In the aerospace industry, competition is high and the need to ensure safety and security while managing costs is paramount. Furthermore, stakeholders—who gain the most by working together—do not necessarily trust each other. Now, mix that with changing enterprise technologies, management of historical records, and customized legacy systems. This issue touches all aspects of the aerospace industry, from frequent flyer miles to aircraft maintenance and drives tremendous inefficiency and cost.Technology that augments, rather than replaces, is needed to transform these complex systems into efficient, digital processes. Blockchain technology offers collaborative opportunities for solving some of the data problems that have long challenged the industry.This SAE EDGE™ Research Report by Rhonda D. Walthall examines how blockchain technology could impact the aerospace industry and addresses some of the unsettled concerns surrounding its implementation.{"uri":[{"xlink:href":"https://www.sae.org

Walthall, Rhonda

Algorithm Protects Networks by Detecting Adversarial Actions

TBMG-3780310/01/2020

Researchers developed a novel algorithm to protect networks by allowing for the detection of adversarial actions that can be missed by current analytical methods. A higher-order network could look for subtle changes in a stream of data that could point to suspicious activity.

Information Warfare - Staying Protected at the Edge

20AERP10_0210/01/2020

On April 1, 2001, a United States Navy EP-3E ARIES II signals intelligence aircraft and a Chinese People's Liberation Army Navy J-8II interceptor fighter jet collided above Hainan Island, China. Per protocol, the EP crew scrambled to destroy sensitive key-management data onboard the aircraft. However, the team was interrupted by opposing soldiers, and as a result failed to destroy cryptographic keys and other highly sensitive information on the plane. In a matter of seconds, U.S. secrets were in the hands of another nation, including intelligence documents, NSA employee names, defense plans, and other confidential documents. This exposure of information set back U.S. intelligence enough to impact the nation's defense strategy for years. Had this aircraft been equipped with hardware-embedded cyber defense capabilities such as instant secure erase (ISE), the complete compromise of sensitive data could have been prevented - U.S. troops would have been able to destroy the data with the

SAE project to develop cyber-secure EV charging

20AUTP10_1110/01/2020

Electric-vehicle charging is critical to the mainstreaming of EVs. A 2019 study by the International Council on Clean Transportation estimates that to create, by 2025, a charging network for the 100 U.S. metro areas with the highest populations will require 82,000 more EV charging stations at workplaces, 103,000 public stations with Level 2 (240-V) chargers and 10,000 direct current fast charging stations. That network must be cyber-secure, scalable and trusted by industry and the public. For this reason, SAE International and industry partners recently launched a collaborative project to strengthen EV charging system security. The SAE EV Charging Public Key Infrastructure (PKI) project will design and test, over the next 18-24 months, an inclusive, global EV charging PKI platform aimed at ensuring the interface points between EV drivers and EV charging infrastructure is secure and trusted. PKI is a best practice used across industries to ensure a high level of trust between entities

Brooke, Lindsay

Information Warfare: Staying Protected at the Edge

TBMG-3788110/01/2020

On April 1, 2001, a United States Navy EP-3E ARIES II signals intelligence aircraft and a Chinese People’s Liberation Army Navy J-8II interceptor fighter jet collided above Hainan Island, China. Per protocol, the EP crew scrambled to destroy sensitive key-management data onboard the aircraft. However, the team was interrupted by opposing soldiers, and as a result failed to destroy cryptographic keys and other highly sensitive information on the plane. In a matter of seconds, U.S. secrets were in the hands of another nation, including intelligence documents, NSA employee names, defense plans, and other confidential documents.

Algorithm Defends Against Side-Channel Attacks on Hardware

TBMG-3782010/01/2020

Electronic devices that used to rely on passwords now use Touch ID or face-recognition software. But protecting software is only one part of electronic security — hardware is also susceptible to attacks. Devices such as remote car keys, cable boxes, and even credit card chips are all vulnerable to hardware attacks, mostly because of their design. These devices are small and lightweight and typically operate on minimal power. Engineers optimize designs, so the devices can work within these low-power constraints.

