Bosch worked with McKinsey to develop and launch CyberCompare—a cybersecurity purchasing platform to help businesses and public sector entities compare quotations and match with cybersecurity vendors and service providers.

Keeping companies safer by matching them with the right cybersecurity providers | McKinsey

Robert Bosch GmbH (/bɒʃ/; German: [bɔʃ] ), commonly known as Bosch (styled BOSCH), is a German multinational engineering and technology company headquartered in Gerlingen, Baden-Württemberg, Germany. The company was founded by Robert Bosch in Stuttgart in 1886.

Bosch (company) - Wikipedia

Safe, efficient, intelligent and powerful solutions for factory automation, mobile applications, machinery applications and engineering. Benefit now!

Bosch Rexroth. WE MOVE. YOU WIN. | Bosch Rexroth

Safe, efficient, intelligent and powerful solutions for factory automation, mobile applications, plant construction and engineering. Secure advantages now!

Bosch Rexroth. WE MOVE. YOU WIN | Bosch Rexroth USA

How Tara Bosch went from recipe testing in a basement kitchen to selling SmartSweets for $360 million

Bosch Company Profile, Stock Price, News, Rankings | Fortune

The Bosch Group is a leading global supplier of technology and services.

Company | Bosch Global

The Bosch Group is a leading global supplier of technology and services. It employs roughly 429,000 associates worldwide (as of December 31, 2023). The company generated sales of 91.6 billion euros in 2023. Its operations are divided into four business sectors: Mobility, Industrial Technology, ...

Company - Bosch Media Service

Bosch | 1,364,636 followers on LinkedIn. The Bosch Group is a leading global supplier of technology and services. It employs roughly 428,000 associates worldwide (as of December 31, 2023). According to preliminary figures, the company generated sales of 91.6 billion euros in 2023.

Bosch | LinkedIn

Engineered to meet the needs of workers. Bosch Tools take care of the job and you.

Bosch Power Tools | Boschtools

Moving stories and inspiring interviews. Experience the meaning of &quot;invented for life&quot; by Bosch completely new. Visit our international website.

Invented for life | Bosch Global

Bosch

bosch

We are back with another Company of the Week feature! Every week, we share an awesome tech brand from our tech company database, making their evergreen mark on the internet. This unique HackerNoon database ranks S&P 500 companies and top startups of the year alike. This week, we are proud to present Bosch! You may know Bosch for its excellent home appliances, but the German multinational engineering and technology company has a worldwide footprint across different business areas, including technology. Want to be featured on HackerNoon’s Company of the Week? Request Your Tech Company Page on HackerNoon! Bosch <> HackerNoon Tech Community Bosch recently utilized HackerNoon for its employer branding needs to advertise its software engineering and IT-related careers. Bosch’s Work #LikeABosch campaign was an excellent opportunity for the company to advertise some of its most in-demand jobs to a tech-focused audience, giving potential job seekers a chance to join an organization that has a simple motto: Grow. Enjoy. Inspire. Learn How You Can Book a Spot on HackerNoon’s Billboard Meet Bosch: #FunFact Remember how we said Bosch is more than just a home appliances company? Well, to drive that point home, Bosch recently published research on how it is using artificial intelligence to improve interior cameras that can help drivers on the road. The cool thing about Bosch’s approach? In addition to using real images, the company is also feeding synthetically generated images to its so-called occupant monitoring camera to improve outcomes. Yup, you read it right: the company is using AI to TEACH AI. You can read the research here: What is real? How artificial images make AI even smarter “It’s easy to overlook the fact that, over the long term, it’s AI more than anything else that will fundamentally change our world — even more so than the crises that are currently preoccupying us. But are we ready for this? Have we truly grasped how the technological structure of our world is changing? For me, the answer is no,” Bosch Chairman Stefan Hartung on why Europe needs the very best AI. Share Your Company's Story via HackerNoon That's all this week, folks! Stay Creative, Stay Iconic. The HackerNoon Team We are back with another Company of the Week feature! Every week, we share an awesome tech brand from our tech company database , making their evergreen mark on the internet. This unique HackerNoon database ranks S&P 500 companies and top startups of the year alike. Company of the Week Company of the Week tech company database tech company database This week, we are proud to present Bosch! You may know Bosch for its excellent home appliances, but the German multinational engineering and technology company has a worldwide footprint across different business areas, including technology. Bosch ! Bosch Want to be featured on HackerNoon’s Company of the Week? Request Your Tech Company Page on HackerNoon! Want to be featured on HackerNoon’s Company of the Week? Request Your Tech Company Page on HackerNoon ! Want to be featured on HackerNoon’s Company of the Week? Request Your Tech Company Page on HackerNoon Bosch <> HackerNoon Tech Community Bosch recently utilized HackerNoon for its employer branding needs to advertise its software engineering and IT-related careers. Bosch’s Work #LikeABosch campaign was an excellent opportunity for the company to advertise some of its most in-demand jobs to a tech-focused audience, giving potential job seekers a chance to join an organization that has a simple motto: Grow. Enjoy. Inspire. Bosch Work #LikeABosch Learn How You Can Book a Spot on HackerNoon’s Billboard Learn How You Can Book a Spot on HackerNoon’s Billboard Learn How You Can Book a Spot on HackerNoon’s Billboard Learn How You Can Book a Spot on HackerNoon’s Billboard Learn How You Can Book a Spot on HackerNoon’s Billboard Meet Bosch: #FunFact Remember how we said Bosch is more than just a home appliances company? Well, to drive that point home, Bosch recently published research on how it is using artificial intelligence to improve interior cameras that can help drivers on the road. The cool thing about Bosch’s approach? In addition to using real images, the company is also feeding synthetically generated images to its so-called occupant monitoring camera to improve outcomes. Yup, you read it right: the company is using AI to TEACH AI. TEACH You can read the research here: What is real? How artificial images make AI even smarter What is real? How artificial images make AI even smarter What is real? How artificial images make AI even smarter What is real? How artificial images make AI even smarter “It’s easy to overlook the fact that, over the long term, it’s AI more than anything else that will fundamentally change our world — even more so than the crises that are currently preoccupying us. But are we ready for this? Have we truly grasped how the technological structure of our world is changing? For me, the answer is no,” Bosch Chairman Stefan Hartung on why Europe needs the very best AI. “It’s easy to overlook the fact that, over the long term, it’s AI more than anything else that will fundamentally change our world — even more so than the crises that are currently preoccupying us. But are we ready for this? Have we truly grasped how the technological structure of our world is changing? For me, the answer is no,” Bosch Chairman Stefan Hartung on why Europe needs the very best AI. Share Your Company's Story via HackerNoon Share Your Company's Story via HackerNoon Share Your Company's Story via HackerNoon Share Your Company's Story via HackerNoon That's all this week, folks! Stay Creative, Stay Iconic. The HackerNoon Team

