Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 215

The DOI matches its Crossref record.

On cellular botnets: measuring the impact of malicious devices on a cellular network core

Traynor, Patrick, Lin, Michael, Ongtang, Machigar, Rao, Vikhyath, Jaeger, Trent, McDaniel, Patrick, La Porta, Thomas·2009·Proceedings of the 16th ACM conference on Computer and communications security

Abstract

The vast expansion of interconnectivity with the Internet and the rapid evolution of highly-capable but largely insecure mobile devices threatens cellular networks. In this paper, we characterize the impact of the large scale compromise and coordination of mobile phones in attacks against the core of these networks. Through a combination of measurement, simulation and analysis, we demonstrate the ability of a botnet composed of as few as 11,750 compromised mobile phones to degrade service to area-code sized regions by 93%. As such attacks are accomplished through the execution of network service requests and not a constant stream of phone calls, users are unlikely to be aware of their occurrence. We then investigate a number of significant network bottlenecks, their impact on the density of compromised nodes per base station and how they can be avoided. We conclude by discussing a number of countermeasures that may help to partially mitigate the threats posed by such attacks.

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 · 10.1145/1653662.1653690

Cites

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

Cited by

See all 215

Metadata

Authors
Traynor, P., Lin, M., Ongtang, M., Rao, V., Jaeger, T., McDaniel, P., & La Porta, T.
Venue
Proceedings of the 16th ACM conference on Computer and communications security
Publisher
ACM
Published
2009-11-09
Pages
223-234
ISSN
1543-7221 (ISSN-L)
OpenAlex
W2115026336
Cited by
215
References
0
FWCI
17.27
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: On cellular botnets: measuring the impact of malicious devices on a cellular network core. https://app.cochat.ai/papers/10.1145/1653662.1653690
The paper
Traynor, P., Lin, M., Ongtang, M., Rao, V., Jaeger, T., McDaniel, P., & La Porta, T. (2009). On cellular botnets: measuring the impact of malicious devices on a cellular network core. Proceedings of the 16th ACM conference on Computer and communications security. https://doi.org/10.1145/1653662.1653690

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.