Browse Topic: Cybersecurity

Items (603)
Software-defined vehicles are those whose functionalities and features are primarily governed by software, thus allowing continuous updates, upgrades, and the introduction of new capabilities throughout their lifecycle. This shift from hardware-centric to software-driven architectures is a major transformation that reshapes not only product development and operational strategies but also business models in the automotive industry. An SDV operating system provides the base platform to manage vehicle software and enable those advanced functionalities. Unlike traditional embedded or general-purpose operating systems, it is designed to meet the particular demands of modern automotive architectures. Reliability, safety, and security become crucial because even minor faults may have serious consequences. Key challenges to be handled by the SDV OS include how to handle software bugs, perform real-time processing, address functional safety and SOTIF compliance, adhere to regulations, minimize
Khan, Misbah UllahGupta, Vishal
As the automotive industry transitions toward software-defined vehicles and highly connected ecosystems, cybersecurity is becoming a foundational design requirement. A challenge arises with the advent of quantum computing, which threatens the security of widely deployed cryptographic standards such as RSA and ECC. This paper addresses the need for quantum-resilient security architectures in the automotive domain by introducing a combined approach that leverages Post-Quantum Cryptography (PQC) and crypto-agility. Unlike conventional static cryptographic systems, our approach enables seamless integration and substitution of cryptographic algorithms as standards evolve. Central to this work is the role of Hardware Security Modules (HSMs), which provide secure, tamper-resistant environments for cryptographic operations within vehicles. We present how HSMs can evolve into crypto-agile, quantum-safe platforms capable of supporting both hybrid (RSA/ECC + PQC) and fully post-quantum
Kuntegowda, Jyothi
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
M, ArvindPraneetha, Appana DurgaRemalli, Ravi Teja
Computer vision has evolved from a supportive driver-assistance tool into a core technology for intelligent, non-intrusive occupant health monitoring in modern vehicles. Leveraging deep learning, edge optimization, and adaptive image processing, this work presents a dual-module Driver Health and Wellness Monitoring System that simultaneously performs fatigue detection and emotional wellbeing assessment using existing in-cabin RGB cameras without requiring additional sensors or intrusive wearables. The fatigue module employs MediaPipe-based facial and skeletal landmark analysis to track Eye Aspect Ratio (EAR), Mouth Aspect Ratio (MAR), head posture, and gaze dynamics, detecting early drowsiness and postural deviations. Adaptive, driver-specific thresholds combined with CAN-bus data fusion minimize false positives, achieving over 92% detection accuracy even under variable lighting and demographics. The emotional wellbeing module analyzes micro-expressions and facial action units to
Iqbal, ShoaibImteyaz, Shahma
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
Kurumbudel, Prashanth Ram
State Transport Units (STUs) are increasingly using electric buses (EVs) as a result of India's quick shift to sustainable mobility. Although there are many operational and environmental benefits to this development, like lower fuel prices, fewer greenhouse gas emissions, and quieter urban transportation, there are also serious cybersecurity dangers. The attack surface for potential cyber threats is expanded by the integration of connected technologies, such as cloud-based fleet management, real-time monitoring, and vehicle telematics. Although these systems make fleet operations smarter and more efficient, they are intrinsically susceptible to remote manipulation, data breaches, and unwanted access. This study looks on cybersecurity flaws unique to connected passenger electric vehicles (EVs) that run on India's public transit system. Electric vehicle supply equipment (EVSE), telematics control units (TCUs), over-the-air (OTA) update systems, and in-car networks (such as the Controller
Mokhare, Devendra Ashok
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
More, ShwetaKulkarni, ShraddhaKumar, PriyanshuGhanwat, HemantJoshi, Vivek
With the emergence of Software-Defined Vehicles (SDVs), more complex software and connectivity technologies are introduced to support new advanced use cases such as phone as a key, smart parking and vehicle management. However, complex software functionality and external connectivity also increase the attack surface of vehicles and its ecosystem. In this paper, we first perform a classification of recent automotive cybersecurity attacks. We further perform an analysis of these attacks and associated vulnerabilities considering the application of best practices of vulnerability management approaches including Common Vulnerability Scoring System (CVSS), Exploit Prediction Scoring System (EPSS), and Stakeholder-Specific Vulnerability Categorization (SSVC). CVSS is a standardized framework used to assign severity scores to known vulnerabilities and helps organizations prioritize vulnerability remediation based on severity. EPSS is a predictive model that estimates the probability of a
Oka, Dennis KengoVadamalu, Raja Sangili
