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REVIEW 2 major objections 7 minor 128 references

Collusion Resistant DNS With Private Information Retrieval

T0 review · 2 major / 7 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read PDNS lets DNS resolvers answer queries without learning the domain.

desk verdict A genuine PIR-based DNS prototype that solves cache population, but the privacy parity with DoHoT is overstated and the collapse of the ANS premise makes 'collusion resistant' conditional, not absolute. read the letter →

arxiv 2507.20806 v1 pith:TKZKP2XS submitted 2025-07-28 cs.NI cs.CR

Yunming Xiao , Peizhi Liu , Ruijie Yu , Chenkai Weng , Matteo Varvello , Aleksandar Kuzmanovic This is my paper · ORCID
classification cs.NIcs.CR
keywords DNSprivacyPrivateInformationRetrievalcollusionresistanceObliviousDoHrecursiveresolverhomomorphicencryptionEDNScaching
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper tries to establish that DNS privacy can be made collusion-resistant without removing recursive resolvers, by having resolvers answer queries blindly through single-server Private Information Retrieval. The proposed PDNS lets a recursive resolver compute PIR answers over its cache so it never learns which domain was queried, removing the non-collusion assumption that ODoH needs between proxy and resolver. To keep caches populated, a client that hits a cache miss performs the iterative lookup itself, and the final authoritative name server privately refills the resolver's cache via a new EDNS extension. The price is that a user's IP and domain are visible to the final authoritative server on cache misses, which the paper argues is acceptable because those servers already see the user's subsequent traffic and because caching limits misses to a small fraction of queries. If the argument holds, PDNS gives users today a practical, financially viable alternative to Tor-based DNS that is about twice as fast.

What carries the argument

The load-bearing mechanism is single-server stateless PIR, specifically the Spiral scheme, which lets a user fetch one slot of a pre-encoded database without revealing the index. PDNS wraps Spiral in a DNS workflow: a public hash maps each domain to one of $2^{15}$ slots of 16 KB in a 512 MB cache, the resolver encodes the whole cache once, and each query is answered homomorphically. On a cache miss, a new EDNS(0) option called EDNS-PR carries the resolver's IP address to the final authoritative name server, which then refills the resolver's cache with a randomly delayed response to blunt timing correlation. DNS records are reshaped for the scheme by replacing the domain name with a 16-byte hash and the TTL with an expiration timestamp, so expired entries can be resolved in a single direct hop to the authoritative server.

What would settle it

Inspect real PDNS cache-miss traces and check whether, for each miss, the authoritative server for the domain would independently observe HTTP(S) traffic from the same user IP to that domain within the record's TTL; if a large fraction of misses are never followed by such traffic, PDNS's parity-with-Tor privacy argument collapses.

Watch

Extended reading notes

Core claim

PDNS claims that a recursive resolver can resolve DNS queries while staying blind to the queried domain, using single-server stateless PIR (Spiral) over a fixed-size hash-table cache. On a cache hit, the user hashes the domain to an index, encrypts it, and the resolver homomorphically returns the whole matching slot, so the resolver learns neither the index nor the slot content. On a cache miss, the client performs the iterative lookup itself and the final authoritative name server sends the fresh record back to the resolver through an EDNS-PR extension, populating the cache without exposing the client's IP to the resolver. The paper argues this shifts privacy exposure from one central resolver (or resolver-proxy pair) to many authoritative servers, that this exposure is acceptable, and that caching keeps it small. In trace-driven experiments PDNS achieves median query times of 208 ms with a 64 MB cache, faster than ODoH's 272 ms and about twice as fast as DNS over Tor, at the cost of a resolver throughput of only 4-8 queries per second on an 8-core server.

Load-bearing premise

The paper assumes that when a user's query misses the resolver's cache, the final authoritative name server learning the user's IP and queried domain is not a new privacy loss because that server already sees the user's subsequent traffic to the domain.