Meet Bosch: HackerNoon Company of the Week

মিট বশ: হ্যাকারনুন কোম্পানি অফ দ্য উইক

Lernen Sie Bosch kennen: HackerNoon-Unternehmen der Woche

Conozca a Bosch: la empresa de la semana de HackerNoon

Rencontrez Bosch : entreprise HackerNoon de la semaine

बॉश से मिलिए: हैकरनून कंपनी ऑफ द वीक

Bosch のご紹介: HackerNoon の今週の企業

Bosch를 만나보세요: 금주의 HackerNoon 회사

Conheça a Bosch: Empresa HackerNoon da Semana

Знакомьтесь, Bosch: компания недели HackerNoon

Bosch ile Tanışın: Haftanın HackerNoon Şirketi

Gặp gỡ Bosch: Công ty HackerNoon của Tuần

认识博世：HackerNoon 本周公司

Dremel 3D45 based on familiar devices are gaining popularity. This allows you to remove intermediaries and reduce the cost of maintaining devices. And we are pleased to present our collaboration with and Bosch, which led to the creation of an interesting project — a self-sustaining 3D Printing Service. Self-sustaining systems Dremel Project description The essence of the project is to create a remote 3D printing service. In which user uploads 3D model, after what to him showing information about the approximate time and cost of 3D model printing. Then service offers two payment methods: Pay immediately and Pay Per time. The cost of printing is calculated by the time spent and the amount of material. Immediately payment is made according to the approximate time of printing with payment before printing. For the implementation of this method took the team from Bosch Connectory, as they have the experience what was gained by creating a with payment in Bosch Coins. coffee machine When user choose Pay Per Time method, payments will be made through payment channels every n-time of the printer work. This method has advantages over Immediately payment: the user pays upon use of the service and materials, and nothing more; both parties are protected and everyone can at any time get their money on the fact of performed work. This method was implemented by our team. The speed and cheapness of transactions in the Byteball network allow you open a payment channel in seconds and all transactions on it are free and unlimited in number. Paying only for the opening and closing of the channel, which is less than 0.0001 €. After selecting a payment method, the user is displayed QR-code. After scanning it, you will receive payment information in Bosch Coins. In the end, when user will confirm the payment, printer will start printing. During a week of work in the office of Bosch Connectory, we have implemented the main core of this project. This is not the end of our work and we will continue remotely. At this stage, we need to “polish” the implemented and expand the functionality. In the final Our team is very grateful for the opportunity to work on such an interesting project. An interesting project like no one inspires to work productively. Special thanks I would like to Express to the team from Bosch Connectory: Gress Antonius, Tran Rui Lun and Roth Hannes. Contact us Follow our for last news, and join our community on Send us your questions and suggestions on — Twitter Telegram . team@biot.ws . Our website — https://biot.ws/

Bosch-BIoT: Self-sustaining 3D Printing service

, BOSCH Venture Capital . Although “a bigger unveil (one of the IOTA partnerships)” at the CES , it was still interesting to watch BOSCH’s tweets from their press conference: This article tries to show why IOTA’s technology perfectly fits in the company’s plans. As we have seen already has bought a “significant amount of IOTA tokens” had been postponed Note: This has not been confirmed by the IOTA Foundation, it’s just my own thoughts so please consider it as such. The overall situation Bosch is one of the biggest and most advanced companies within the realm of vehicle parts suppliers and IoT: Bosch ranked first in eight of nine key reputation attributes, making it the most admired automotive supplier worldwide. ( ) link As the European Patent Organisation confirmed for 2016 (more recent numbers are not available at the time of writing), BOSCH has the most granted patents of all European patentees: Bosch’s own focus these days is on the three S: https://twitter.com/boschusa/status/950404229897883648 As one of the executives at the CES in Las Vegas: said Of our nearly 400,000 associates worldwide, more than 20,000 are software engineers, nearly 20% of whom are working exclusively in IoT. Interestingly enough, this seems a perfect match for IOTA’s capabilities (that’s why BOSCH invested in it, of course). Yet the question remains what BOSCH could do with? Smart cities Smart cities will be huge topic in the near future, BOSCH’s tweet says it all: alone has announced a plan to invest $500m over the next seven years smart city infrastructure. In Bay area a beacon project has been launched which is supposed simply by using 5000 smart street lights. Las Vegas to save over $8m across 15 years Bosch sensors are the eyes and ears of the connected city. In this case, its brain is our software.(Mike Mansuetti, Preseident of Bosch North America) Furthermore it was stated that by 2020 all electronic products . As you can imagine, this will result in a incredible amount of data that will be set free. IOTA’s scaling capabilities and speed enable it to be the base-layer of all these transactions of information. In the following, I shall give an overview of some usecases which could technically be done using IOTA infrastructure. will be web-enabled Climate monitoring The idea here is to analyze the air quality, humidity and pollen concentration in order to improve the overall quality by putting measures into place if necessary. The product to gather the information is already working and : The Climo. has received the CES 2018 Innovation Award Several of these Climo boxes were deployed in Las Vegas right before the CES in order to show the capabilities to the conference attendees. Of course, the collected data can be “faked”, for example by positioning the boxes in a very “green/healthy” part of the city. However, the idea is to collect data from so many points that the overall number of information sources will prevent biased results. Moreover, you could also only focus on a specific area of the city in order to compare the data to other parts of the city. IOTA’s network called “tangle” would be the link between all the sensors. IOTA’s tangle would be the layer on which all of these information pieces are exchanged. To make this clearer: Imagine hundreds of Climos in Las Vegas sending their data every second to the = real time information. A sophisticated blockchain might be able to handle this, agreed. And such a blockchain might come up with a marketplace, agreed. Right, that’s hundreds of Climos +hundreds of thousands homes sending their data every second over a public ledger! And this is why IOTA is needed because it offers the , the and it has ! IOTA market place But what if hundreds of thousands of residents buy the technology for their own roof because they want to make good money by selling the data to air-quality-improving-companies’ R&D branches? speed scalabilty no transaction fees Collecting data about air quality can be done easily by companies, municpalities as well as by individuals. The incentive is to sell that data on a marketplace which in turn can be used by corporates to build products which will improve air quality again. It’s a win-win situation. Community-based parking Have you ever been in a city trying desperately to find a parking spot? BOSCH thought about this problem and their solution is simply brilliant: Cars driving past a parking space recognize spaces via sensors, and connection hardware and drivers receive the parking space information in real-time. They are then quickly and easily navigated towards an empty space. ( ) link Watch this short video to get the idea: Again, this is a lot of data: Every car sensors possible parking spots, transmits the data in real-time and the exact same data needs to be transfered to all the cars looking for a parking spot. Of course, this could be perfectly combined with self-driving vehicles: You just hop off at the store where you want to go, the car finds itself a spot to wait (or is used for other purposes in the meantime) and comes back to you once you are done. This sounds rather futuristic and utopian, but BOSCH . 20 US cities (such as Miami, LA and Boston) will offer this amazing technology ! has already equipped 1.5m cars with their IoT software in 2018 Again, this is so much data be produced for one city alone — but if it is successful, the whole world will want this technology and that means an incredible amount of data which needs to be processed. Since IOTA was tailored exactly for IoT cases like that, all the data could be transfered in real-time without any fees! One could also imagine a usecase like this: Before starting your trip in the car you reserve a free parking spot for a certain amount and can be sure to get this one (e.g. right in front of your destination). The possibilities are endless! Other usecases I think you got the gist so far: It’s a lot of information which can be used (if processed in real-time) to help individuals have a better/smarter/… life. The following are just some ideas how the technology can help us and each of these usecases would perfectly be doable using IOTA’s tangle as a base-layer: XDK You might ask: Fine, nice tech — but BOSCH using IOTA would need a working product by now? You are right, and this product really exits: the XDK. It is a small developer kit which collects various data (for example from machines) for later analysis: Dominik Schiener, Co-founder of IOTA, introduced how IOTA’s technology works on this kit: So BOSCH is apparently really interested in IOTA’s capabilities. These ideas are being made real as you are reading this. Of course, BOSCH is not the only company doing this. And since there are many others trying to make money establishing this kind of technology in countless industries: Yet neither consumers nor the companies want a different solution for each industry (imagine different standards among TVs and each producer would have to follow different sets of rules for different standards; we had this problem once between BluRay and HD-DVD; there could only be one…). So the question remains: What will be the standard protocol in IoT/Industry 4.0 to transfer and process all this data? In my opinion, there is only one candidate which offers everything that is needed: speed for real-time transactions scalability to handle millions and billions of transactions no costs in order to make it as attractive as possible the necessary connections with in the industries (partnerships, cooperations etc.) And guess what? The only existing tech out there offering each of these is IOTA even if it only at a rather early stage of its development. The time of thousands of cryptocurrencies is ending(95% of which are just copycats of Bitcoin without real usecases) — 2018 will be the year of real-world adoption and nobody is better prepared for this than IOTA (for more information in this regard read (more than 60,000 views within a week!). my previous articles If you want to, I would be happy about a little donation ;-): IOTA: KGOZYHJRYVDBSXTUSECYJVEBLDVYFKCAKAWTPTCKXMBNOWNVRDRHRVSJNIVOQUFRODFPXWYSGROKRWKRZWJZTJOHSX