Unsettled Technology Domains in Industrial Smart Assembly Tools Supporting Industry 4.0

EPR202001809/29/2020

“Smart” refers to tools that are “specific, measurable, achievable, reasonable/realistic, and time bound.” Smart assembly tools are used in many industries, including automotive, aerospace, and space for measuring, inspecting, gauging, drilling, and installing all existing fastening systems. Inside the Industry 4.0 environment, these tools have a huge influence on Information and Communication Technology (ICT), assembly cost reduction, process control, and even the product and process quality.These four domains—and their undefined nature—are the focus of this SAE EDGE™ Research Report. The technical issues identified here need to be discussed, the goals clarifying the scope of the industry-wide need to be aligned, and the issues requiring standardization need prioritized.NOTE: SAE EDGE Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE Research Reports is to

Roye, Thorsten

Development of a Secure Private Neural Network Capability

20AERP09_0409/01/2020

Machine Learning (ML) tools like Deep Neural Networks (DNNs) have gained widespread popularity due to their ability to quickly and accurately perform discriminative tasks, such as object detection and classification. However, current implementations of this concept have several drawbacks. First, traditional DNNs require access to unprotected (unencrypted) data. Even if the data is secured and the ML tool is made compatible for use with encrypted data, the resulting operational performance is slowed to the point that it renders the approach intractable. Second, recent research has shown many DNNs are susceptible to white box (full access to the machine learning tool and operations) and black box (only access to system input and output) attacks, allowing adversaries to maliciously manipulate the ML tool's output. In its short history, this concept has been successfully applied to a broad spectrum of problems: speech and image recognition, medical imagery diagnostics, drug discovery

Autonomy is Coming to Commercial Vehicles

20AVEP09_1009/01/2020

But not without its share of technical and implementation hurdles - and tech-startup casualties. Despite a pandemic that continues to punish global economic markets, not to mention vehicle manufacturers' and suppliers' product plans, many heavy-duty truck makers are not relaxing on efforts to bring to market high-level (SAE Level 4 or 5) autonomous trucks. Partnerships with self-driving tech startups can be a big part of the roadmap, the latest example coming in mid-July as Navistar announced it will co-develop SAE L4 trucks, targeted for production by 2024, with San Diego-based TuSimple. The producer of International commercial trucks and IC Bus school and commercial buses also has taken a minority stake in TuSimple. These moves follow a two-year “technical relationship” with the startup, which operates a U.S. fleet of 40 self-driving trucks that moves freight between Arizona and Texas for companies like UPS and McLane Company. TuSimple plans to demonstrate completely driverless

Gehm, Ryan

Development of a Secure Private Neural Network Capability

TBMG-3761409/01/2020

Operating System Software

TBMG-3760509/01/2020

Green Hills Software Santa Barbara, CA +1 805-965-0124

Smart Sensors for Hazardous Areas

TBMG-3766309/01/2020

Smart wireless sensors for rotating machines are deployed in thousands of installations worldwide. But producing a cost-effective and easy-to-deploy sensor solution for motors and pumps operating in hazardous areas, is a challenge. These are areas where the presence of flammable vapor or gases requires special precautions to prevent the risk of explosion. The lack of such sensors has limited the range of machinery that could be remotely monitored and has left a huge gap in the ability to gain meaningful information on the health and performance of motors that operate equipment such as pumps, fans, and compressors. It has also resulted in an increased safety risk for operators who need to venture into hazardous areas of plants to carry out condition monitoring of equipment.

Protecting Patients and Their Data from Cyberattacks Aimed at Their Connected Health Devices

TBMG-37357

08/01/2020

The security of connected health technology is often assumed to exist when it does not, or considered to be prohibitively expensive or complex, or, worst of all, relegated to an afterthought. This is dangerous thinking, especially as the industry increasingly moves to a smartphone-based command-and-control model for these safety-critical applications.