The modern vehicle is no longer a mechanical appliance—it has transformed into a software-defined cyber-physical system, integrating OTA updates, cloud-connected diagnostics, V2X services, and telematics-driven personalization. While this evolution promises unprecedented value in consumer experience and fleet operations, it also surfaces a dramatically expanded and evolving attack perimeter, especially across safety-critical ECUs and communication buses. Cyber vulnerabilities have shifted from isolated IT threats to real-time, embedded exploits. Controller area network (CAN), the backbone of vehicle bus systems, remains intrinsically insecure due to its lack of authentication and encryption, making it highly susceptible to message injection and denial-of-service by low-cost tools. Similarly, OEM implementations of BLE-based passive entry systems have proven vulnerable to replay and spoofing attacks with minimal hardware. In the Indian context, the transition to connected mobility is
Shah, RavindraAwasthi, Vibhu VaibhavKarle, Ujjwala
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:
Yadav, Sanjay KumarKumar, PrabhakarR, DineshJoon, SushantRai, AyushTripathi, Vinay Mani
The rapid expansion of electric vehicle (EV) charging infrastructure introduces complex cybersecurity challenges across hardware, software, network, and cloud layers. This review paper synthesizes existing research, standards, and documented incidents to identify critical vulnerabilities and propose layered mitigation strategies. We present a structured threat taxonomy based on the STRIDE model, enriched with real-world attack vectors and mapped to mitigation controls. Our analysis spans physical tampering, insecure firmware updates, protocol-level flaws in OCPP and ISO 15118, and cloud misconfigurations. While prior studies often focus on isolated domains, this work unifies fragmented insights into a cohesive framework. We highlight gaps in current literature, such as inconsistent adoption of secure protocols and limited validation of EVSE identity formats. By aligning threats with industry standards (SAE J3061, NIST CSF, IEC 62443) and scoring risks using CVSS v3.1, we offer a
Aggarwal, AkshitGupta, SaurabhSirohi, KapilArisetty, VenkateshChatterjee, Avik
The escalating dependence of Autonomous Vehicles on Intelligent Transportation Systems (ITS) has highlighted the imperative for comprehensive security protocols to safeguard such vehicles against cyber threats. Intrusion Detection Systems (IDS’s) are pivotal in ensuring the protection of these systems by detecting and alleviating unauthorized access and nefarious activities. The German Traffic Sign Recognition Benchmark (GTSRB) database, which encompasses an extensive compilation of traffic sign imagery, functions as a vital asset for the advancement of machine learning-based IDS. This research elucidates an intrusion detection system (IDS) that employs machine learning algorithms to scrutinize the GTSRB database. The proposed IDS emphasize the preprocessing of the GTSRB dataset to extricate pertinent features that can be employed for the training of machine learning models. Research also focuses on model development with machine learning algorithms to classify traffic signs and
Patil, KamaleshAkbar Badusha, A.Jadhav, SavitriGunale, Kishanprasad
This paper explores the implementation of ISO 21434 Automotive Cybersecurity Assurance Levels (CAL), focusing on enhancing component level cybersecurity for a vehicle. CAL values, which range from 1 to 4, provide a metric for ensuring that assets are protected against relevant threats at various phases of the product life cycle. By identifying parameters in the attack feasibility rating and their severity early in the product life cycle, specifically during the concept phase of ISO 21434, organizations can determine the CAL values. The CAL value serves as a benchmark to determine the level of severity required during the design, development and verification phases of the product life cycle. This paper outlines a method to establish CAL values as per ISO 21434 guidelines. The proposed methodology includes a detailed analysis of threat modeling, which is crucial for identifying and mitigating potential cybersecurity risks. By conducting threat modeling, organizations can systematically
Ghosh, SubhamKhader Batcha, Jashic
Threat Analysis and Risk Assessment (TARA) is a continuous activity, acting as a foundation of cybersecurity analysis for electrical and electronics automotive products. Existing TARA methodologies in the automotive domain exhibits challenges due to redundant and manual processes, particularly in handling recurring common assets across Electronic Control Units (ECUs) and functional domains. Two primary approaches observed for performing TARA are Manual-Asset-Centric TARA and Catalogue-Driven TARA. Manual-Asset Centric TARA is constructed from scratch by manually identifying the assets, calculating risks by likelihood, and impact determination. Catalogue-Driven TARA utilizes the precompiled likelihood and impact against identified assets. Both approaches lack standardized and modular mechanisms for abstraction and reuse. This results in poor scalability, increased efforts, and difficulty in maintaining consistency across vehicle platforms. The proposed method in this research overcomes
Goyal, YogendraSinha, SwatiSutar, SwapnilJaisingh, Sanjay
The proliferation of wireless charging technology in electric vehicles (EVs) introduces novel cybersecurity challenges that require comprehensive threat analysis and resilient design strategies. This paper presents a proactive framework for assessing and mitigating cybersecurity risks in wireless charger Electronic Control Units (ECUs), addressing the unique vulnerabilities inherent in electromagnetic power transfer systems. Through systematic threat modeling, vulnerability assessment, and the development of defense-in-depth strategies, this research establishes design principles for creating robust wireless charging ecosystems resistant to cyber threats. The proposed framework integrates hardware security modules, encrypted communication protocols, and adaptive threat detection mechanisms to ensure operational integrity while maintaining charging efficiency. Experimental validation demonstrates the effectiveness of the proposed security measures in preventing unauthorized access, data
