China Smart Car Information Security (Cybersecurity And Data Security) Research Report 2025: AI Fusion Intelligent Protection And Ecological Collaboration Ensure Cybersecurity And Data Security

(MENAFN- GlobeNewsWire - Nasdaq) Key market opportunities in automotive information security include AI integration, enhancing cybersecurity via DevSecOps, and post-quantum cryptography deployment. The shift towards full lifecycle security design, driven by stringent regulations, highlights the growth potential in AI-driven threat responses and quantum-resistant solutions.

Dublin, Sept. 25, 2025 (GLOBE NEWSWIRE) -- The "Smart Car Information Security (Cybersecurity and Data Security) Research Report, 2025" report has been added to ResearchAndMarkets's offering.
Research on Automotive Information Security: AI Fusion Intelligent Protection and Ecological Collaboration Ensure Cybersecurity and Data Security

At present, what are the security risks faced by intelligent connected vehicles? Automotive information security covers two aspects: cybersecurity and data security. Cybersecurity measures and data security technologies are embedded in the information security framework to form multi-layer protection.

Intelligent connected vehicles have become integrated mobile smart terminals. The EEAs continue to evolve, but automotive information security attacks are increasing, including autonomous driving safety attacks (sensor failure and deception, software vulnerabilities and network attacks, decision algorithm defects, data privacy and security), vehicle-road-cloud integrated network attacks (Internet of Vehicles platform attacks, roadside infrastructure tools, satellite Internet attacks), and attacks on charging networks (new energy vehicle battery system attacks, charging station network attacks).

The trend of flattening the supply chain requires ecological collaboration and protection, and the shortened SDV iteration cycle increases the pressure of security testing

Software-defined vehicles (SDV) separate software and hardware. OEMs are currently adopting an iterative R&D model to shorten the new function release cycle to 3-6 months, so that the pressure of automotive software security testing is prominent. Faced with the threat of cybersecurity and data security, OEMs are increasingly integrating security practices into all phases of the vehicle lifecycle development within their agile DevOps for development and operation. They are gradually embracing the integrated development of DevSecOps.

With the trend of flattening the supply chain, OEMs now have to face more suppliers, and it is difficult for them to obtain device source code, and there is a lack of efficient firmware security testing tools. In view of this, OEMs are gradually increasing vulnerability management efforts and continuously strengthening software supply chain security efforts. Effective response measures include software bill of materials (SBOM) management, software composition analysis (SCA), code review, SAST, IAST, DAST, fuzz testing and other technologies.

The application of AI in the field of automotive information security is evolving from single-point defense to intelligence and systematization

AI is reshaping the paradigm of automotive information security, shifting from passive protection to a closed loop of `prediction-defense-response`. The application of AI in the field of automotive information security is evolving from single-point defense to intelligence and systematization. The main trends are reflected in two aspects: technology application and industrial ecology. The technology application trends include the following:

Cloud-edge-vehicle linkage: For example, NavInfo and Alibaba Cloud jointly build an intelligent cloud base to support the closed loop of autonomous driving R&D data and security strategy collaboration.

The application of post-quantum cryptography technology in the automotive industry has moved from technical accumulation to industrialization

The application of post-quantum cryptography technology in the automotive industry has moved from technical accumulation to industrialization under the impetus of both quantum threats and intelligent cybersecurity demand. In the short term, chip performance and standard unification should be handled. In the long term, a full-stack protection system of `algorithm-chip-communication-cloud platform` will be formed. OEMs should give priority to the layout of hybrid encryption, automotive chip certification and V2X security upgrades to cope with quantum security challenges in the next 10 years. The post-quantum cryptography migration strategy of the US NIST clearly states that for important infrastructure and business systems, the existing PKI algorithms will be replaced in 2028-2030.

Traditional asymmetric encryption algorithms like RSA and ECC are indeed vulnerable to attacks from quantum computers using algorithms like Shor's. This means that, if powerful quantum computers become a reality, public key cryptography systems relying on these algorithms for vehicle-to-cloud communication, OTA updates, and identity authentication could be compromised. The life cycle of a car is as long as 10-15 years, and quantum computers may break through in the next 10 years, so post-quantum protection should be deployed in advance.

Stricter policies and regulations force OEMs to make safety design in advance, shifting from `after-the-fact remediation` to `full life cycle safety design`

Since the release of the `Data Security Law` in 2021, national ministries and commissions have issued a total of 39 policies and regulations related to data security in the automotive industry (such as `Several Provisions on Automotive Data Security Management (Trial)`, `Guidelines for Detecting Important Data in Connected Vehicles and Autonomous Driving`, GB/T 41871-2022 `Information Security Technology - Security Requirements for Automotive Data Processing`, GB/T 44464-2024 `General Requirements for Automotive Data`, GB/T `Intelligent Connected Vehicles - Data Security Management System Specifications` (under preparation)) and 7 standards, so that the industry's data security management system is becoming perfect.

At present, the data security challenges faced by OEMs include a wide variety of data types and diverse attacks, such as 0-day attacks, supply chain risks (OEMs share data with many partners and suppliers, so third-party risks become an important source of data leakage), and human factors (employees' weak security awareness and operational errors are also important causes of data leakage). Therefore, it is necessary to construct a data protection and governance system for the entire life cycle, and it is recommended to strengthen the construction in the following aspects (see the figure below).