The Case for FOTA in AV Data Security

20AVEP07_0707/01/2020

Firmware over-the-air data transmission helps OEMs drive secure vehicle autonomy. Cars are increasingly becoming mobile living spaces. That's why the subject of security is so important for OEMs and suppliers. When a car becomes a personal mobile device that the owner uses for communications and personalizes with apps, it becomes vulnerable to opportunities for manipulation. Hacker attacks on connected cars have already made the headlines. In one example, a wireless connection was used to access the CAN bus that controls many network units in the vehicle. This allowed the hackers to remotely control the car and switch off the engine while it was in use. Other criminals have managed to gain control over brakes, door locks, air conditioners and windshield wipers. This is hardly surprising, since more and more vehicles have interfaces for exchanging data with the outside world.

Hilmer, Holger

MEDIA INDEPENDENT SECURE OFFBOARD NETWORK

ARINC848 (Current)06/19/2020

ARINC Specification 848 is a functional standard based on a protocol specification profile for a secured network interface. The purpose is to define a common method of initiating a mutually authenticated tunnel between an aircraft service and its Enterprise service. ARINC Specification 848 defines a standard implementation for securing the communications between an onboard Local Area Network (LAN) and an Enterprise LAN on the ground. Various aircraft network architectures and various air to ground communication channels (aka media) are accommodated in this document. For example, L-band Satellite Communication (Satcom), Ku/Ka-band Satcom, Gatelink Cellular, and Gatelink are considered.

Airlines Electronic Engineering Committee

Robotic Combat Vehicles: Putting the Brains Behind the Brawn

TBMG-3682205/01/2020

Autonomic and Apoptotic Highly Distributed System

TBMG-3683905/01/2020

NASA Goddard Space Flight Center has developed software that mimics the biological mechanisms of autonomic systems and apoptotic systems (the process that shuts down cells when they no longer serve a purpose). The software provides self-management and security for a distributed system such as a satellite swarm in which craft communicate and collaborate. Originally developed for space missions, this capability has now been extended for use in terrestrial applications involving cloud and grid-based systems and other applications requiring highly distributed operation.

Robotic Combat Vehicles

20AERP05_0405/01/2020

Putting the Brains Behind the Brawn A new era of Robotic Combat Vehicles (RCV) is about to begin. The U.S. Army is getting ready to evaluate competing candidates to meet requirements for light and medium versions of a new class of modular unmanned ground vehicle (UGV). Designed to be controlled in the field via remote control, and in the future, autonomously, these new robot tanks have the potential to revolutionize ground warfare. We witnessed the debut of this emerging class of “robo-tank” when the Ripsaw M5 was unveiled by the team of Textron Systems, Howe & Howe, and FLIR Systems at the Association of the U.S. Army (AUSA) Conference, in October 2019. A couple months later, in January, the Army announced contracts to buy eight experimental RCVs for use in wargame tests next year. QinetiQ North America, along with its partner Pratt & Miller, was selected to provide four of their EMAV robots (Expeditionary Modular Autonomous Vehicles). Textron was tapped to provide four of the Ripsaw

Enriching Systems Theory Based Cyber-Security and Safety Analysis Using Stakeholder Value Networks

2020-01-014304/14/2020

System-theoretic process analysis for security (STPA-Sec) is a powerful safety and security analysis method that focuses on unsafe and unsecure interactions between subsystems rather than component failure and its resulting chain-of-event failure modes. The first step of STPA-Sec requires the analyst to identify the system boundary and list the system losses and hazards. Current approach to performing this first and critical step of STPA-Sec requires interviewing the stakeholders and could potentially result in a narrow focus due to stakeholder’s mental model and resulting answers to questions. In some cases, stakeholders are not available for interviews and we risk influencing the system loss identification by the mental model of the analyst. We believe these two potential issues in the STPA-Sec analysis: narrow focus and missing access to stakeholder, can be address by factoring additional system information through stakeholder analysis. To illustrate the benefit of this approach a