Uthaman, SreekumarMulay, Abhijit BGadekar, Pundlik
The exponential growth of connected and autonomous vehicles has significantly escalated cybersecurity threats, compelling automotive Original Equipment Manufacturers (OEMs) to adopt robust and structured Cybersecurity Incident Response (CSIR) capabilities. Current automotive cybersecurity regulations, such as AIS 189 in India and UNECE WP.29 globally, mandate precise frameworks for proactive threat detection, timely response, and comprehensive incident documentation. This research presents an innovative, comprehensive CSIR framework specifically tailored to integrate seamlessly into OEM cybersecurity management processes. Leveraging a combination of real-time monitoring systems, structured threat categorization methodologies, and integrated escalation and communication protocols, the proposed CSIR framework ensures efficient incident handling aligned with stringent regulatory compliance. The framework encompasses advanced methodologies including Vehicle Security Operations Center (VSOC
Chaudhary lng, VikashDesai, ManojChatterjee, AvikChatterjee lng, Avik
With the increasing complexity and connectivity in modern vehicles, cybersecurity has become an indispensable technology. In the era of Software-Defined Vehicles (SDVs) and Ethernet-based architectures, robust authentication between Electronic Control Units (ECUs) is critical to establish a trust. Further, the cloud connected ECUs must perform authentication with backend servers. These authentication requirements often demand multiple certificates to be provisioned within a vehicle, ensuring secure communication between various combinations of ECUs. As a result, a single ECU may end up storing multiple certificates, each serving a specific purpose. This work proposes a method to limit the number of certificates required in a given ECU without compromising security. We introduce a Cross-Intermediate Certificate Authority (Cross-ICA) Trust Architecture, which enables the use of a single certificate per ECU for inter-ECU communication as well as backend server authentication. In this
Venugopal, VaisakhGoyal, YogendraRaja J, SolomonRai, AjayRath, Sowjanya
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
Shukla, SiddharthChatterjee lng, Avik
Modern vehicles use a network of Electronic Control Units (ECUs) that transmit over thousands of signals. The production of these ECUs is fraught with cybersecurity challenges that can lead to significant vulnerabilities, which pose risks not only to the suppliers but also to Original Equipment Manufacturers (OEMs) and end users. The automotive industry increasingly relies on sophisticated electronic systems but there is a lack of standardized approach to ensure implementation of robust cybersecurity measures during ECU production. It is imperative to establish effective safeguards against potential threats to ensure vehicle and passenger safety. This paper proposes a comprehensive approach to enhancing cybersecurity in ECU production. Key measures include the activation of cybersecurity protections in production units, secure flashing at plant and memory upload process, effective plant password generation, and securing the debug interface to prevent unauthorized access. By
Kulanthaisamy, NagarajanM S, TejaswiniSankar, Ganesh
In recent years many automotive cybersecurity relevant regulations have been released and some have already started to come into effect. Moreover, some other regulations will come into effect in the next few years. These regulations provide requirements and guidance to automotive organizations with different degree of specifics. In this paper, we review a number of different cybersecurity relevant regulations such as UNR 155, UNR 156, AIS 189, AIS 190, GB 44495, GB 44496, EU Cyber Resilience Act, and BIS Final Rule. We break down and categorize these regulations based on their scope and highlight key areas relevant to different teams within the organizations. These key areas include Cybersecurity Management System (CSMS), Software Update Management System (SUMS), secure software development and software supply chain security, continuous cybersecurity activities (monitoring, incident response), and vulnerability disclosure and management. We then map responsibilities from the
Oka, Dennis KengoVadamalu, Raja Sangili
The increasing adoption of electric vehicles (EVs) has raised the importance of secure communication between EVs and Electric Vehicle Supply Equipment (EVSE). As EV infrastructure rapidly evolves, cybersecurity threats targeting the vehicle-charger interface pose major risks to user safety, data integrity, and operational continuity. This paper presents an overview of existing EV-EVSE communication standards and explores their associated vulnerabilities. We identify potential cyber threats, including man-in-the-middle attacks, replay attacks, and protocol spoofing, that could compromise the security of EV charging systems. The study proposes an enhanced cybersecurity framework incorporating session authentication, and anomaly detection techniques to fortify EV-EVSE communication. The proposed mitigation strategies aim to ensure secure, reliable, and resilient charging infrastructure essential for the widespread adoption of electric mobility.