IOTA: possible BOSCH usecases

VANCOUVER, Canada, March 18th, 2025/Chainwire/--The artificial intelligence landscape is evolving. Traditional AI models remain centralized, relying on static text data and corporate control. iAgent is introducing a decentralized AI framework where AI agents are trained, owned, and monetized on-chain using real-world visual data. iAgent iAgent Backed by a recent $3 million investment, iAgent has forged several strategic partnerships with leading projects such as Base, LayerZero, Avalanche, Aethir, Arbitrum, and XAI Games. With over 700,000 users on its AGNTxp platform, iAgent is at the forefront of AI x Gaming x DePIN innovation. Now, with TGE live, iAgent is laying the foundation for AI Agents to become a new digital asset that can be trained, validated, and exchanged transparently. "AI should be decentralized, transparent, and monetizable. iAgent is ensuring AI models belong to those who train them, not corporations." — Jamie Batzorig, Co-Founder of iAgent. "AI should be decentralized, transparent, and monetizable. iAgent is ensuring AI models belong to those who train them, not corporations." — Jamie Batzorig, Co-Founder of iAgent. iAgent’s Product Hub: Powering the AI Economy iAgent’s ecosystem consists of a suite of interconnected products aimed at supporting AI development, deployment, and monetization through a decentralized framework. Each component is designed to enhance the verifiability, scalability, and accessibility of AI models across various ecosystems. Visual Learning Model (VLM): Adaptive AI Training Unlike traditional AI that relies on text-based training (LLMs), iAgent’s Visual Learning Models (VLMs) enable AI agents to learn from real-world gameplay footage. This approach allows AI to analyze, strategize, and adapt dynamically, making them more intelligent and applicable in real-world scenarios. iAgent’s VLM-powered AI utilizes real-player interactions to enhance its adaptability, enabling continuous optimization for performance in competitive gaming environments and other applications: Current live for Counter Strike 2, Off the Grid & Citizen Conflict. Players have already contributed 25 TB+ gameplay data.
Over 10,000+ hours of gameplay footage recorded Players have already contributed 25 TB+ gameplay data. Over 10,000+ hours of gameplay footage recorded ERC-** Agent Standard: A New AI Digital Asset Class iAgent’s ERC-** standard will bring AI Agents on-chain as verifiable, secure, and interoperable digital assets. This aims to enable true ownership, trading, and cross-chain utilization without centralized control. While enhancing trust and transparency through provable authenticity and ownership history. AI Agent Marketplace: The Open AI Economy The AI Agent Marketplace serves as the foundation of iAgent’s decentralized ecosystem, enabling seamless AI model deployment, trading, and monetization. Developers can list AI-powered agents for rental or sale, while businesses and game studios can purchase or integrate AI models tailored to their needs. iAgent DEV Hub: Decentralized AI Infrastructure The iAgent DEV Hub acts as the backbone of the protocol, offering developers and AI researchers a comprehensive suite of tools, SDKs, and APIs to build and optimize AI models. It provides a trustless AI validation framework, leveraging on-chain verification nodes, cross-DePIN compute integration, and AI execution tracking. AI in Gaming: The Next Evolution of Intelligent Agents Gaming offers high-quality, labeled data, making it a suitable environment for training advanced AI models. iAgent is introducing adaptive AI agents to gaming, facilitating: AI-powered game assistants – AI agents that analyze in-game movements, provide real-time coaching and improve player performance in FPS games like Valorant.
Smart NPCs that evolve dynamically – NPCs in RPGs like World of Warcraft that learn and adapt to a player’s choices, creating truly immersive experiences.
AI anti-cheat and security systems – AI in games like CS2 that detects aimbots and wallhacks in real-time, ensuring fair gameplay.
Predictive AI for in-game economies – AI models that track in-game trends, helping players optimize asset trading in games like Diablo 4. AI-powered game assistants – AI agents that analyze in-game movements, provide real-time coaching and improve player performance in FPS games like Valorant. Smart NPCs that evolve dynamically – NPCs in RPGs like World of Warcraft that learn and adapt to a player’s choices, creating truly immersive experiences. AI anti-cheat and security systems – AI in games like CS2 that detects aimbots and wallhacks in real-time, ensuring fair gameplay. Predictive AI for in-game economies – AI models that track in-game trends, helping players optimize asset trading in games like Diablo 4. iAgent’s decentralized AI infrastructure will expand beyond gaming, creating an open AI economy applicable across industries. "Gaming is the first major use case, but our AI infrastructure will extend to multiple sectors. AI models will be owned, monetized, and deployed across various real-world applications." — MHL Solutions, iAgent Advisor. "Gaming is the first major use case, but our AI infrastructure will extend to multiple sectors. AI models will be owned, monetized, and deployed across various real-world applications." — MHL Solutions, iAgent Advisor. Roadmap: From Foundation to AI Economy 2023-2024: Establishing the iAgent Protocol Development of Visual Learning Models (VLMs) and AI ownership framework.
