Hardware and Software Constraints for Automotive Firewall Systems?
Bibliographic record
Abstract
Introduction The introduction of Ethernet and Gigabit Ethernet [2] as the main invehicle network infrastructure is the technical foundation for different new functionalities such as piloted driving, minimizing the CO2- footprint and others. The high data rate of such systems influences also the used microcontrollers due the fact that a big amount of data has to be transferred, encrypted, etc. Figure 1 Motivation - Vehicles will become connected to uncontrolled networks The usage of Ethernet as the in-vehicle-network enables the possibility that future road vehicles are going to be connected with other vehicles and information systems to improve system functionality. These previously closed automotive systems will be opened up for external access (see Figure 1). This can be Car2X connectivity or connection to personal devices. Allowing vehicle systems to communicate with other systems that are not within their physical boundaries impose a previously non-existing security problem. Any external communication with the vehicle system must be considered as a potential security threat, which may impact the system functionality or any of the safety properties. This may result in new vulnerabilities that could be exploited by malicious attackers [1, 3]. Any external access to the system must be authorized and firewalled, so that only trustworthy users and services can make use of the functionality. In order to achieve a high level of security a holistic security concept is highly essential. A holistic security concept is based on the following basic building block: Physical Security (tamper proof) Network Security Secure System Software (ECU Hardening) Application Hardening In order to archive a high level of confidence for the internal secure network communication a firewall concept is required. A holistic firewall approach includes firewalls in different ECU with different firewall functionalities. This paper addresses the hardware and software architecture patterns for building automotive firewall systems. In the first chapter state-of-the-art firewall concepts will be shortly presented and afterwards special automotive requirements will be introduced. In following chapters the basic requirements for a firewall system from the OEM point of view will be discussed. It is followed by having a closer look on the hardware aspects which come along with automotive requirements. The paper finishes with some software aspects about realizing firewalls.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".