Uthaman, SreekumarPatil, Urmila
Effective communication is the key for bringing harmony - be it the communication between humans and humans, or communication between machine and machine. Today’s car is a sophisticated gadget, equipped with the best of technologies running using millions of lines of codes of software. The effective use of these technologies involve communication between car to car and car to infrastructure using Dedicated Short-Range Communication (DSRC), C-V2X (Cellular Vehicle-to-Everything). It is pertinent that any communication using the internet needs to be digitally secure and that the systems are designed to mitigate the perceived threats. The methods used for ensuring cyber safety of automobiles need to be verified before the end product is put to use. Automotive Industry Standards AIS-189 and AIS-190 have been formulated to provide a harmonized verification framework. Both the vehicle manufacturer and the test agency need to equip themselves with necessary skills and tools to ensure
Nayak, PratikTandon, VikramBadusha, AkbarDesai, ManojSathianesan, Rejin
As vehicles transform into complex cyber-physical systems within Intelligent Transportation Systems (ITS), automotive cybersecurity has become a foundational pillar in securing safe, reliable, and trustworthy transportation. This paper examines cybersecurity challenges in connected and autonomous vehicles (CAVs), focusing on Vehicle-to-Everything (V2X) communications technologies, including Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Pedestrian (V2P), and critical systems like electronic control units (ECUs), battery management units (BMUs), and sensor fusion modules. Key vulnerabilities, such as remote hacking, denial-of-service (DoS) attacks, malware injection, and data breaches, threaten vehicle functionality, passenger safety, and privacy. Key protection mechanisms, including encryption, intrusion detection systems (IDS), cryptographic protocols, secure over-the-air (OTA) updates, and Advanced Artificial Intelligence (AI) and Machine Learning (ML
Kumar, OmKumar, RajivSankar M, GopiHaregaonkar, Rushikesh Sambhaji
The rapid adoption of connected vehicle technologies and advanced driver assistance systems (ADAS) necessitates robust security mechanisms capable of identifying and mitigating sophisticated cyber threats in real-time. Traditional signature-based intrusion detection systems (IDS) are often inadequate in addressing the dynamic and evolving nature of automotive cybersecurity threats, particularly in modern vehicle networks like Controller Area Network (CAN), CAN with Flexible Data-Rate (CAN-FD), and Automotive Ethernet. This research introduces a novel Real-time Intrusion Detection System utilizing advanced Machine Learning (ML) techniques designed specifically for automotive network environments. The proposed IDS framework employs supervised and unsupervised ML algorithms, including anomaly detection, behavioral analytics, and predictive threat modeling, to achieve high accuracy and rapid threat identification capabilities. Through extensive testing in simulated and actual vehicle
Chaudhary lng, VikashDesai, ManojChatterjee, Avik
This paper presents a comprehensive technical review of the Software-Defined Vehicle (SDV), a paradigm that is fundamentally reshaping the automotive industry. We analyze the architectural evolution from distributed Electronic Control Units (ECUs) to centralized zonal compute platforms, examining the critical role of Service-Oriented Architectures (SOA), the AUTOSAR standard, and virtualization technologies in enabling this shift. A comparative analysis of leading High-Performance Computing (HPC) platforms, including NVIDIA DRIVE, Tesla FSD, and Qualcomm Snapdragon Ride, is conducted to evaluate the silicon foundation of the SDV. The paper further investigates key enabling technologies such as Over- the-Air (OTA) updates, Digital Twins, and the integration of Artificial Intelligence (AI) for applications ranging from predictive maintenance to software-defined battery management. We scrutinize the competing V2X communication standards (DSRC vs. C-V2X) and address the paramount
Ahmad, AqueelHemanth, KhimavathKumar, OmKumar, RajivHaregaonkar, Rushikesh Sambhaji
The proliferation of connectivity features (V2X, OTA updates, diagnostics) in modern two-wheelers significantly expands the attack surface, demanding robust security measures. However, the anticipated arrival of quantum computers threatens to break widely deployed publickey cryptography (RSA, ECC), rendering current security protocols obsolete. This paper addresses the critical need for quantum-resistant security in the automotive domain, specifically focusing on the unique challenges of two-wheeler embedded systems. This work presents an original analytical and experimental evaluation of implementing selected Post-Quantum Cryptography (PQC) algorithms, primarily focusing on NIST PQC standardization candidates (e.g., lattice-based KEMs/signatures like Kyber/Dilithium), on microcontroller platforms representative of those used in two-wheeler Electronic Control Units (ECUs) - typically ARM Cortex-M series devices characterized by limited computational power, memory (RAM/ROM), and strict
