Venue: ICLR 2023 TinyPapers

Reviews:

final_score: rating: High Potential (HP): a submission which meets the reviewing criteria and has potential to make an impact on the field
review_content: summary_of_contributions: The authors propose utilizing a distributed deep learning framework to investigate transferability of network intrusion detection between federated nodes. Their preliminary studies investigate the impact of feature pre-processing to improve transferability.
strengths_and_weaknesses: Strengths:
- Interesting idea of potentially high impact.

Weaknesses:
- No real description regarding the preprocessing steps is provided.
- Are there any reasons why the temporal averaging seems to be “best” in some sense? Does the differential inputs step really help with attack 1? Remains slightly unclear.

suggested_changes: - Make sure citations read correctly, i.e., show up in brackets as opposed to regular inline text.
- Provide more information about the preprocessing steps and how they help specifically (maybe in the appendices?).
- Eventually the authors are encouraged to compare against standard methods in the literature to see how their method compares with others.
- Would be nice to have a sense for how much added computation the two suggested preprocessing steps introduce.
- Furthermore, does using a distributed DL system introduce new problems compared to other more conventional techniques?
review_title: null

Decision: Invite to present