Download PDF version Contact company

Green Hills Software, the pioneer in embedded safety and security, announces it has adopted the two new international security standards and regulations for automotive cybersecurity – ISO/SAE 21434 and UNECE WP.29 – for the INTEGRITY® real-time operating system (RTOS) and associated products and services.

For decades, Green Hills has been helping electronics manufacturers create and deploy embedded systems at the highest levels of safety and security. By offering compliant products and associated evidence reports for these new standards, Green Hills will build upon its proven pedigree as the foundational run-time software provider trusted by OEMs and their Tier 1 suppliers for automotive electronics.

Software-Defined services

Utilizing these new security standards enables manufacturers to design and deploy purpose-built, secure, software-defined systems in connected vehicles, including highly automated driving, high performance compute clusters, domain controllers, vehicle gateways, telematics, keyless entry, diagnostic connections and electric vehicle charging stations, to name a few.

As reliance on vehicle connectivity grows and demand for software-defined services rises, the risk of cyberattacks against connected vehicles continues to rise. With over 100 ECUs and hundreds of millions of lines of code, connected vehicles are a target-rich platform for cyberattacks.

Malicious vehicle control

A single exploited security vulnerability could put an entire fleet of vehicles at risk, numbering in the millions

Multiple points of entry to modern connected vehicles provide opportunities for malicious vehicle control, fraud, and data-breaches that threaten companies, drivers, and road users. A single exploited security vulnerability could put an entire fleet of vehicles at risk, numbering in the millions.

With nearly 80% of new cars connected to the internet, cybersecurity breaches have the potential to put billions of dollars in sales and lawsuits at risk – not to mention the damage to brand reputation. As a result, governmental bodies and independent regulators are drafting two related measures for managing cybersecurity threats throughout a connected vehicle’s lifecycle.

Ensuring cybersecurity risks

Green Hills is collaborating with its customers and adopting cybersecurity assessment policies for the following:

  • The draft ISO/SAE 21434 ‘Road vehicles – Cybersecurity engineering’ Standard was recently published by SAE International and ISO (Organization for Standardization). It is a baseline for vehicle manufacturers and suppliers to ensure cybersecurity risks are managed efficiently and effectively from both a product lifecycle and organizational perspective spanning concept, development, production, operation, maintenance, and decommissioning.
  • The WP.29 regulations from the United Nations Economic Commission for Europe (UNECE) make OEMs responsible for cybersecurity mitigation in four cybersecurity areas spanning the entire vehicle lifecycle: managing cyber risks; securing vehicles by design; detecting and responding to security incidents; and providing safe and secure over-the-air (OTA) software updates. While WP.29 defines concrete examples of threats and mitigations, OEMs can choose how they show the threats are addressed, such as complying with ISO/SAE 21434. The regulation is expected to be finalized in early 2021 and applied initially to many member nations including European nations, South Korea, UK, and Japan, and will likely influence vehicle homologation polices in the US, Canada and China. WP.29 will be legally binding within adopting countries, and while the ISO/SAE 21434 standard is not a regulation, it is expected to be widely accepted in the global industry like ISO 26262.

Connected vehicle electronics

Connected cars bring significant risks and rewards to OEMs and their suppliers,” said Chris Rommel, Executive Vice President, IoT & Industrial Technology at VDC Research. “Green Hills has earned a high stature in the industry for supplying security-critical foundational software to companies building life-critical systems like aircraft avionics, vehicle ADAS and medical equipment, and its support of these new cybersecurity standards is noteworthy.”

ISO/SAE 21434 and WP.29 are valuable additional steps towards protecting connected vehicles from cybersecurity vulnerabilities,” said Dan Mender, VP of Business Development at Green Hills Software. “Green Hills has decades of experience developing and delivering security-certified technologies at the highest levels. Adopting these standards expands our offerings to global automotive OEMs and their suppliers bringing the industry’s leading secure software run-time environment to next-generation connected vehicle electronics.”

Download PDF version Download PDF version

In case you missed it

What Is The Role Of Gunshot Detectors In The Security Ecosystem?
What Is The Role Of Gunshot Detectors In The Security Ecosystem?

