Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 432

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

ANODR: anonymous on demand routing with untraceable routes for mobile ad-hoc networks

Kong, Jiejun, Hong, Xiaoyan·2003·Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing

Abstract

In hostile environments, the enemy can launch traffic analysis against interceptable routing information embedded in routing messages and data packets. Allowing adversaries to trace network routes and infer the motion pattern of nodes at the end of those routes may pose a serious threat to covert operations. We propose ANODR, an anonymous on-demand routing protocol for mobile ad hoc networks deployed in hostile environments. We address two closely related problems: For route anonymity, ANODR prevents strong adversaries from tracing a packet flow back to its source or destination; for location privacy, ANODR ensures that adversaries cannot discover the real identities of local transmitters. The design of ANODR is based on "broadcast with trapdoor information", a novel network security concept which includes features of two existing network and security mechanisms, namely "broadcast" and "trapdoor information". We use simulations and implementation to validate the effectiveness of our design.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/778415.778449

Cites

26 of 26 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 26 references

Metadata

Authors
Kong, J., & Hong, X.
Venue
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
Publisher
ACM
Published
2003-06
Pages
291-302
OpenAlex
W2168812739
Cited by
432
References
26
FWCI
12.67
Type
conference paper
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: ANODR: anonymous on demand routing with untraceable routes for mobile ad-hoc networks. https://app.cochat.ai/papers/10.1145/778415.778449
The paper
Kong, J., & Hong, X. (2003). ANODR: anonymous on demand routing with untraceable routes for mobile ad-hoc networks. Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing. https://doi.org/10.1145/778415.778449

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.