Editorial extensions

If this is right

  • PDNS removes the need to trust a proxy not to collude with a resolver, the assumption that limits ODoH.
  • PDNS is about twice as fast as DoH over Tor with comparable privacy guarantees, and with a small cache it is faster than ODoH (208 ms versus 272 ms median).
  • Only cache misses expose queries to authoritative servers; in the paper's traces fewer than 10% of queries miss, and 90% of misses come from expired records that can be resolved directly at the final authoritative server.
  • With foreseen PIR hardware accelerators, answer time drops to a few milliseconds, making PDNS competitive with plain DoH while retaining collusion resistance.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the claim that final authoritative servers already see users' subsequent traffic fails for a large fraction of real users, PDNS's privacy guarantee would reduce to 'resolver learns nothing, final ANS learns query and IP on misses,' which is still stronger than DoH but not equivalent to Tor.
  • The cache-refill mechanism generalizes to other hierarchical systems with shared caches, such as certificate transparency logs or blockchain light clients, wherever a cache must be populated without revealing who asked for what.
  • A direct test of the paper's scalability projection would be to run Spiral's Answer primitive on an FHE accelerator and measure whether query resolution actually falls to the assumed few milliseconds on multi-GB caches.
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Signed reviews

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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

2 major / 7 minor

Summary. PDNS is a DNS privacy extension that integrates single-server PIR (Spiral) into the recursive resolver (ReR). A user hashes the queried domain to a cache slot, encrypts the slot index, and the ReR evaluates the PIR answer over an encoded cache without learning the domain; to populate the cache after a miss, the user performs the iterative lookup directly and the final authoritative name server (ANS) forwards the record to the ReR via the paper's EDNS-PR extension, with randomized delay to hinder timing correlation. The paper claims that PDNS removes the proxy non-collusion assumption that limits ODoH, achieves median query latencies of 208 ms (64 MB cache) versus 272 ms for ODoH, and is about 2x faster than DoH over Tor, with privacy guarantees 'similar' to DoHoT, at the cost of scalability (4-8 QPS per ReR). The contributions include a working prototype (Rust Spiral client/ReR, ~200-line BIND9 patch), trace-driven evaluation over 1,415 residential VPN nodes and 122K domains, a cache-miss proof mechanism to defend reflection attacks, and a deployment cost model.

Significance. If taken at face value, the ReR-blind query path is a meaningful advance: it removes the trusted proxy from the query path entirely, and the PIR construction rests on the published LWE-based security of Spiral rather than on fitted parameters; the cache shape, PIR choice, and throughput numbers are measured engineering decisions, and the paper reports the 4-8 QPS bottleneck and its cost model transparently. The paper also deserves credit for shipping an open-source prototype and for honestly disclosing its limitations (anycast, scalability, third-party final ANSes). The significance is nevertheless conditional: the headline parity with DoHoT and the 'Survive Non-Collusion Violation: Yes' entry in Table 1 hold only if exposing (user IP, full domain) to final ANSes on cache misses is privacy-neutral, a premise that Section 3.1 hedges with 'likely' and Section 9 partially retracts for Route 53-class deployments. As a system that distributes DNS exposure across many ANSes rather than concentrating it at one resolver, PDNS is a credible and useful contribution; as a no-trust-assumptions protocol it is not yet demonstrated.