Sadly, active shooter incidents have become so common that they no longer grab big headlines or dominate the news cycle. A near-constant cascade of active shooter events persists in the background of our collective consciousness, a familiar drumbeat that is no less tragic because it is continuous. As more active shooter incidents occur, the security marketplace continues to implement solutions to minimize the impact, including gunshot detection. We asked this week's Expert Panel Roundtable: What is the role of gunshot detectors in today’s security ecosystem? 

Mythic’s AI Chip Leverages Analog Technology For Faster Speed, Less Power
Mythic’s AI Chip Leverages Analog Technology For Faster Speed, Less Power

For security professionals who thought analog systems were a thing of the past, a new approach by Mythic Inc. demonstrates that everything old is new again. Using older technology in a new way, the Mythic M1076 Analog Matrix Processor leverages analog computer chips from a previous generation to drive new levels of artificial intelligence (AI) performance with lower power requirements.  Low power and high speed  Mythic provides power-efficient AI at the edge, including inside video cameras. The design combines embedded flash memory with analog computing power to achieve faster AI processing, supporting up to 25 trillion operations per second (TOPS), with the very-low power levels conducive to edge devices. The scalable, single-chip analog compute-in-memory architecture provides high-performance inference without consuming the power and energy that digital solutions require to move data at high speeds between separate processing and storage components. Single-chip design  High-resolution video analytics with low latency, comparable to a GPU, is provided by AI, but at 10 times less power “We use a different approach to processing and storage by resurrecting analog technology for faster computing power in a limited size and cost,” says Tim Vehling, Senior Vice President, Product and Business Development at Mythic. The Mythic chip solves several design challenges for camera manufacturers. The single-chip design with no DRAM (dynamic random-access memory) caters to limited space requirements. High-resolution video analytics with low latency, comparable to a graphics processing unit (GPU), is provided by AI, but at 10 times less power than a typical system on chip (SoC) or GPU. The typical 3-4-watt power draw is consistent with a limited power budget for power over Ethernet (PoE). Passive heat dissipation does not require active thermal management. Applications of the analog chip For video applications, the chip provides faster speed to accommodate more cameras, more resolution, and more details in images. In addition to providing scalability, the chip supports a variety of host platforms, including X86, NVIDIA Jetson Xavier NX/TX2, Qualcomm RB5, and NXP i.MX8M. It supports Linux Ubuntu 18.04 and Linus for Tegra (NVIDIA) operating systems. The chips can plug into NVIDIA or Qualcomm platforms to enhance AI capabilities for a variety of applications. The chip also has utility in other deployments, including drones, where Mythic works with the Qualcomm RBS platform to enable multi-thousand-dollar drones for larger applications. Integration into devices The chip can augment the capabilities of a CPU without replacing it or completely redesigning a product The chip handles image sensing, multiple cameras, radar, and lidar sensors, in addition to flight navigation, control, and communication, in addition to in-flight analytics. Inside NVRs, Mythic chips provide high-level processing at a fraction of the cost, says Vehling. Integration of the technology into cameras and other products is simple – it simply plugs into an M.2 expansion slot, and the software is downloaded to drive the AI algorithms. The chip can augment the capabilities of a CPU without replacing it or completely redesigning a product, in effect providing an instantaneous improvement in performance. No shortage Because Mythic uses older technology, there are no shortages compared to some later-generation chips. The 40-nanometer chips are a mature technology, manufactured in Japan, while newer processors are smaller at 5 or 7 nanometers. The newer chips are more likely to be in short supply. The Mythic M1076 chip is currently being evaluated but is not yet in production. The company expects to be shipping the product in the second half of 2022, and it will be sold to camera manufacturers and other OEMs to be incorporated into their products.  Adds value inside cameras For security end-users, Mythic’s AI chips will add new value inside video cameras and other equipment in terms of better performance, small size, and less power. For integrators, the technology will expand equipment options, such as providing high-level analytics in cameras while requiring only 2 to 3 watts of power, consistent with the use of PoE.

Why Face Recognition As A Credential Is The Ideal Choice For Access Control?
Why Face Recognition As A Credential Is The Ideal Choice For Access Control?