AGNTxp launch, onboarding 700K+ users and generating 75K+ AI identities.
AI data collection platform, accumulating 25+ TB+ gameplay data.
Genesis Node Sale to decentralize AI model validation and verification. Development of Visual Learning Models (VLMs) and AI ownership framework. AGNTxp launch, onboarding 700K+ users and generating 75K+ AI identities. AI data collection platform, accumulating 25+ TB+ gameplay data. Genesis Node Sale to decentralize AI model validation and verification. 2025: Scaling AI Deployment & Monetization March 2025: TGE live, launching $AGNT as the core AI economy token.
On-chain governance rollout, enabling staking & liquid staking. TGE live, launching $AGNT as the core AI economy token. On-chain governance rollout, enabling staking & liquid staking. April 2025: AI Agent Marketplace launch, enabling AI deployment, trading, and rental.
ERC-** Standard proposal, formalizing AI ownership and validation. AI Agent Marketplace launch, enabling AI deployment, trading, and rental. ERC-** Standard proposal, formalizing AI ownership and validation. May 2025: AGNT-Hub powered by $AGNT. AGNT-Hub powered by $AGNT. June 2025: AI Agent Explorer & Analytics Platform, enabling transparent AI tracking. AI Agent Explorer & Analytics Platform, enabling transparent AI tracking. Q3 2025: Integration of VLM-powered AI into partner games in the AAA and indie gaming ecosystem.
Visual Data Monetization framework, allowing users to sell gameplay data to train AI. Integration of VLM-powered AI into partner games in the AAA and indie gaming ecosystem. Visual Data Monetization framework, allowing users to sell gameplay data to train AI. Q4 2025: Protocol Testnet Launch, deploying decentralized AI compute infrastructure.
Mainnet launch, establishing the fully operational iAgent Protocol. Protocol Testnet Launch, deploying decentralized AI compute infrastructure. Mainnet launch, establishing the fully operational iAgent Protocol. AGNT: Advancing Practical Applications in AI and Blockchain As the core of the iAgent ecosystem, AGNT enables: AI Training & Trading – AI models can be owned, sold, and deployed through the marketplace.
Compute & Staking Rewards – GPU node operators are incentivized for providing AI training power.
Visual Data Monetization – Users can get AGNT by contributing high-quality labeled data.
Governance Participation – AGNT holders shape the evolution of iAgent’s decentralized AI infrastructure. AI Training & Trading – AI models can be owned, sold, and deployed through the marketplace. Compute & Staking Rewards – GPU node operators are incentivized for providing AI training power. Visual Data Monetization – Users can get AGNT by contributing high-quality labeled data. Governance Participation – AGNT holders shape the evolution of iAgent’s decentralized AI infrastructure. AI is Becoming an Asset Class, and iAgent is Leading the Way. The AI, gaming, and DePIN industry is set to grow from $553.7 billion today to $2.8 trillion by 2030. iAgent aims to build the infrastructure for this growth. About iAgent Protocol iAgent’s Visual Learning Model allows gamers to train custom AI agents from their gameplay footage, powered by decentralized computing. By leveraging blockchain technology, it introduces a new digital asset class, enabling users to Create, Own, and Monetize their AI agents in gaming. iAgent’s iAgent’s Founded by a powerhouse team of industry veterans and innovators, iAgent's leadership team includes eight C-level executives with a combined 20+ years of experience at Fortune 500 companies, driving strategic growth and innovation. On the tech front, the team comprises 12 top-tier AI and blockchain engineers, bringing expertise from global giants like Bosch, Meta, Airbus, and Samsung. The best minds shaping the future of AI x Gaming x DePIN together. Website | Twitter | Telegram | Discord | Whitepaper | Linktree Website Website Twitter Twitter Telegram Telegram Discord Discord Whitepaper Whitepaper Linktree Linktree Contact Co-Founder & CEO Jamie Batzorig iAgent Corporation jamie@iagentpro.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

iAgent Secures $3M, Launches $AGNT, And Will Introduce a New ERC-**Standard For AI Agents

iAgent beveilig $3 miljoen, stel $AGNT bekend en sal 'n nuwe ERC-**-standaard vir KI-agente bekendstel

iAgent zajistí 3 miliony dolarů, spouští AGNT $ a představí nový standard ERC-** pro AI agenty

iAgent obtiene 3 millones de dólares, lanza $AGNT y presentará un nuevo estándar ERC-** para agentes de IA

iAgent lève 3 millions de dollars, lance $AGNT et introduira une nouvelle norme ERC-** pour les agents IA

iAgent ने $3M हासिल किया, $AGNT लॉन्च किया, और AI एजेंटों के लिए एक नया ERC-**मानक पेश करेगा

iAgent Sekirize $3M, lanse $AGNT, epi li pral prezante yon nouvo ERC-**Standa pou ajan AI.

iAgent が 300 万ドルを調達し、$AGNT を立ち上げ、AI エージェント向けの新しい ERC-** 標準を導入

„iAgent“ užsitikrina 3 mln. USD, paleidžia USD AGNT ir pristatys naują ERC-** DI agentų standartą

iAgent garante US$ 3 milhões, lança $AGNT e apresentará um novo padrão ERC-**para agentes de IA

iAgent Yizewe $ 3M, Itangiza $ AGNT, Kandi Izana ERC Nshya - ** Ibisanzwe kubakozi ba AI

iAgent säkrar $3 miljoner, lanserar $AGNT och kommer att introducera en ny ERC-**-standard för AI-agenter

iAgent 3 миллион долларро таъмин мекунад, $AGNT-ро оғоз мекунад ва ERC-** стандарти нави агентҳои AI-ро ҷорӣ мекунад

Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2. Current Security Testing Platforms 2. Current Security Testing Platforms 2.1. Recent progress 2.1. Recent progress 3. A New Testing Platform and 3.1. Testing platform roles 3. A New Testing Platform and 3.1. Testing platform roles 3.2. Web-based remote access 3.2. Web-based remote access 3.3. Testbed setup 3.3. Testbed setup 4. Enabled Testing Methodologies 4.1. Secure Development Lifecycle (SDL) testing and 4.2. Penetration testing 4.1. Secure Development Lifecycle (SDL) testing and 4.2. Penetration testing 4.3. Research testing 4.3. Research testing 5. Conclusion & Outlook, and References 5. Conclusion & Outlook, and References 5. Conclusion & Outlook With vehicles becoming more software-defined, the need for higher quality and more automated security testing is evident. A flexible, easy-to-use, and remote-capable test platform not only improves the current industry testing capabilities, but it can also potentially provide easier access to logistically challenging and costly hardware. This allows the industry access a larger pool of talent for testing and allows more people to learn about automotive components. Furthermore, we see potential in leveraging this type of cloud-based platform to reduce costs and increase participation for global hacking competitions and Bug Bounty programs. That being said, the ideal testing platform is one that the community will actually use and implement in their research, development, and production. In this work, we propose several well-defined methodologies to build a useful and configurable remote testing platform. However, as the needs of the automotive security industry changes, this testing platform should be able to adapt and be as flexible as possible. Once other testing platforms mature, future work should investigate the different underlying technologies and features used to build these platforms and explore relevant trade-offs and limitations. References [1] CanBusHack. Cloudcar. Available at https://cloudcar.canbushack. com/. Accessed on 2024-03-15. [2] Sam Curry. Web hackers vs. the auto industry: Critical vulnerabilities in ferrari, bmw, rolls royce, porsche, and more. Available at https://samcurry.net/web-hackers-vs-the-auto-industry/. Accessed on 2024-03-15. [3] International Organization for Standardization. ISO/SAE 21434: 2021: Road Vehicles: Cybersecurity Engineering. ISO, 2021. [4] Eclipse Foundation. Eclipse opendut. Available at https://projects. eclipse.org/projects/automotive.opendut. Accessed on 2024-03-15. [5] Stefan Gehrer, Jorge Guajardo Merchan, and Shalabh Jain. System and method for intrusion detection on a physical level using an internal analog to digital converter, March 31 2022. US Patent App. 17/032,624. [6] Block Harbor. Block harbor vsec. Available at https://blockharbor. io/vsec-platform/. Accessed on 2024-03-15. [7] Jake Jepson, Subhojeet Mukherjee, Martin Span, and Jeremy Daily. Canlay: A network virtualized testbed for vehicle systems– improving system integration and verification efforts. In INCOSE International Symposium, volume 33, pages 1–16. Wiley Online Library, 2023. [8] Keysight. Sa8710a automotive cybersecurity test platform. Available at https://www.keysight.com/us/en/product/SA8710A/ automotive-cybersecurity-penetration-test-platform.html. Accessed on 2024-03-15. [9] Sekar Kulandaivel. Revisiting remote attack kill-chains on modern in-vehicle networks. PhD thesis, Carnegie Mellon University, 2021. [10] Sekar Kulandaivel, Tushar Goyal, Arnav Kumar Agrawal, and Vyas Sekar. {CANvas}: Fast and inexpensive automotive network mapping. In 28th USENIX Security Symposium (USENIX Security 19), pages 389–405, 2019. [11] Sekar Kulandaivel, Shalabh Jain, Jorge Guajardo, and Vyas Sekar. Cannon: Reliable and stealthy remote shutdown attacks via unaltered automotive microcontrollers. In 2021 IEEE Symposium on Security and Privacy (SP), pages 195–210. IEEE, 2021. [12] Shahid Mahmood, Hoang Nga Nguyen, and Siraj A Shaikh. Automotive cybersecurity testing: Survey of testbeds and methods. Digital Transformation, Cyber Security and Resilience of Modern Societies, pages 219–243, 2021. [13] BG Networks. Bg networks crate. Available at https://bgnetworks. com/crate/. Accessed on 2024-03-15. [14] Mert D Pese, Troy Stacer, C Andr ´ es Campos, Eric Newberry, ´ Dongyao Chen, and Kang G Shin. Librecan: Automated can message translator. In Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, pages 2283–2300, 2019. [15] CARLA Team. Carla open-source simulator for autonomous driving research. Available at https://carla.org/. Accessed on 2024-03- 15. [16] GRVA WP29 UNECE. Un regulation no. 155—cyber security and cyber security management system. Technical report, Technical Report. United Nations, 2021. [17] VDA. Automotive spice. Available at https://vda-qmc.de/en/ automotive-spice/. Accessed on 2024-03-15. [18] Vector. Vector vt system. Available at https://www.vector.com/int/ en/products/products-a-z/hardware/vt-system/#c174985. Accessed on 2024-03-15. [19] VicOne. Vicone automotive cyberthreat landscape report 2023. Available at https://documents.vicone.com/reports/ automotive-cyberthreat-landscape-report-2023.pdf. Accessed on 2024-03-15. [20] Anthony Kee Teck Yeo, Matheus E. Garbelini, Sudipta Chattopadhyay, and Jianying Zhou. Vitrobench: Manipulating in-vehicle networks and cots ecus on your bench: A comprehensive test platform for automotive cybersecurity research. Vehicular Communications, 43, 2023. This paper is available on arxiv under CC BY 4.0 DEED. This paper is available on arxiv under CC BY 4.0 DEED. available on arxiv Authors:
(1) Sekar Kulandaivel, Robert Bosch LLC — Research and Technology Center;
(2) Wenjuan Lu, Block Harbor Cybersecurity;
(3) Brandon Barry, Block Harbor Cybersecurity;
(4) Jorge Guajardo, Robert Bosch LLC — Research and Technology Center. Authors: Authors: (1) Sekar Kulandaivel, Robert Bosch LLC — Research and Technology Center; (2) Wenjuan Lu, Block Harbor Cybersecurity; (3) Brandon Barry, Block Harbor Cybersecurity; (4) Jorge Guajardo, Robert Bosch LLC — Research and Technology Center.