major comments (2)
  1. [§3.1, §7.1, Table 1, abstract; §9 'Third-Party Final ANSes'] The load-bearing premise of the paper's central claim is stated in Section 3.1: a cache-miss query that reveals the full domain and the user IP to the final ANS 'does not leak any extra private information about a user than what the subsequent traffic directed to the domain' reveals, because 'ANSes are likely already gaining information about users from users' subsequent traffic [73].' This premise converts the design's inherent exposure of (IP, domain) to final ANSes into the abstract's 'similar privacy guarantees' to DoHoT and into the 'Survive Non-Collusion Violation: Yes' entry for single-server PIR in Table 1, and it is not established. First, the paper provides no evidence that the final ANS that serves a user's cache-miss query also observes that user's subsequent HTTP(S) traffic, and the claim is contradicted by the paper's own Section 9, which admits that for third-party ANS services such as Route 53, PDNS 'would leak some information to a third party which does not already have access to this information via direct traffic,' with the fix deferred to future work. Second, even if the ANS already knew the query, that does not make it known to the ReR: a single colluding ANS can transmit the (domain, user IP) pair to the ReR over the cache-population path (or simply omit the randomized delay), giving the ReR exactly the link the PIR query was designed to hide. The Section 3.1 restriction to 'realistic collusion... not among millions of ANSes' does not bound this threat, because one colluding ANS, or one multi-service operator such as Google or Cloudflare (discussed in Section 9), suffices. DoHoT, with which the paper claims parity, hides the user IP from the resolver entirely; PDNS does not. The abstract, Table 1, and Section 7.1 therefore overstate the guarantee: either the claims must be scoped to non-collusion between the ReR and the final ANS (which makes PDNS a different trade-off than advertised), or the PIR-at-the-ANS mechanism of Section 9 must be moved into the design rather than left as future work.
  2. [§4.2, §7.2, Appendix G] The timing-attack defense is load-bearing for the cache-miss path, because the ReR learns the domain when the ANS populates the cache, and the randomized delay is the only mechanism preventing the ReR from correlating that event with the user IP and query time it already observes. The Appendix G analysis supports a weaker conclusion than the Section 7.2 claim that PDNS 'effectively thwarts' timing attacks. For the uniform delay U(0, 2Δ) proposed in Section 4.2, Equation (2) yields entropy exactly at the threshold Te ≈ 0.69 nats, i.e., two equiprobable candidate queries, so the ReR can attribute a given population event to the correct user with 50% probability per miss. Over the paper's measured ~10% miss rate, with the ReR knowing the source IP and exact time of every PIR query, a 50%-accurate per-event signal is a substantial accumulation of user-to-query links rather than a thwarted attack. The model also assumes equally spaced queries made by different users (Figure 9), which is violated by the bursty traffic documented in Appendix F; under bursts, Δ shrinks and the candidate set for U(0, 2Δ) shrinks with it. The authors should report the per-event correlation success probability rather than a threshold-satisfying entropy, justify choosing the geometric distribution from Figure 10 for the actual design, and analyze the bursty regime.
minor comments (7)
  1. [§7.1] The sentence 'PDNS is slightly faster than DoH and ReR-Less DoH assuming a small cache, and no connection reuse' cannot be right as written, since PDNS is 208 ms and DoH is 69 ms; 'ODoH' was presumably the intended comparison, as ODoH is 272 ms without reuse.
  2. [Abstract, intro, §7.1] The '2x faster than DoH over Tor' claim should state which cache configuration it refers to: the introduction says the factor holds 'even on a large cache (512MB)', while Section 7.1 gives 208 ms (small cache) and 450 ms (large cache) and never reports the DoHoT median used for comparison; the two sections should be reconciled and the DoHoT baseline number reported.
  3. [Figure 2 caption, §6.2] The exponent notation is lost in '216 slots' (Figure 2 caption) and '215 slots with a size of 16KB' (Section 6.2); these should read 2^16 and 2^15, and the same check should be applied to '210', '220', and similar values elsewhere in Section 6.2.
  4. [References [1], [8]] Reference [8], labeled 'Google Cloud Pricing Calculator', points to the same AWS calculator URL as reference [1]; the Google Cloud link appears to be a copy-paste error and should be corrected.
  5. [Appendix G] The threshold Te ≈ 0.69 is evaluated with natural logarithms, but the base is never stated; because the numerical value of the entropy depends on the base, the analysis should state the base or report entropy in bits.
  6. [§7.2, Figure 4(c)] The 'preserving regional access pattern' analysis treats large absolute domain-popularity rank differences between PDNS and ground truth as a privacy benefit; rank perturbation is an observation about how the PIR slot-return distribution reshapes cache-visible statistics, not a demonstrated privacy guarantee, and the framing should be softened or argued more carefully.
  7. [Appendix E.1, §7.1] The DoHoT durations are collected from a single laboratory location, while PDNS numbers are obtained by injecting 1,415-node Mysterium latencies; the paper discloses this asymmetry, but the headline 2x comparison would be considerably more robust if both protocols were measured over the same client population.

Circularity Check

1 steps flagged · score 4.0 of 10

The 'Survive Non-Collusion Violation' property is self-definitional: §3.3 declares the final-ANS-to-ReR information transfer 'not a case of collusion,' so the Table 1 'Yes' holds by stipulation rather than by the PIR construction.

