Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 495

The DOI matches its Crossref record.

Constructing attack scenarios through correlation of intrusion alerts

Ning, Peng, Cui, Yun, Reeves, Douglas S.·2002·Proceedings of the 9th ACM conference on Computer and communications security

Abstract

Traditional intrusion detection systems (IDSs) focus on low-level attacks or anomalies, and raise alerts independently, though there may be logical connections between them. In situations where there are intensive attacks, not only will actual alerts be mixed with false alerts, but the amount of alerts will also become unmanageable. As a result, it is difficult for human users or intrusion response systems to understand the alerts and take appropriate actions. This paper presents a practical technique to address this issue. The proposed approach constructs attack scenarios by correlating alerts on the basis of prerequisites and consequences of attacks. Intuitively, the prerequisite of an attack is the necessary condition for the attack to be successful, while the consequence of an attack is the possible outcome of the attack. Based on the prerequisites and consequences of different types of attacks, our method correlates alerts by (partially) matching the consequences of some prior alerts with the prerequisites of some later ones. Moreover, to handle large collections of alerts, this paper presents three interactive analysis utilities aimed at reducing the complexity of the constructed attack scenarios without losing the structure of the attacks. This paper also reports the experiments conducted to validate the proposed techniques

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 · 10.1145/586110.586144

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 495

Metadata

Authors
Ning, P., Cui, Y., & Reeves, D. S.
Venue
Proceedings of the 9th ACM conference on Computer and communications security
Publisher
ACM
Published
2002-11-18
Pages
245-254
ISSN
1543-7221 (ISSN-L)
OpenAlex
W2141200504
Cited by
495
References
0
FWCI
13.72
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: Constructing attack scenarios through correlation of intrusion alerts. https://app.cochat.ai/papers/10.1145/586110.586144
The paper
Ning, P., Cui, Y., & Reeves, D. S. (2002). Constructing attack scenarios through correlation of intrusion alerts. Proceedings of the 9th ACM conference on Computer and communications security. https://doi.org/10.1145/586110.586144

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.