The Future of Automated Security Testing

Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2. Current Security Testing Platforms 2. Current Security Testing Platforms 2.1. Recent progress 2.1. Recent progress 3. A New Testing Platform and 3.1. Testing platform roles 3. A New Testing Platform and 3.1. Testing platform roles 3.2. Web-based remote access 3.2. Web-based remote access 3.3. Testbed setup 3.3. Testbed setup 4. Enabled Testing Methodologies 4.1. Secure Development Lifecycle (SDL) testing and 4.2. Penetration testing 4.1. Secure Development Lifecycle (SDL) testing and 4.2. Penetration testing 4.3. Research testing 4.3. Research testing 5. Conclusion & Outlook, and References 5. Conclusion & Outlook, and References 4. Enabled Testing Methodologies 4.1. Secure Development Lifecycle (SDL) testing VSEC Test aims to integrate all methods of vehicle cybersecurity testing into a single easy-to-use platform. As discussed above, a portion of cybersecurity verification, as required by the ISO/SAE standard, is no different than software and systems verification required by other industry standards. The remote capabilities and test management features offered by VSEC Test allows test engineers to design and set up the test procedures one time in order to run on a schedule or triggered by other tools as a part of CI/CD frameworks. This centralized platform for test procedures and results can potentially be used to exchange data throughout the supply chain and ensure consistent verification test coverage for the development life cycle of a vehicle. For example, we perform continuous cybersecurity functional testing on components with over-the-air (OTA) update functionality as a service. We set up the test rack and develop the test procedures once on VSEC Test, and it is performed on a periodic schedule and also whenever a new software update is applied. Continuous functional testing against cybersecurity requirements effectively identified vulnerabilities that were overlooked during the development cycle. In addition, VSEC Test provides a set of built-in tests as a preliminary scan for known weaknesses and vulnerabilities, which can be used directly against a target vehicle or ECU. This scan can allow users to easily and quickly determine if there are large gaps in measures protecting the interface or if there are known exploits that will work on the target vehicle or ECU. 4.2. Penetration testing Pentesting approaches. Most pentest engagements start with an exploratory phase, where the tester aims to discover as much information about the target as possible. The duration and effort in this phase is largely determined by the amount of information available to the tester. VSEC Test allows users to build a pool of their own test scripts or use built-in discovery scans specifically targeting automotive networks, including protocols such as UDS and XCP. These tests can be queued up and ran in the background or over the weekend, saving time and allowing a team to focus on more technically challenging tasks or other projects. The web interface allows testers to access and check on test status at any time from anywhere to determine the next step of action. Pentesting approaches. Partner Pentesting. A major difficulty in accessing the talent pool of world-class vehicle penetration testers is physical location. The VSEC Test platform enables any remote engineer with credentials to connect to the bench and handle any physical interactions with the component and remotely script and execute tests from VSEC Test. We call this Partner Pentesting. Partner Pentesting. To evaluate the Partner Pentesting concept, we set up a scenario as depicted in Figure 2, where a remote wireless penetration testing specialist is working with a local test engineer to control a software-defined radio connected to the cloud and capture communication between the key fob and the car in addition to any vehicle network messages. The specialist then proceeds to study and decode the traffic, create scripts to attack the communication, and work together with the local test engineer to validate findings. In this case, without physical access to the vehicle and a local partner to perform tasks, it would have been very difficult to perform a meaningful penetration test against the vehicle’s wireless entry system. Side-channel analysis. On the other hand, we have other benches in the lab can be tested with little to no user interactions. For these targets, fully remote networklevel penetration test with a test bench setup can achieve results on-par with on-site engagements. However, we found that more hands-on penetration testing procedures such as hardware analysis and side channel attacks are still very difficult to perform without having an onsite specialist. As a result, while acceptable for many scenarios, fully remote penetration testing remains very limited for certain configurations due to manual activation required for physical interfaces and required hardware and tooling interaction for certain procedures. However, we are able to make progress with a Partner Pentesting setup that provides assistance from onsite personnel and achieves comparable outcomes as a fully onsite engagement. Side-channel analysis. This paper is available on arxiv under CC BY 4.0 DEED. This paper is available on arxiv under CC BY 4.0 DEED. available on arxiv Authors:
(1) Sekar Kulandaivel, Robert Bosch LLC — Research and Technology Center;
(2) Wenjuan Lu, Block Harbor Cybersecurity;
(3) Brandon Barry, Block Harbor Cybersecurity;
(4) Jorge Guajardo, Robert Bosch LLC — Research and Technology Center. Authors: Authors: (1) Sekar Kulandaivel, Robert Bosch LLC — Research and Technology Center; (2) Wenjuan Lu, Block Harbor Cybersecurity; (3) Brandon Barry, Block Harbor Cybersecurity; (4) Jorge Guajardo, Robert Bosch LLC — Research and Technology Center.

Enabled Testing Methodologies: Secure Development Lifecycle (SDL) Testing and Penetration Testing

Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2. Current Security Testing Platforms 2. Current Security Testing Platforms 2.1. Recent progress 2.1. Recent progress 3. A New Testing Platform and 3.1. Testing platform roles 3. A New Testing Platform and 3.1. Testing platform roles 3.2. Web-based remote access 3.2. Web-based remote access 3.3. Testbed setup 3.3. Testbed setup 4. Enabled Testing Methodologies 4.1. Secure Development Lifecycle (SDL) testing and 4.2. Penetration testing 4.1. Secure Development Lifecycle (SDL) testing and 4.2. Penetration testing 4.3. Research testing 4.3. Research testing 5. Conclusion & Outlook, and References 5. Conclusion & Outlook, and References 3.3. Testbed setup Sourcing ECUs. In the context of this work, we define ECUs as production ECUs from the field (i.e., real vehicles), engineering samples (e.g., A-samples, Bsamples), or even off-the-shelf automotive-grade microcontrollers (MCUs). Depending on the user, obtaining ECUs for the testing platform will require different approaches. Where an engineer and pentester would get hardware from their own supply chain or from the contracted customer, respectively, a researcher would likely obtain ECUs from a real vehicle from either a salvage yard or buying ECUs directly from OEM parts shops. Sourcing ECUs. Testing a single ECU can be sufficient if the tests are focused on purely CAN physical layer specifics or other singleECU session-based protocols, such as Unified Diagnostic Services (UDS) protocol and Universal Measurement and Calibration Protocol (XCP). In some cases, multiple ECUs are needed to wake up certain ECUs (e.g., a powertrain ECU may require a body ECU and vice versa), although we have reverse-engineered some of these wake-up messages. For our platform, we source ECUs across three different OEMs from a local salvage yard and from a real vehicle: five powertrain ECUs (two pairs of duplicates from different model years), a gateway ECU, a power steering ECU, and two instrument panel clusters (IPCs). We also acquire a C-sample gateway ECU from one of the aforementioned OEMs, which matches the OEM of one of the IPCs. Additionally, we also obtain a CANenabled automotive-grade MCU with full programming capabilities. Configurable network. Most users will often work on projects that require ECUs with different bus speeds, different OEMs, and different attached hardware (e.g., measurement tools, actuators, etc.) As such, it is necessary for a testing platform to provide the ability to configure the platform remotely. The alternative here is having access to multiple real vehicles or (re)building separate test beds, which is expensive and harder to manage. We build a prototype of a configurable CAN bus network system that supports multiple bus speeds, multiple ECUs from multiple OEMs, and the ability to switch on/off the power of each ECU on-demand via VSEC Test. Configurable network. In Figure 1, we depict an example of of a single platform that: (1) hosts multiple buses with different bus speeds, (2) multiple OEM platforms on one bench, and (3) the ability to control the network topology. The figure demonstrates what the entire bench looks like with ECUs from three different OEMs as well as how our testing platform would bring up a network consisting of just ECUs from OEM #1 and OEM #2. Using a relay board that powers on/off each ECU on command, a tester could also isolate a single ECU or subset of ECUs from the entire set. The ability to slowly ramp up the number of ECUs under test is useful when developing a technique (e.g., a new attack), and the ability to test a technique against multiple OEM implementations can determine the applicability of the technique. For our platform, we construct a configurable network by attaching the power supply of each ECU to a 16-port relay board,[1] which is controlled by an Arduino Due MCU. A script on the tester PC communicates with this MCU over Serial, and the code on the Arduino toggles the user-specified ECU to activate/deactivate. In this work, we focus on CAN buses, and adding a new bus protocol such as Automotive Ethernet or CAN-FD would be similar. Network simulation. Real CAN traffic from road tests is often only available after a vehicle is in production. This traffic is usually the only information a researcher can access to simulate the bus network. Reverse-engineering CAN traffic can successfully uncover which CAN messages control which vehicle features/sensors [14], [20]. Engineers and some pentesters (depending on the contract) have access to proprietary CAN database (DBC) files, which identify the producer/consumer of each signal for all CAN messages. An alternative source of information for engineers and pentesters are Restbus simulations, which provides sufficient CAN traffic for the ECU under test to function as expected. For our platform, we investigated another method of obtaining a larger network of ECUs by combining the traffic from multiple ECUs that belong to the same make and model but are physically-distributed. We implemented a test bed with an IPC located in Pennsylvania and remotely connected to a powertrain ECU hosted in Michigan. While there is some latency involved with forwarding CAN traffic between these two locations, the latency is small enough to enable access to most UDS commands and exhibit control of the IPC without any obvious delays. Network simulation. Environment simulation. While reverse-engineering and proprietary DBC files can enable users to interpret CAN signals, it is still challenging to mimic traffic from road tests without spending hours driving a vehicle. Users can utilize driving simulators, such as CARLA [15], to provide hours and miles of Environment simulation. simulated road traffic. Combining these simulators with either a reverse-engineered or original DBC file can generate realistic CAN bus traffic to the ECUs under test. Engineers often have access to advanced sensor and actuator models that can significantly enhance the realism of the CAN bus traffic. While these models are typically deployed in software-only simulations, they could be connected to our testing platform to capture results only observed on real hardware. For our testing platform, we utilize CARLA in combination with a DBC file to provide realistic speed values to an IPC and then deploy an intrusion detection system (IDS) from prior work [5] as if it were in a real car. Measurement tools. We expand the capabilities of the platform by connecting measurement tools, such as oscilloscopes and logic analyzers, and offering software control of these tools. As these tools are often expensive, a platform with centralized hardware can reduce overall hardware costs by permitting shared access to these tools. For our platform, we connect a Picoscope oscilloscope to the power pins of an ECU and a Saleae logic analyzer to all of our CAN buses. Via command-line scripts, the Picoscope can capture power profiles as input to the aforementioned IDS. Additionally, the logic analyzer can observe bit-level CAN bus traffic for the purpose of building advanced CAN bus attacks [9]–[11]. Measurement tools. This paper is available on arxiv under CC BY 4.0 DEED. This paper is available on arxiv under CC BY 4.0 DEED. available on arxiv [1] The ignition pin can be powered by a separate relay if needed, thus having up to 16 ports can help control both main power and ignition while maximizing the number of ECUs under test. Authors:
(1) Sekar Kulandaivel, Robert Bosch LLC — Research and Technology Center;
(2) Wenjuan Lu, Block Harbor Cybersecurity;
(3) Brandon Barry, Block Harbor Cybersecurity;
(4) Jorge Guajardo, Robert Bosch LLC — Research and Technology Center. Authors: Authors: (1) Sekar Kulandaivel, Robert Bosch LLC — Research and Technology Center; (2) Wenjuan Lu, Block Harbor Cybersecurity; (3) Brandon Barry, Block Harbor Cybersecurity; (4) Jorge Guajardo, Robert Bosch LLC — Research and Technology Center.

Our Testbed Setup: Sourcing ECUs, Configurable Network, and Network Simulation

Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2. Current Security Testing Platforms 2. Current Security Testing Platforms 2.1. Recent progress 2.1. Recent progress 3. A New Testing Platform and 3.1. Testing platform roles 3. A New Testing Platform and 3.1. Testing platform roles 3.2. Web-based remote access 3.2. Web-based remote access 3.3. Testbed setup 3.3. Testbed setup 4. Enabled Testing Methodologies 4.1. Secure Development Lifecycle (SDL) testing and 4.2. Penetration testing 4.1. Secure Development Lifecycle (SDL) testing and 4.2. Penetration testing 4.3. Research testing 4.3. Research testing 5. Conclusion & Outlook, and References 5. Conclusion & Outlook, and References 3.2. Web-based remote access The first step to developing a user-friendly testing platform is providing an easy-to-use and familiar interface. Vehicle Security Engineering Cloud [6] (VSEC) is a cloud-based platform that aims to connect and automate various steps of the vehicle cybersecurity engineering process. A major problem we see in the V&V processes is the lack of repeatability and frequency of tests. To address this problem, while maintaining confidentiality, VSEC Test centralizes the testing process and execution while distributing the efforts across locations and resources. Managed remote access. Via a web interface, the VSEC Test platform allows users to register and connect hardware test benches or vehicles to the cloud, which are then shared and managed centrally under an enterprise account. Authorized users are able to schedule benches, access all available interfaces of the bench via a Linux terminal, and control multiple power sources to individual configured targets. User access is configured and controlled by the lab orchestration software to prevent unauthorized access. Features such as file explorer and workspace sharing can be enabled to allow quick ways to reproduce test environments; otherwise, each user has a sandbox environment in a Docker container to keep their workspace separated. In addition, VSEC Test also hosts a test management system that allows for continuous and repeated test setup with connected benches. Managed remote access. To evaluate the effectiveness and robustness of the VSEC Test platform, we set up a few bench and vehicle targets in the lab and connected various vehicle interfaces to a local machine that connects to VSEC Test on the cloud. We used built-in tests to remotely scan for basic information from a complete vehicle network, and compared the results with similar open-source tools installed directly to the local machine. Then we set up a custom test case on VSEC Test to be ran periodically on the remote target while purposely triggering some network downtime during test execution to simulate unplanned network disruptions, and compared the results to a local setup. We found that the added latency due to the cloud connection was not sufficient to cause a noticeable negative effect on the effectiveness of the test team. Test results obtained from the cloud platform are functionally equivalent to those achieved through a local setup. Moreover, the cloud platform provides the added benefit of facilitating instant sharing of results among team members and automating the report generation process, thereby eliminating the need for manual compilation of results from open-source tools. This paper is available on arxiv under CC BY 4.0 DEED. This paper is available on arxiv under CC BY 4.0 DEED. available on arxiv Authors:
(1) Sekar Kulandaivel, Robert Bosch LLC — Research and Technology Center;
(2) Wenjuan Lu, Block Harbor Cybersecurity;
(3) Brandon Barry, Block Harbor Cybersecurity;
(4) Jorge Guajardo, Robert Bosch LLC — Research and Technology Center. Authors: Authors: (1) Sekar Kulandaivel, Robert Bosch LLC — Research and Technology Center; (2) Wenjuan Lu, Block Harbor Cybersecurity; (3) Brandon Barry, Block Harbor Cybersecurity; (4) Jorge Guajardo, Robert Bosch LLC — Research and Technology Center.