Key Topics Covered:

1 Automotive Information Security

• Current Security Risks of Intelligent Connected Vehicles
• Security Issues Of Intelligent Vehicles
• Vehicle Attacks
• Classification of Internet of Vehicles Security Risks
• Summary of Major Global Intelligent Vehicle Cybersecurity Events
• Attack Classification
• Automotive Information Security Vulnerability Trends
• Authoritative Cybersecurity Vulnerability Platforms at Home and Abroad
• Vulnerability Rating Mechanism in the Automotive Industry
• Supply Chain Security
• Comparison of Software Component Detection Tools
• Software Bill of Materials (SBOM)
• Software Supply Chain Security
• Software Security and Compliance Scenarios in the Automotive Industry
• Recommendations for Automotive Information Security Compliance System
• Role of TARA in Automotive Cybersecurity
• Specific Application Examples of TARA in Automotive Cybersecurity
• Case of Foundation Model Reconstructing TARA Platform
• Security Products for WP29 R155/44495
• Protection Technology: IDPS & VSOC
• IDS/IDPS Architecture
• Core Capability of VSOC
• VSOC: Evolution to Collaboration with Agent
• IDPS & VSOC Solution Case
• Protection Technology: Penetration Testing & Fuzz Testing
• Penetration Testing Technology
• Fuzz Testing Technology
• Fuzz Testing of Key Components
• Fuzz Testing at the Vehicle-level/Development Stage
• Protection Technology: SAST, IAST & DAST
• SAST Technology
• SAST Solution Providers and Cooperation with OEMs
• IAST Technology
• IAST Solution Providers and Cooperation with OEMs
• DAST Technology
• DAST Solution Providers and Cooperation with OEMs
• DevSecOps
• Protection Technology: Post-quantum Cryptography
• SPHINCS+ Post-quantum Cryptographic Algorithm
• Application of PQC in the Automotive Field
• PQC Application Case in the Automotive Safety Field
• Cooperation Cases between Major PQC Suppliers and Automotive Customers
• Policies, Regulations and Standards
• Laws, Regulations and Standards Related To Information Security
• Three National Mandatory Standards
• Framework of GB 44495
• Impact of GB 44495 on OEMs

2 Automotive Data Security

• Data Security Regulations and Policies
• Legal Provisions of Automotive Data Security Management System
• Standardization of Automotive Data Security Management System
• Model Data Compliance Embedded in the Development Process
• National Standards/Industry Standards Related to Classification and Grading of Intelligent Connected Vehicle Data
• Data Security Challenges Faced by OEMs and Protection Response Suggestions
• Data Security Test Items
• Automotive Data Security Test: Personal Information Protection Test Method
• Automotive Data Security Test: Anonymization Test Method
• Autonomous Driving Data Desensitization: Key Technology for Protecting Privacy and Data Security
• Overview of OEMs and Models with Automotive Privacy Protection Logos
• Background of Cross-border Data Regulations and Policies
• Core Methods for OEMs to Let Data Cross Borders
• Implementation Paths and Core Measures for Cross-border Data
• Typical Model Cross-border Data Cases
• Automotive Cross-border Service Providers and Cooperative OEMs
• Agile Technology
• Eagle Cloud
• XDLP
• BJCA
• SafePloy
• Infosec Technologies

3 Information Security Practices of OEMs

• SERES
• Automotive Information Security System Construction
• Data Security Construction Steps and Effects
• Information Security Ecological Synergy Strategy and Effects
• Technology Integration and Innovation in Data Security Construction
• Security Protection Improvement through Intelligent Operation
• Automotive Information Security Cooperation Case
• Leapmotor
• Xpeng
• NIO
• Li Auto
• Xiaomi
• BYD
• Geely
• Dongfeng Motor
• BAIC
• FAW
• SAIC
• GAC
• JAC Group
• Chery
• Changan
• Great Wall Motor

4 Typical Automotive Information Security Hardware Companies

• UNI-SENTRY
• Thinktech
• NationalChip
• Shanghai Hangxin
• HSEC
• Fudan Microelectronics

5 Major Automotive Information Security Software Providers

• Software Security TechnologySourceGuard
• Seczone
• SECTREND
• Feysh Technology
• TICPSH
• Chiwu Technology

6 Typical Internet of Vehicles Information Security Solution Providers

• Vecentek
• GoGoByte
• Inchtek
• SECDEER
• SEC-ICV
• Yaxon Zhilian
• Qingtianxinan

7 Trends and Summary

• Summary of Automotive Information Security Chips
• Summary of Fuzz Testing Solutions
• Summary of SCA Tools/Platforms
• Summary of Source Code Security Tools/Platforms
• Summary of IDPS & VSOC Solutions
• Summary of Secure Communication Solutions/Platforms and Cooperative OEMs
• Summary of Internet of Vehicles Security Solutions and Cooperative OEMs
• Summary of Automotive Cybersecurity Solutions and Cooperative OEMs
• Summary of Automotive Data Security Solutions and Cooperative OEMs
• Trend 1: The application of Post-quantum cryptography technology in the automotive industry has moved from technical accumulation to industrialization
• Summary of Post-quantum Cryptography Products and Cooperative OEMs
• Trend 3: Application of AI in Automotive Information Security/Cooperation Cases
• Trend 4: Foundation Model Automotive Information Security Application/OEMs
• Application of Agents in Automotive Information Security/Cooperation Cases

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