outright steal the aircraft, to the data networks used for communications which can be jammed or even eavesdropped on to gain access to sensible information. All this has the potential to turn the benefits of UAS into liabilities and although the last decade has seen great advances in the development of protection and countermeasures against the described threats and beyond the risk still endures.

In the past, aircraft network design did not demand for information security considerations. The aircraft systems were simple, obscure, proprietary and, most importantly for security, the systems have been either physically isolated or they have been connected by directed communication links. The union of the aircraft systems thus formed a federated network. These properties are in sharp contrast with today’s system designs, which rest upon platform-based solutions with shared resources being interconnected by a massively meshed and shared communication network. The resulting connectivity and the high number of interfaces require an in-depth security analysis as the systems also provide functions that are required for the safe operation of the aircraft. This network design evolution, however, resulted in an iterative and continuous adaption of existing network solutions as these have not been developed from scratch.

This document describes a process for use by ADHP integrators of EEE parts and sub-assemblies (items) that have been targeted for other applications. This document does not describe specific tests to be conducted, sample sizes to be used, nor results to be obtained; instead, it describes a process to define and accomplish application-specific qualification; that provides confidence to both the ADHP integrators, and the integrators’ customers, that the item will performs its function(s) reliably in the ADHP application.

Breathing Life into Artificial Intelligence and Next Generation Autonomous Aerospace Systems Robotic Rotational Molding Creates New Opportunities for Military and Aerospace Applications Rim-Driven Electric Aircraft Propulsion High-Speed Midwave Infrared Cameras Enable Military Test Range Tracking System What Today's Advances in Radar Technology Mean for Testing and Training Tackling Ruggedization Challenges for RF Communications in Software Defined Radios AUVSI XPONENTIAL 2023 The Blueprint for Autonomy Multi-Scale Structuring of the Polar Ionosphere Understanding a radically new sensing capability for polar ionospheric science introduced by observational evidence recently provided by the electronically steerable Resolute Bay Incoherent Scatter Radar (RISR). Stepped-Frequency Distributed Radar for Through-the-Wall Sensing A technical analysis of the effectiveness of distributed radar for through-the-wall sensing applications.

Knowledge wins at 2017 Formula SAE Lincoln The University of Pennsylvania and Texas A&M win the Electric and Internal Combustion Classes, respectively. Flying high at SAE Aero Design New for the twin 2017 competitions in Texas and Florida was a requirement for planes registered in the Regular Class to carry "passengers." Pedal to the metal at Formula SAE Michigan More than 100 university teams compete in this premier student racecar design competition combining static and dynamic events. Removing bumps on the path to fully automated driving Inaugural workshop for new AutoDrive Challenge student competition held at SAE World Headquarters.

DoD to Deploy Thousands of Low Cost Autonomous Systems Under Replicator Program Top Productivity Improvement Tips for Manufacturing Turbine Discs FACE Technical Standard Offers MOSA Lessons for Safety-Critical Software in Any Sector Adamant: A Soon-to-be Open Source, Mission-Critical Flight Software Framework Written in Ada Benefits and Challenges of Direct-RF Sampling for Avionic Platforms More Airports Test RF as Counter Measure for UAS in Restricted Airspace Adapting U.S. Army Acquisition to Ensure the Reliability and Safety of Autonomous Vehicles This report presents several challenges that the U.S. Army will face in the transition to autonomous vehicles, challenges that are only magnified in the current acquisition environment with limited testing. Artificial intelligence algorithms introduce additional complexity, resulting in systems with a complex combination of human, machine, and autonomous controllers.