Mishra, Abhigyan
ISO/SAE 21434 emphasizes comprehensive cybersecurity risk management throughout the automotive lifecycle. However, specific guidance on validating cybersecurity measures at the production level remains limited. This paper addresses the gap in production-stage validation, particularly after End-of-Line (EOL) flashing, which includes configurations of security hardware and software protection (e.g., hardware register configuration, Debug and P-flash password settings etc.) Current automotive cybersecurity validation methods, despite adherence to ISO/SAE 21434, lack specific procedures for the production stage. The existing system-level validation using the ASPICE V-model (e.g., SWE.6, SYS.5) does not ensure the integrity and functionality of cybersecurity features in the final manufactured unit post-EOL flashing. This gap poses a risk of vulnerabilities being introduced during the EOL process, compromising critical security measures. To mitigate the cybersecurity risks in production
Chakraborty, SuchetaKulanthaisamy, NagarajanSankar, Ganesh
Modern cars have advanced significantly with the rapid growth of connectivity and communication technologies. In the wake of rising cyber attacks and enforcement of regulations, implementation of cybersecurity is imperative to safeguard vehicles. The cybersecurity controls such as secure boot, secure updates, and secure communication require cryptographic primitives (keys/certificates). These security features are largely dependent on robust Key Management System (KMS), as keys are the sensitive assets that must be protected throughout the lifecycle of vehicle. Several security critical applications like over-the-air and car-to-car interaction essentially needs robust KMS to protect the vehicle assets from expanding attack vectors. Traditionally KMS is established centrally in a backend server. The cloud based KMS is becoming complex due to increased number of keys/certificates required to provision in a vehicle. We propose a self-governing in-vehicle key management system for a
Goyal, YogendraSutar, SwapnilJaisingh, Sanjay
Automotive Product Development is a very complex process involving many functions across the organization along with the application of numerous technologies. Generally, most original equipment manufacturers follow a stage-gate process for any new product development. The increasing application of electrical and electronic systems, software and enhanced regulations focusing on overall safety of the eco-system further increases the complexity during development. This paper details the development and implementation of a comprehensive framework designed to enhance the quality and governance of the product development in the automotive industry. As the sector undergoes significant transformation, the need for structured development approach and robust oversight has become critical to success. The paper introduces a newly developed framework for Final Data Judgment (FDJ) and Engineering Sign-Off (ESO), representing a next-generation strategy towards defect free design, robust engineering
Digikar, AshishPathak, IshaKothari, Bhushan
Commercial vehicles form the backbone of global supply chains. In India, the commercial vehicle (CV) industry is at a transformative crossroads, evolving from traditional hardware-centric models to advanced, software-defined architectures. Central to this shift are Software-Defined Vehicles (SDVs) and Automotive Software-as-a-Service (SaaS), catalysing a move toward intelligent, connected, and highly productive mobility solutions. With the Indian CV market surpassing $50 billion in 2024 and witnessing robust growth due to expanding e-commerce, infrastructure projects and regulatory evolution. Indian original equipment manufacturers (OEMs) are spearheading this revolution. This paper presents a comprehensive analysis of the technological enablers, monetization strategies, distinct challenges and opportunities encountered by Indian OEMs during their shift toward SDVs and automotive SaaS based business models. This research also examines the most important technical pillars underpinning
Saini, GouravJahagirdar, ShwetaKhandekar, Dhiraj Baburao