The Vehicle Security Engineering Cloud Explained

Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2. Current Security Testing Platforms 2. Current Security Testing Platforms 2.1. Recent progress 2.1. Recent progress 3. A New Testing Platform and 3.1. Testing platform roles 3. A New Testing Platform and 3.1. Testing platform roles 3.2. Web-based remote access 3.2. Web-based remote access 3.3. Testbed setup 3.3. Testbed setup 4. Enabled Testing Methodologies 4.1. Secure Development Lifecycle (SDL) testing and 4.2. Penetration testing 4.1. Secure Development Lifecycle (SDL) testing and 4.2. Penetration testing 4.3. Research testing 4.3. Research testing 5. Conclusion & Outlook, and References 5. Conclusion & Outlook, and References 3. A New Testing Platform We present a flexible and configurable testing platform for automotive security by extending a cloud-based framework with additional components to support a number of testing methodologies. We focus on building a solution that is useful for many types of users, ranging from penetration testers to security researchers, and we aim to create a platform that bridges features in both software and hardware testing. We do not aim to cover all aspects of functional and safety testing, and we do not attempt to recreate a HIL system. We implement some of these testing methodologies and discuss practical benefits of our tests. 3.1. Testing Platform Roles We design this testing platform with a variety of users and roles in mind: Penetration testers: Users who need to test quickly and easily launch automated pentesting scripts, perform wireless tests while remote, access platforms without needing to ship hardware, connect a local device to a remote device (e.g., OEM dealership tool), and easily switch between different test beds from different contracts. Penetration testers: Researchers: Users who need to easily deploy and demonstrate novel security research on ECUs from multiple OEMs, copies of the same ECU for repeatability, and multiple model years while performing analysis with measurement tools (e.g., oscilloscopes, logic analyzers) and launching attacks from a custom ECU on the network. Researchers: Engineers: Users who needs managed access to the platform via scheduling, global remote access to test beds, quick reconfiguration of a prior project to handle new vulnerabilities, and a familiar user interface to interact with. Engineers: Lab technicians: A role that is responsible for setting up hardware in the lab, activating hardware-only features inperson, and moving probes for measurement tools if need. Lab technicians: This paper is available on arxiv under CC BY 4.0 DEED. This paper is available on arxiv under CC BY 4.0 DEED. available on arxiv Authors:
(1) Sekar Kulandaivel, Robert Bosch LLC — Research and Technology Center;
(2) Wenjuan Lu, Block Harbor Cybersecurity;
(3) Brandon Barry, Block Harbor Cybersecurity;
(4) Jorge Guajardo, Robert Bosch LLC — Research and Technology Center. Authors: Authors: (1) Sekar Kulandaivel, Robert Bosch LLC — Research and Technology Center; (2) Wenjuan Lu, Block Harbor Cybersecurity; (3) Brandon Barry, Block Harbor Cybersecurity; (4) Jorge Guajardo, Robert Bosch LLC — Research and Technology Center.

A New Testing Platform and Testing Platform Roles

Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2. Current Security Testing Platforms 2. Current Security Testing Platforms 2.1. Recent progress 2.1. Recent progress 3. A New Testing Platform and 3.1. Testing platform roles 3. A New Testing Platform and 3.1. Testing platform roles 3.2. Web-based remote access 3.2. Web-based remote access 3.3. Testbed setup 3.3. Testbed setup 4. Enabled Testing Methodologies 4.1. Secure Development Lifecycle (SDL) testing and 4.2. Penetration testing 4.1. Secure Development Lifecycle (SDL) testing and 4.2. Penetration testing 4.3. Research testing 4.3. Research testing 5. Conclusion & Outlook, and References 5. Conclusion & Outlook, and References 2.1. Recent progress Despite the challenges faced by the industry, we have seen considerable effort being made recently to address the shortcomings of cybersecurity testing. Table 1 compares our platform against several other modern testing platforms and highlights the key attributes that we offer and also explore in this paper. Testing hardware. Electronics test and measurement equipment and software manufacturer, Keysight Technologies, launched the SA8710A Automotive Cybersecurity Test Platform [8] a few years back with hardware that connects to all relevant interfaces on a modern vehicle and built-in security scanners and fuzzing tools. Built with its product line of connectivity and measurement instruments, the Keysight platform offers hardware that is capable of capturing small variations and disturbances in communication signals. Last year, we saw the launch of the BG Networks CRATE [13], an all-in-one hardware box capable of connecting to most of the vehicle interfaces, with options to expand using USB. The CRATE™ also offers some software tools to facilitate remote access and fuzz testing. Other traditional hardware test interface providers do not offer specific hardware for security testing, but they offer software plug-ins to support limited security testing [18]. Testing hardware. Testing frameworks. The Eclipse openDuT [4] framework focuses on automated and repeatable test and validation executions in the automotive space. This work is still in an incubating state and eventually aims to support a number of use cases, such as fully automated gray-box tests, tests across distributed test benches, and other functional tests. This framework provides end-to-end encryption of a private network between edge devices (ECUs, Restbus simulations, etc.) with an underlying control and registration logic. Ideally, network traffic from different devices under test can be linked together to create a more unified approach for testing. Additionally, CANlay offers virtual configurable networks where isolated ECUs can be bridged with sensor simulators for J1939 testing. A subset of ECUs here called overlays can be tested by carrying network traffic between these isolated ECUs. Testing frameworks. The ideal solution. In contrast to prior work, we aim to build a platform that is easy to use by many users without deep hardware knowledge and preferably provide remote access to enable global teams to work on the same project at the same time. The platform should be capable of offering multiple test beds and, if required, the test bed should be configurable so that only a subset of ECUs can be operated on-demand. This hardware should be located in a central location with staff on site that specialize in hardware to support remote users that access the system. It should also be easy for a remote test engineer to launch their own custom security tests using remotely-programmable hardware and measurement tools. The ideal solution. This paper is available on arxiv under CC BY 4.0 DEED. This paper is available on arxiv under CC BY 4.0 DEED. available on arxiv Authors:
(1) Sekar Kulandaivel, Robert Bosch LLC — Research and Technology Center;
(2) Wenjuan Lu, Block Harbor Cybersecurity;
(3) Brandon Barry, Block Harbor Cybersecurity;
(4) Jorge Guajardo, Robert Bosch LLC — Research and Technology Center. Authors: Authors: (1) Sekar Kulandaivel, Robert Bosch LLC — Research and Technology Center; (2) Wenjuan Lu, Block Harbor Cybersecurity; (3) Brandon Barry, Block Harbor Cybersecurity; (4) Jorge Guajardo, Robert Bosch LLC — Research and Technology Center.

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