In the field of access control, face recognition has come a long way. Once considered too slow to authenticate people's identities and credentials in high traffic conditions, face recognition technology has evolved to become one of the quickest, most effective access control identity authentication solutions across all industries. Advancements in artificial intelligence and advanced neural network (ANN) technology from industry leaders like Intel have improved the accuracy and efficiency of face recognition. However, another reason the technology is gaining traction is due to the swiftly rising demand for touchless access control solutions that can help mitigate the spread of disease in public spaces. Effective for high volumes Face recognition eliminates security risks and is also virtually impossible to counterfeit Modern face recognition technology meets all the criteria for becoming the go-to solution for frictionless access control. It provides an accurate, non-invasive means of authenticating people's identities in high-traffic areas, including multi-tenant office buildings, industrial sites, and factories where multiple shifts per day are common. Typical electronic access control systems rely on people providing physical credentials, such as proximity cards, key fobs, or Bluetooth-enabled mobile phones, all of which can be misplaced, lost, or stolen. Face recognition eliminates these security risks and is also virtually impossible to counterfeit. Affordable biometric option Although there are other biometric tools available, face recognition offers significant advantages. Some technologies use hand geometry or iris scans, for example, but these options are generally slower and more expensive. This makes face recognition a natural application for day-to-day access control activities, including chronicling time and attendance for large workforces at construction sites, warehouses, and agricultural and mining operations. In addition to verifying personal credentials, face recognition can also identify whether an individual is wearing a facial covering in compliance with government or corporate mandates regarding health safety protocols. Beyond securing physical locations, face recognition can also be used to manage access to computers, as well as specialized equipment and devices. Overcoming challenges with AI So how did face recognition become so reliable when the technology was once dogged by many challenges, including difficulties with camera angles, certain types of facial expressions, and diverse lighting conditions? Thanks to the emergence of so-called "convolutional" neural network-based algorithms, engineers have been able to overcome these roadblocks. SecurOS FaceX face recognition solution FaceX is powered by neural networks and machine learning which makes it capable of authenticating a wide range of faces One joint effort between New Jersey-based Intelligent Security Systems (ISS) and tech giant Intel has created the SecurOS FaceX face recognition solution. FaceX is powered by neural networks and machine learning which makes it capable of authenticating a wide range of faces and facial expressions, including those captured under changing light, at different resolution levels, and varying distances from the video camera. Secure video management system A common face recognition system deployment begins with IP video cameras that feed footage into a secure video management system connected to a video archive. When the software initially enrolls a person’s face, it creates a "digital descriptor" that is stored as a numeric code that will forever be associated with one identity. The system encrypts and stores these numeric codes in a SQL database. For the sake of convenience and cost savings, the video server CPU performs all neural network processes without requiring any special GPU cards. Unique digital identifiers The next step involves correlating faces captured in a video recording with their unique digital descriptors on file. The system can compare newly captured images against large databases of known individuals or faces captured from video streams. Face recognition technology can provide multi-factor authentication, searching watchlists for specific types of features, such as age, hair color, gender, ethnicity, facial hair, glasses, headwear, and other identifying characteristics including bald spots. Robust encryption SED-compatible drives rely on dedicated chips that encrypt data with AES-128 or AES-256 To support privacy concerns, the entire system features an encrypted and secure login process that prevents unauthorized access to both the database and the archive. An additional layer of encryption is available through the use of Self-Encrypting Drives (SEDs) that hold video recordings and metadata. SED-compatible drives rely on dedicated chips that encrypt data with AES-128 or AES-256 (short for Advanced Encryption Standard). Anti-spoofing safeguards How do face recognition systems handle people who try to trick the system by wearing a costume mask or holding up a picture to hide their faces? FaceX from ISS, for example, includes anti-spoofing capabilities that essentially check for the "liveliness" of a given face. The algorithm can easily flag the flat, two-dimensional nature of a face mask, printed photo, or image on a mobile phone and issue a "spoof" alarm. Increased speed of entry Incorporating facial recognition into existing access control systems is straightforward and cost-effective Incorporating facial recognition into existing access control systems is straightforward and cost-effective. Systems can operate with off-the-shelf security cameras and computers. Users can also leverage existing infrastructure to maintain building aesthetics. A face recognition system can complete the process of detection and recognition in an instant, opening a door or turnstile in less than 500ms. Such efficiency can eliminate hours associated with security personnel checking and managing credentials manually. A vital tool Modern face recognition solutions are infinitely scalable to accommodate global enterprises. As a result, face recognition as a credential is increasingly being implemented for a wide range of applications that transcend traditional access control and physical security to include health safety and workforce management. All these capabilities make face recognition a natural, frictionless solution for managing access control, both in terms of performance and cost.