Flow-Based Compromise Detection: Lessons Learned

Rick Hofstede (Corresponding Author), Aiko Pras (Corresponding Author), Anna Sperotto, Gabi Dreo Rodosek

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)
1 Downloads (Pure)

Abstract

Although the aggregated nature of exported flow data provides many advantages in terms of privacy and scalability, flow data may contain artifacts that impair data analysis. In this article, we investigate the differences between flow data analysis in theory and practice — that is, in lab environments and production networks.
Original languageEnglish
Article number8283485
Pages (from-to)82-89
Number of pages8
JournalIEEE security & privacy
Volume16
Issue number1
Early online date6 Feb 2018
DOIs
Publication statusPublished - 16 Dec 2018

Fingerprint

Data flow analysis
compromise
Scalability
data analysis
privacy
artifact

Cite this

Hofstede, Rick ; Pras, Aiko ; Sperotto, Anna ; Dreo Rodosek, Gabi. / Flow-Based Compromise Detection : Lessons Learned. In: IEEE security & privacy. 2018 ; Vol. 16, No. 1. pp. 82-89.
@article{cf6bc4e4ad1e477cafce8c5b6e1204c4,
title = "Flow-Based Compromise Detection: Lessons Learned",
abstract = "Although the aggregated nature of exported flow data provides many advantages in terms of privacy and scalability, flow data may contain artifacts that impair data analysis. In this article, we investigate the differences between flow data analysis in theory and practice — that is, in lab environments and production networks.",
author = "Rick Hofstede and Aiko Pras and Anna Sperotto and {Dreo Rodosek}, Gabi",
year = "2018",
month = "12",
day = "16",
doi = "10.1109/MSP.2018.1331021",
language = "English",
volume = "16",
pages = "82--89",
journal = "IEEE security & privacy",
issn = "1540-7993",
publisher = "IEEE",
number = "1",

}

Flow-Based Compromise Detection : Lessons Learned. / Hofstede, Rick (Corresponding Author); Pras, Aiko (Corresponding Author); Sperotto, Anna ; Dreo Rodosek, Gabi.

In: IEEE security & privacy, Vol. 16, No. 1, 8283485, 16.12.2018, p. 82-89.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Flow-Based Compromise Detection

T2 - Lessons Learned

AU - Hofstede, Rick

AU - Pras, Aiko

AU - Sperotto, Anna

AU - Dreo Rodosek, Gabi

PY - 2018/12/16

Y1 - 2018/12/16

N2 - Although the aggregated nature of exported flow data provides many advantages in terms of privacy and scalability, flow data may contain artifacts that impair data analysis. In this article, we investigate the differences between flow data analysis in theory and practice — that is, in lab environments and production networks.

AB - Although the aggregated nature of exported flow data provides many advantages in terms of privacy and scalability, flow data may contain artifacts that impair data analysis. In this article, we investigate the differences between flow data analysis in theory and practice — that is, in lab environments and production networks.

U2 - 10.1109/MSP.2018.1331021

DO - 10.1109/MSP.2018.1331021

M3 - Article

VL - 16

SP - 82

EP - 89

JO - IEEE security & privacy

JF - IEEE security & privacy

SN - 1540-7993

IS - 1

M1 - 8283485

ER -