Sidhu, Amardeep, Moulton, Allen

An Integrated View on Automotive SPICE, Functional Safety and Cyber-Security

2020-01-014504/14/2020

Automotive domain has seen safety engineering at the forefront of the industry’s priorities for the last decade. Therefore, additional safety engineering efforts, design approaches and well-established safety processes have been stipulated. Today many connected and automated vehicles are available and connectivity features and information sharing is increasingly used. This increases the attractiveness of an attack on vehicles and thus introduces new risks for vehicle cyber-security. Thus, just as safety became a critical part of the development in the late 20th century, the automotive domain must now consider cyber-security as an integral part of the development of modern vehicles. Aware of this fact, the automotive industry has therefore recently taken multiple efforts in designing and producing safe and secure connected and automated vehicles. As the domain geared up for the cyber-security challenges, they leveraged experiences from many other domains, but nevertheless, must face

Macher, Georg, Schmittner, Christoph, Dobaj, Jürgen, Armengaud, Eric, Messnarz, Richard

Safety development trend of the intelligent and connected vehicle and countermeasures for enterprise research and development

2020-01-008504/14/2020

Automotive safety is always the focus of consumers, the selling point of products, the focus of technology. In order to achieve automatic driving, interconnection with the outside world, human-automatic system interaction, the security connotation of intelligent and connected vehicles (ICV) changes: information security is the basis of its security. Functional safety ensures that the system is operating properly. Behavioral safety guarantees a secure interaction between people and vehicles. Passive security should not be weakened, but should be strengthened based on new constraints. In terms of information security, the threshold for attacking cloud, pipe, and vehicle information should be raised to ensure that ICV system does not fail due to malicious attacks. The cloud is divided into three cloud platforms according to functions: ICVs private cloud, TSP cloud, public cloud. The transmission side classifies three APNs based on usage: enterprise-owned APN, public network APN, and

Zhao, Fuquan, Tan, Hong, Liu, Zongwei

Test Method for the SAE J3138 Automotive Cyber Security Standard

2020-01-014204/14/2020

This paper will provide an Overview of Automotive Cyber Security Standards related to the Vehicle OBD-II Data Link. The OBD-II Connector Attack Tree is described with respect to the SAE J3138 requirements for Intrusive vs. non-Intrusive Services. A proposed test method for SAE J3138 is described including hardware and software scripting. Finally, example test results are reviewed and compared with a potential threat boundary.

Zachos, Mark

Hypervisor Implementation in Vehicle Networks

2020-01-133404/14/2020

As technology has grown in complexity, so have the use cases and applications. In particular, vehicle systems have evolved from the mechanically simple tool with the singular utility of transport to a transportation device embedded with computer systems, allowing for the vastly superior UX. As the technological advances and increased vehicular functionality, this has also increased the number of vulnerabilities and opportunity for a successful system breach. Any of these within the present architecture, when successfully exploited, may lead to a cascade of failures, or a limited number of critical failures. To mitigate this opportunity for the attackers, one non-obtrusive measure involves a method used in non-vehicle systems. The hypervisor implementation is recommended to assist with this mitigation. While this has not been researched at length in the present use case, the application of this well-versed tool is viable. The hypervisor offers many benefits to the vehicle architecture

Parker, Charles E., Wasen, Jessica

Automated Driving System Data Logger

J3197_202004 (Historical)

04/11/2020

This recommended practice provides common data output formats and definitions for a variety of data elements that may be useful for analyzing the performance of automated driving system (ADS) during an event that meets the trigger threshold criteria specified in this document. The document is intended to govern data element definitions, to provide a minimum data element set, and to specify a common ADS data logger record format as applicable for motor vehicle applications. The data elements defined in this document are unique to Levels 3, 4, or 5 ADS features, as defined by SAE J3016, and provide additional background of the events leading up to a crash or crash-like event. The data from sensors such as camera(s), LiDAR(s) etc. will provide information in the absence of a human driver. The data included in the ADS data logger is expected to be used in conjunction with the SAE J1698 EDR record and traditional accident reconstruction analysis. The event data recorder (EDR) and ADS data

Event Data Recorder Committee