Provably Secure and Practical Onion Routing.
Bibliographic record
Abstract
Abstract—The onion routing network Tor is undoubtedly the most widely employed technology for anonymous web access. Although the underlying onion routing (OR) protocol appears satisfactory, a comprehensive analysis of its security guarantees is still lacking. This has also resulted in a significant gap between research work on OR protocols and existing OR anonymity analyses. In this work, we address both issues with onion routing by defining a provably secure OR protocol, which is practical for deployment in the next generation Tor network. We start off by presenting a security definition (an ideal functionality) for the OR methodology in the universal composability (UC) framework. We then determine the exact security properties required for OR cryptographic primitives (onion construction and processing algorithms, and a key exchange protocol) to achieve a provably secure OR protocol. We show that the currently deployed onion algorithms with slightly strengthened integrity properties can be used in a provably secure OR construction. In the process, we identify the concept of predictably malleable symmetric encryptions, which might be of independent interest. On the other hand, we find the currently deployed key exchange protocol to be inefficient and difficult to analyze and instead show that a recent, significantly more efficient, key exchange protocol can be used in a provably secure OR construction. In addition, our definition greatly simplifies the process of analyzing OR anonymity metrics. We define and prove forward secrecy for the OR protocol, and realize our (whitebox) OR definition from an OR black-box model assumed in a recent anonymity analysis. This realization not only makes the analysis formally applicable to the OR protocol but also identifies the exact adversary and network assumptions made by the black box model. Keywords-onion routing; security proof; universal composability I.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".