This comprehensive research presents an in-depth analysis of communication protocols essential for implementing fast charging systems in India's rapidly expanding electric two-wheeler and three-wheeler market. As India witnesses unprecedented growth in electric mobility, with two-wheelers representing over 95% of current EV sales, the establishment of standardized, secure, and efficient charging protocols becomes paramount for widespread adoption. This study examines the current landscape of AC charging methodologies, evaluates the technical and economic feasibility of DC fast charging implementation, and provides detailed comparative analysis of existing international standards including IS 17017-25, IS 17017-31, ChaoJi, and CCS 2.0. The research concludes with strategic recommendations for developing cyber-secure, cost-effective charging infrastructure specifically tailored to meet India's unique market requirements and operational constraints.
Uthaman, SreekumarMulay, Abhijit B
As automotive electronic systems become increasingly complex, the demand for robust data security and privacy protection mechanisms has grown significantly. The AUTOSAR (Automotive Open System Architecture) standard has emerged as a widely adopted framework in the automotive industry due to its strong support for interoperability, functional safety, and cybersecurity. Within the AUTOSAR Classic Platform (CP), the Crypto Stack Service as a core component that enables critical security functionalities such as encryption, decryption, digital signature verification, and key management. However, the deployment of the Crypto Stack across heterogeneous Electronic Control Units (ECUs) introduces a series of technical challenges. These challenges stem primarily from variations in hardware resources, differences in operating system implementations, and inconsistencies in software execution environments. As a result, issues such as architectural compatibility, task scheduling efficiency, and
Wu, ShudiFan, SunjiaYu, YaqiXiu, Jiapeng
Burton, SimonChalmers, SethWishart, JeffreyZheng, Ling
This information report identifies and evaluates isolation building blocks applicable to TA sandboxing within a HPSE. These building blocks can be used to support SAE J3101 TA requirements for sandboxing of TAs and secure communication between TAs. TAs must execute within their own trust domain to prevent compromise of the HPSE and other TAs. TA trust domain isolation strength may vary depending on the risk profile of the TA deployed, hence the requirement for isolation building blocks to match the risk profile. A multitenancy TA HPSE has a higher risk profile than multiple TAs from the same source (e.g., OEM). TA multitenancy must not compromise the security properties of the HPSE (the secure integration and execution of trusted multi-vendor code). In this report, we provide information on the following: HPSE TA use cases and risk profiles HPSE TA isolation building blocks for manufacturers Threat analysis to determine the effectiveness of isolation security models As the ECU E/E
Vehicle Electrical System Security Committee
With the development of ship intelligence, network security threats are increasing day by day. This paper proposes a ship network security situation awareness algorithm based on an improved spatiotemporal attention mechanism, and constructs a supporting defense mechanism. The algorithm accurately captures changes in network security situation through dynamic weight allocation and multi-scale feature extraction. In the experimental simulation, OMNeT++ is combined with SUMO to build a ship network simulation environment, and Maritime - CPS - Dataset and other data sets are used for testing. The algorithm in this paper is compared with ARIMA, LSTM, GRU and other algorithms. The results show that in terms of situation awareness accuracy, the algorithm in this paper reaches 95.6%, which is 27.8% higher than ARIMA, 12.3% higher than LSTM, and 10.1% higher than GRU respectively; the average response time of the defense mechanism is shortened to 2.3 seconds, which is 40% faster than the
Kong, ZeyuZhou, BofeiWan, Shiyao
With the rapid development of Internet of Vehicles (IoV) and cyber-physical systems (CPS), connected autonomous vehicles (CAVs) have also developed rapidly. However, at the same time, in-vehicle networks also face more security challenges, mainly in terms of resource constraints, dynamic attacks, protocol heterogeneity, and high real-time requirements. Firstly, the trade-offs between lightweight encryption primitives and their software and hardware collaborative design in terms of performance, resource overhead, and security strength are analyzed. Secondly, the resource efficiency of AI-based intrusion detection system (IDS) is evaluated at the edge. Finally, we propose a dynamic adaptive collaborative defense framework (DACDF), which integrates federated learning with dynamic weight distillation, blockchain authentication with lightweight verifiable delay function (Light-VDF) and cross-domain IDS with hierarchical attention feature fusion to deal with collaborative attacks in resource
