Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 319

The DOI matches its Crossref record.

Web application security assessment by fault injection and behavior monitoring

Huang, Yao-Wen, Huang, Shih-Kun, Lin, Tsung-Po, Tsai, Chung-Hung·2003·Proceedings of the twelfth international conference on World Wide Web - WWW '03

Abstract

As a large and complex application platform, the World Wide Web is capable of delivering a broad range of sophisticated applications. However, many Web applications go through rapid development phases with extremely short turnaround time, making it difficult to eliminate vulnerabilities. Here we analyze the design of Web application security assessment mechanisms in order to identify poor coding practices that render Web applications vulnerable to attacks such as SQL injection and cross-site scripting. We describe the use of a number of software-testing techniques (including dynamic analysis, black-box testing, fault injection, and behavior monitoring), and suggest mechanisms for applying these techniques to Web applications. Real-world situations are used to test a tool we named the Web Application Vulnerability and Error Scanner (WAVES, an open-source project available at http://waves.sourceforge.net) and to compare it with other tools. Our results show that WAVES is a feasible platform for assessing Web application security.

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 · 10.1145/775152.775174

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 319

Metadata

Authors
Huang, Y.-W., Huang, S.-K., Lin, T.-P., & Tsai, C.-H.
Venue
Proceedings of the twelfth international conference on World Wide Web - WWW '03
Publisher
ACM Press
Published
2003
Pages
148
OpenAlex
W2003115932
Cited by
319
References
0
Type
conference abstract
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: Web application security assessment by fault injection and behavior monitoring. https://app.cochat.ai/papers/10.1145/775152.775174
The paper
Huang, Y.-W., Huang, S.-K., Lin, T.-P., & Tsai, C.-H. (2003). Web application security assessment by fault injection and behavior monitoring. Proceedings of the twelfth international conference on World Wide Web - WWW '03. https://doi.org/10.1145/775152.775174

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.