Browse Topic: Cybersecurity
The useability of development processes in the automotive sector has decreased in the past years to a level at which their application and true benefit to is being questioned. Such degradation can be attributed to new additions to the processes and introduction of FuSa and Cybersecurity standards. The processes try to keep up with the shift from the traditional ‘plan–implement–test–roll-out' methodology to more agile methods. In addition, process departments typically in charge of these processes, focus on compliance to the letter of the standard to achieve certification, often with little thought to the actual implementation and the process they will be used by their engineering teams. Process growth to meet the needs of new and more complex technologies often mandates the use of new tools, which if implemented incorrectly can lead to unnecessary bureaucracy and additional overheads. Furthermore, the language of these new processes is in a form from assessor, making it difficult for
The automotive industry is evolving from a reactive, independently self-determined approach to cybersecurity, complicated by a complex supply chain. Over time, this has resulted in a fragmented industry comprised of any number of proprietary solutions verses a standardized, regulated paradigm to facilitate a platform-oriented approach. This document, an update on collaborative work from the SAE Vehicle Electrical Hardware Security Task Force (TEVEES18B) and GlobalPlatform Automotive Task Force, outlines this transition strategy. An extensible number of additional examples of use cases of Global Platform Technologies are explored in this document.
Modern vehicles require sophisticated, secure communication systems to handle the growing complexity of automotive technology. As in-vehicle networks become more integrated with external wireless services, they face increasing cybersecurity vulnerabilities. This paper introduces a specialized Proxy based security architecture designed specifically for Internet Protocol (IP) based communication within vehicles. The framework utilizes proxy servers as security gatekeepers that mediate data exchanges between Electronic Control Units (ECUs) and outside networks. At its foundation, this architecture implements comprehensive traffic management capabilities including filtering, validation, and encryption to ensure only legitimate data traverses the vehicle's internal systems. By embedding proxies within the automotive middleware layer, the framework enables advanced protective measures such as intrusion detection systems, granular access controls, and protected over-the-air (OTA) update
Automotive Over-the-Air (OTA) software updating has become a cornerstone of the modern connected vehicle, enabling manufacturers to remotely deploy bug fixes, security patches, and new features. However, this convenience comes with significant cybersecurity challenges. This paper provides a detailed examination of automotive OTA update security and the software store (software Applications & services store) mechanisms. I discuss the current industry standards and regulations, notably ISO/SAE 21434 and the United Nations Economic Commission for Europe (UNECE) regulations UN R155 (cybersecurity) and UN R156 (software updates) and explain their relevance to secure OTA and software update management. I then explored the Uptane framework, an open and widely adopted architecture specifically designed to secure automotive OTA updates. Next, OTA-specific threat models are analyzed, detailing potential attack vectors and corresponding mitigation strategies. Real-world case studies are presented
The integration of Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) has transformed various industries, offering substantial benefits. The application of these technologies in engine reliability testing has immense potential as they offer real-time monitoring and analysis of engine performance parameters. Engine reliability testing is vital for ensuring the safety, efficiency, and longevity of engines. Traditional methods are time consuming, expensive, and rely heavily on manual inspection and data analysis. This paper shows how IoT and ML technologies can enhance the efficiency of engine reliability testing. The paper includes the following case studies:
With the rapid advancement of connected vehicle technologies, infotainment Electronic Control Units (ECUs) have become central to user interaction and connectivity within modern vehicles. However, this enhanced functionality has introduced new vulnerabilities to cyberattacks. This paper explores the application of Artificial Intelligence (AI) in enhancing the cybersecurity framework of infotainment ECUs. The study introduces AI-powered modules for threat detection and response, presents an integrated architecture, and validates performance through simulation using MATLAB, CANoe, and NS-3. This approach addresses real-time intrusion detection, anomaly analysis, and voice command security. Key benefits include zero-day exploit resistance, scalability, and continuous protection via OTA updates. The paper references real-world automotive cyberattack cases such as OTA vulnerability patches, Connected Drive exploits, and Uconnect hack, emphasizing the critical need for AI-enabled proactive
With the increasing connectivity of modern vehicles, cybersecurity threats have become a critical concern. Intrusion Detection Systems (IDS) play a vital role in securing in-vehicle networks and embedded vehicle computers from malicious attacks. This presentation shares about an IDS framework designed specifically for POSIX-based operating systems used in vehicle computers, leveraging system-level monitoring, anomaly detection, and signature-based methods to identify potential security breaches. The proposed IDS integrates lightweight behavioral analysis to ensure minimal computational overhead while effectively detecting unauthorized access, privilege escalation, communication interface monitoring etc. By employing a combination of rule-based and OS datapoints, the system enhances threat detection accuracy without compromising real-time performance. Practical series deployments demonstrate the effectiveness of this approach in mitigating cyber threats in automotive environments
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