  1. self definitional [§3.3 Workflow, Cache update; see also §2.3 and Table 1]
    "As long as the final ANS does not “collude” with the ReR, the user’s privacy is maintained. This is not a violation of our privacy model as final ANSes have access to the user queries anyway (§ 3.1); instead, rather than being a case of collusion, it is merely a unidirectional information transfer from the final ANS to the ReR."

    The paper's headline property, 'Survive Non-Collusion Violation: Yes' (Table 1), is evaluated against a threat model in which only ReR–proxy collusion counts as collusion. In PDNS, every cache miss sends the user's IP and full query directly to the final ANS, and that ANS then forwards the response to the ReR. If the final ANS and ReR collude, or are the same operator (as the paper acknowledges for Google/Cloudflare in §9), the ReR learns the exact user–query link. The paper pre-empts this by stipulating that the transfer is 'not a case of collusion' because ANSes already have the query from subsequent traffic. The property is therefore satisfied by definition, not by the PIR construction.

full rationale

No other circular steps were found. The ReR's blindness rests on Spiral's published single-server PIR and standard LWE assumptions, not on any quantity fitted in this paper. Performance claims (208 ms and 450 ms median query times, 2x faster than DoHoT, QPS limits) come from the implemented prototype plus measured trace latencies; the F1-based 5 ms 'hardware accelerator' point is explicitly a simulation assumption, not a fitted parameter. The cache shape (2^15 slots of 16 KB) is selected from the benchmarks, and the timing-attack entropy analysis uses an explicit model with a stated threshold T_e. Self-citations ([121]–[123]) support methodology and prior systems, not the central privacy claim. The one definitional circularity is the collusion-resistance label discussed above: the paper makes 'collusion' exclude the final ANS, which is the very actor whose collusion with the ReR would defeat the claimed guarantee. That is a partial circularity in a central claim, while the rest of the derivation is self-contained and benchmarked against external baselines.

Assumptions & free parameters 4 free parameters · 6 assumptions · 0 invented entities

The central design rests on standard cryptographic assumptions (LWE) plus several domain assumptions: that ANSes already see equivalent user traffic, that ANS collusion is out of scope, that a minimum user population exists, and that ANSes will adopt DoH and EDNS-PR. The paper's free parameters are engineering choices made from its own benchmarks, not fitted constants disguised as predictions.

free parameters (4)
  • PDNS cache shape: N=2^15 slots, S=16KB = 2^15 slots x 16KB = 512MB
    Chosen in Section 6.2 to minimize measured Answer latency on a 512MB cache; affects all reported PDNS query times.
  • F1 hardware Answer time assumption = 5ms
    Assumed future FHE accelerator performance in Section 7.1; used to project 70ms PDNS query times.
  • Timing-attack delay distribution = U(0,2Δ) or G(1/Δ) with E[X]=Δ
    Assumed delay sampling in Section 4.2 and Appendix G; the defense effectiveness depends on this distribution choice.
  • Entropy threshold Te = 0.69
    Chosen in Appendix G as the equal-likelihood two-query bound; the defense's effectiveness conclusion depends on this threshold.
assumptions (6)
  • standard math LWE hardness and Spiral's FHE security hold.
    Spiral PIR security rests on standard lattice assumptions (Section 2.2, Appendix B).
  • domain assumption Final ANSes already see equivalent user information from subsequent traffic.
    Used in Sections 2.3 and 3.1 to justify the privacy trade-off of exposing cache-miss queries to ANSes.
  • domain assumption Malicious ANSes and ReR-ANS collusion are out of scope.
    Section 3.1 restricts collusion to a limited number of parties, such as a few ReRs and proxies, and treats ANSes as non-critical; this limits the collusion-resistance claim.
  • domain assumption At least a few PDNS users are active simultaneously.
    Section 2.3 states a single active user with a cache miss is identifiable via timing; privacy relies on user population.
  • domain assumption Participating ANSes will adopt DoH and EDNS-PR.
    Section 4.3 acknowledges no popular ANS supports DoT/DoH today; the design depends on this adoption.
  • domain assumption DNS query name minimization is used at non-final ANSes.
    Section 3.1 privacy analysis for non-final ANSes assumes QNAME minimization.

