This policy is based on the AI Use Policy of IEEE Security & Privacy 2026 and USENIX Security '26.
What constitutes the use of AI is constantly evolving in the research field. When using AI, and in their overall scientific process, authors are expected to engage with respect and integrity when submitting to VehicleSec: works submitted should constitute self-respecting work that upholds the author's scientific values and personal dignity, that respects the time and energy of reviewers, and respects the importance of scientific inquiry and integrity.
Authors must carefully consider their decision to use generative AI tools in their submission and appropriately disclose their use in a separate and well-marked section in the body of the paper (the section will count towards the page limit).
We also ask that authors adhere to three key criteria with regard to their use of generative AI tools in the scientific process:
- Originality: First, authors are responsible for the entire content of their paper, including all text and figures. While any tool may be used for writing, it is crucial that all content is accurate and original, ensuring transparency and maintaining the integrity of the research process. In particular, authors are responsible for the thoroughness of their literature review and must determine relevant prior work and cite it to ensure proper credit. If the authors have used AI tools to improve their writing, they should state: "Generative AI tools were used for editorial purposes in this manuscript, and all outputs were inspected by the authors to ensure accuracy and originality."
- Transparency: If generative AI tools are integral to the paper's methodology, their use should be explicitly detailed. Any idea generated by a generative AI tool should be independently developed and validated by the authors. Furthermore, authors must elaborate on how they handled limitations introduced in their work by their use of generative AI. Such limitations could, for instance, include difficulties in obtaining results that are reproducible when an LLM used is not open-sourced.
- Responsibility: Third, authors should take care to develop LLMs (and ML models in general) responsibly. Any data collection towards training models should take into account relevant ethical considerations such as consent and data holder rights, including intellectual property. Authors also have to justify the need for the environmental footprint of their experiments to achieve their goals and support their methodology. We recognize calculating such a footprint is a technical challenge in itself. We refer the authors to the work of Lacoste et al. We emphasize that the goal here is not to calculate the exact footprint but rather to explain experimental choices made as part of the scientific process (e.g., why was an AI tool necessary, why was a particular model size selected, how the authors minimized the volume of queries made, which hardware was used to run experiments).
The following uses are allowed:
- Use of generative AI tools for text-editing the paper
- Use of generative AI tools as part of a research methodology
- Use of generative AI tools to generate artifacts that are *verified* for correctness by the authors
What is NOT allowed:
- Wholesale generation of research and the paper from a generative AI technology
- Use of generative AI tools to generate artifacts or results (e.g., graphs, analysis results) that are *not verified* for correctness by authors.
- For example: authors should not simply give data to a generative AI technology and ask it to summarize or plot a graph without a strong verification methodology. Here, "verification" is subjective based on the opinion of reviewers.
- Examples of acceptable verification methodologies include:
- Manually verifying a script generated by a generative AI technology
- Manually verifying all data items classified by a generative AI technology
Authors are responsible for the accuracy and authenticity of their paper submissions, including content developed with the assistance of generative AI tools. Failure to comply with these rules is grounds for desk rejection without further review.
Authors should be prepared to answer these questions in the VehicleSec '26 submission portal:
- "I attest that the research team has read the ethics considerations in the VehicleSec Symposium Call for Papers, and adheres to the three key criteria described in the Use of Generative AI Policy."
- "I attest that the research team considered the ethics and the AI Use Policy of this research, that the authors believe the research was done ethically, and that the team's next-step plans (e.g., after publication) are ethical."