QoD: Ideas about Evaluating Quality of Datasets

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F20%3A00344910" target="_blank" >RIV/68407700:21240/20:00344910 - isvavai.cz</a>

Result on the web

<a href="https://pesw.fit.cvut.cz/2020/PESW_2020.pdf" target="_blank" >https://pesw.fit.cvut.cz/2020/PESW_2020.pdf</a>

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

QoD: Ideas about Evaluating Quality of Datasets

Original language description

Importance of computer networks is raising every year. The reason is that we are connecting more and more devices, applications and our daily routines depends on connectivity. On the other hand, this is a great potential for attackers. They can hide their activities in complex network environment and steal valuable data. Without solid dataset, our evaluation score is misinterpreting the real score in production environment, and, therefore, proper datasets have essential role in research&development of any ML-based classifier or detector. The main motivation for this paper is to find a way how to evaluate quality of any dataset to estimate if it is good enough for ML experiments. To our best knowledge, there are only a few studies focused on quality evaluation of datasets with network traffic. For experiments, we selected datasets about DNS over HTTP (DoH) detection and URL classification problems that are already being elaborated. All metrics are calculated from dataset level. Impact of these metrics is evaluated on Random Forest (RF) model. We show results we have discovered in our datasets and ML detection modules. Eventually, we discuss possible next steps in this research.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 8th Prague Embedded Systems Workshop

ISBN

978-80-01-06772-7

ISSN

—

e-ISSN

—

Number of pages

2

Pages from-to

8-9

Publisher name

České vysoké učení technické v Praze

Place of publication

Praha

Event location

Praha, virtual

Event date

Nov 6, 2020

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

—