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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)

Countering cybersecurity threats against unmanned vehicle systems Cranfield University researchers have developed a monitoring system whose purpose is to monitor mission profile implementation at both high level mission execution and at lower level software code operation to tackle specific threats of malicious code and possible spurious commands received over a vehicle's data links.

The SAE AS2C Standard AS5506C Architecture Analysis and Description Language (AADL) is a modeling language for predictive analysis of real-time software reliant, safety and cybersecurity critical systems that provides both the precision of formal modeling and the tool-agnostic freedom of a text-based representation. ...AADL supports multiple domains of architectural analysis such as timing, latency, resources, safety, scheduling, and cybersecurity. Adventium Labs conducted an exercise to determine the applicability of software engineering practices (e.g., continuous integration (CI), application programming interface (API) sharing, test driven development (TDD)) to the AADL-based Architecture Centric Virtual Integration Process (ACVIP).

Innovations in Mobility: Aerospace Digital Summitaerospace mobility leaders convene leverage cutting-edge technology, design, develop safety measures, integrate current regulations, suggest future policies, expand markets, diversify revenue streams.

This document provides background and detailed technical information on existing methods to secure loadable software parts.

Abstract Despite more and more rigorous defense mechanisms in place for cyber-physical systems, cybercriminals are increasingly attacking systems for benefits using a variety of means including malware, phishing, ransomware, and denial of service. Cyberattacks could not only cause significant economic loss but also disastrous consequences for individuals and organizations. Therefore, it is advantageous to detect and fix potential cyber vulnerabilities before the system is fielded. To this end, this article presents a language, VERDICT, and a novel framework, Cyber Vulnerability Analysis Framework (CyVAF) to (i) define cyber threats and mitigation defenses based on system properties, (ii) detect cyber vulnerabilities of system architecture automatically, and also (iii) suggest mitigation defenses. VERDICT is developed as an annex to the Architecture Analysis and Design Language (AADL) but can also be used independently.

Cyber security in the aviation industry, especially in relation to onboard aircraft systems, presents unique challenges in its implementation and management. The cyber threat model is constantly evolving and will continually present new and different challenges to the aircraft operator in responding to new cyber threats without either invoking a lengthy software update and re-certification process or limiting aircraft-to-ground communications to the threatened system or systems. This presentation discusses a number of system architectural options and developing technologies that could be considered to enhance the aircraft cyber protection and defensive capabilities of onboard systems as well as to minimize the effort associated with certification/re-certification. Some of these limit the aircraft?s vulnerabilities or in cyber terms, its ?threat surface?.

This brief User Guide recaps the content of the AS6518B UCS Architectural Model. The purpose of the UCS Architecture Model is to provide the authoritative source for other models and products within the UCS Architecture as shown in the AS6512B UCS Architecture: Architecture Description.

This Recommended Practice defines the technical requirements for a terrestrial-based PNT system to improve vehicle (e.g., unmanned, aerial, ground, maritime) positioning/navigation solutions and ensure critical infrastructure security, complementing GNSS technologies.

This specification establishes process controls for the repeatable production of aerospace parts by Electron Beam Powder Bed Fusion (EB-PBF). It is intended to be used for aerospace parts manufactured using additive manufacturing (AM) metal alloys, but usage is not limited to such applications.

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 With the recent advancement in technologies, researchers worldwide have a growing interest in unmanned aerial vehicles (UAVs). The last few years have been significant in terms of its global awareness, adoption, and applications across industries. In UAV-aided wireless networks, there are some limitations in terms of power consumption, data computation, data processing, endurance, and security. So, the idea of UAVs and Edge or Fog computing together deals with the limitations and provides intelligence at the network’s edge, which makes it more valuable to use in emergency applications. Fog computing distributes data in a decentralized way and blockchain also works on the principle of decentralization. Blockchain, as a decentralized database, uses cryptographic methods including hash functions and public key encryption to secure the user information. It is a prominent solution to secure the user’s information in blocks and maintain privacy.

This specification establishes process controls for the repeatable production of aerospace parts by Laser Powder Bed Fusion (L-PBF). It is intended to be used for aerospace parts manufactured using Additive Manufacturing (AM) metal alloys, but usage is not limited to such applications.

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.