Zhou, YouZhang, JiguiDing, KaniYang, Guozhi
Amid escalating global warming challenges, the aviation industry must adopt low-carbon and green practices. China, aiming to meet its dual carbon goals, urgently requires enhanced research and development in sustainable aviation fuels (SAF), including their sustainability certification. However, China’s regulatory framework and limited research foundation in biofuels exacerbate this endeavor. This article summarizes the development status of SAF sustainability certification internationally and within China, encompassing the indicator framework, full life cycle greenhouse gas (GHG) calculation methodologies, and emission reduction thresholds. It also highlights issues encountered in the application of current international sustainability certification systems in China, such as high certification costs and inadequate data security. Advancement in domestic sustainability certification in China faces obstacles related to the incomplete foundational database, despite possessing life cycle
Zhang, ShupingHe, YinJia, QuanxingJia, QinTao, ZanMiao, JiaheShi, YaoZhang, XiangpingWang, Siyu
Manufacturers need pragmatic guidance when choosing network protocols that must balance responsiveness, high data throughput, and long-term maintainability. This paper presents a step-by-step, criteria-driven framework that scores protocols on six practical dimensions, real-time behavior, bandwidth, interoperability, security, IIoT readiness, and legacy support and demonstrates the approach on both greenfield and brownfield scenarios. By combining vendor specifications, peer-reviewed studies, and field experience, the framework delivers transparent, weighted rankings designed to help engineers make defensible deployment choices. This paper explores how network protocols can be mapped to different layers of the automation pyramid, ranging from field-level communication to enterprise-level. For example, Profinet is shown to be highly effective for time-critical applications such as robotic assembly and motion control due to its deterministic, real-time ethernet capabilities. Meanwhile
Tarapure, Prasad
The rapid evolution of autonomy in Off-Highway Vehicles (OHVs)—spanning agriculture, mining, and construction—demands robust cybersecurity strategies. Sensor-control systems, the cognitive core of autonomous OHVs, operate in harsh, connectivity-limited environments. This paper presents a structured approach to applying threat modeling to these architectures, ensuring secure-by-design systems that uphold safety, resilience, and operational integrity.
Kotal, Amit
In view of the complexity of railway engineering structure, the systematicness of professional collaboration and the high reliability of operation safety, this paper studied the spatial-temporal information data organization model with all elements in whole domain for Shuozhou-Huanghua Railway from the aspect of Shuozhou-Huanghua Railway spatial-temporal information security. Taking the unique spatial-temporal benchmark as the main line, the paper associated different spatial-temporal information to form an efficient organization model of Shuozhou-Huanghua Railway spatial-temporal information with all elements in the whole domain, so as to implement the effective organization of massive spatial-temporal information in various specialties and fields of Shuozhou-Huanghua Railway; By using GIS (Geographic Information System) visualization technology, spatial analysis technology and big data real-time dynamic rendering technology, it was realized the real-time dynamic visualization display
Liu, KunYu, HongshengZhu, PanfengLiu, WenbinWang, Yaoyao
The automotive industry's rapid shift towards electric and connected vehicles intensifies the demand for robust solutions addressing software integrity, cybersecurity, and stringent regulatory compliance, particularly concerning powertrain components and related control units. This paper addresses the significant challenge faced by automotive companies in efficiently managing and deploying an exponentially increasing number of software and hardware variants under the rigorous requirements of UNECE Regulation No. 156. This regulation mandates secure, traceable, and systematic software update processes for new vehicles and their components [1]. The proposed solution demonstrates a transformative approach that significantly reduces the software release cycle for Over-The-Air (OTA) updates which usually take 6 to 8 months to emerge [2]. By leveraging advanced techniques in automated compliance tracking, efficient parameter management, and centralized documentation, this approach bridges
Sammer, GeraldSchuch, NikolasKammerhofer, Markus
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