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Cite this review

Pith. "Pith review of Collusion Resistant DNS With Private Information Retrieval." pith.science (2026). https://pith.science/paper/TKZKP2XS

@misc{pith2026250720806,
  author       = {Pith},
  title        = {Pith review of: Collusion Resistant DNS With Private Information Retrieval},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/TKZKP2XS}},
  note         = {Machine review of arXiv:2507.20806}
}
read the original abstract

There has been a growing interest in Internet user privacy, demonstrated by the popularity of privacy-preserving products such as Telegram and Brave, and the widespread adoption of HTTPS. The Domain Name System (DNS) is a key component of Internet-based communication and its privacy has been neglected for years. Recently, DNS over HTTPS (DoH) has improved the situation by fixing the issue of in-path middleboxes. Further progress has been made with proxy-based solutions such as Oblivious DoH (ODoH), which separate a user's identity from their DNS queries. However, these solutions rely on non-collusion assumptions between DNS resolvers and proxies -- an assumption difficult to guarantee in practice. To address this, we explore integrating single-server Private Information Retrieval (PIR) into DNS to enable encrypted query processing without relying on trust assumptions. However, applying PIR to DNS is challenging due to its hierarchical nature -- particularly, interactions with recursive resolvers can still leak information. Navigating performance and privacy trade-offs, we propose PDNS, a DNS extension leveraging single-server PIR to strengthen privacy guarantees. We have implemented a prototype of PDNS and compared its performance against state-of-the-art solutions via trace-driven experiments. The results show that PDNS achieves acceptable performance (2x faster than DoH over Tor with similar privacy guarantees) and strong privacy guarantees today, mainly at the cost of its scalability, which specialized hardware for PIR can address in the near future.

Figures

Figures reproduced from arXiv: 2507.20806 by the authors.

Figure 1
Figure 1. Visualization of PDNS and its workflow. stateless PIR schemes. Assuming that the database size 𝑁 is known to both user and server. [C] is denoted as an encoding of C and is initially filled with zeros. The way a server encodes the database is specific to the PIR scheme. Define the following primitives for the user setup and database construction. • SetupUser(𝑁) → (qk, pk): Given as input the database size, the user … view at source ↗
Figure 2
Figure 2. PDNS cache as a hash table with 2 16 slots. valid. DNS records stored at the ReR also contain a timestamp of when the record was resolved. Each time a DNS query is matched in the cache, the ReR checks whether this record is expired. To allow the client to perform this operation, we replace the TTL field with a timestamp indicating when the record expires, i.e., timestamp at insertion plus TTL, as illustrated in [PI… view at source ↗
Figure 3
Figure 3. Benchmarking results for PDNS. Network latency is negligible. [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figures from the paper (7 more)
Figure 4
Figure 4. Figure 4: Evaluation of PDNS. contrast, our security mechanism reduces significantly and puts a deterministic cap on the reflection traffic. Given the space con￾straints, we leave the full result analysis in Appendix E.3. Preserving regional access pattern – In addition to the c…
Figure 5
Figure 5. Figure 5: ANS CPU usage as a function of the query rate. [PITH_FULL_IMAGE:figures/full_fig_p016_5.png]
Figure 6
Figure 6. Figure 6: Additional benchmarking results. (a) Initialization duration, (b) communication cost during initialization, and (c) [PITH_FULL_IMAGE:figures/full_fig_p017_6.png]
Figure 7
Figure 7. Figure 7: Memory and CPU as a function of cache size. [PITH_FULL_IMAGE:figures/full_fig_p017_7.png]
Figure 8
Figure 8. Figure 8: Analysis of active DNS measurements. guarantees cache hits as long as our queries happen within such an interval. The one-second interval guarantees a cache miss as long as we perform queries slower than once a second. While many public ReRs would ignore such low TTL v…
Figure 9
Figure 9. Figure 9: Illustration of the modeling for delayed response [PITH_FULL_IMAGE:figures/full_fig_p019_9.png]
Figure 10
Figure 10. Figure 10: The effectiveness of delayed response forwarding to PDNS ReR. [PITH_FULL_IMAGE:figures/full_fig_p020_10.png]

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Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.