A comprehensive dataset from a smart grid testbed for machine learning based CPS security research

Chuadhry Mujeeb Ahmed, Nandha Kumar Kandasamy

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

Data-sets play a crucial role in advancing the research. However, getting access to real-world data becomes difficult when it comes to critical infrastructures and more so if that data is being acquired for security research. In this work, a comprehensive dataset from a real-world smart electric grid testbed is collected and shared with the research community. A few of the unique features of the dataset and testbed are highlighted.
Original languageEnglish
Title of host publicationCyber-Physical Security for Critical Infrastructures Protection - 1st International Workshop, CPS4CIP 2020, Revised Selected Papers
EditorsHabtamu Abie, Silvio Ranise, Luca Verderame, Enrico Cambiaso, Rita Ugarelli, Gabriele Giunta, Isabel Praça, Federica Battisti
Place of PublicationCham, Switzerland
PublisherSpringer
Pages123-135
Number of pages13
Volume12618
ISBN (Electronic)9783030697815
ISBN (Print)9783030697808
DOIs
Publication statusPublished - 18 Feb 2021
EventInternational Workshop on Cyber-Physical Security for Critical Infrastructures Provision - Virtual, Guildford, United Kingdom
Duration: 18 Sep 202018 Sep 2020
https://sites.google.com/fbk.eu/cps4cip20

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12618 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Workshop on Cyber-Physical Security for Critical Infrastructures Provision
Abbreviated titleCPS4CIP 2020
Country/TerritoryUnited Kingdom
CityGuildford
Period18/09/2018/09/20
Internet address

Keywords

  • data-sets
  • smart grid
  • testbed
  • machine learning
  • CPS
  • security research

Fingerprint

Dive into the research topics of 'A comprehensive dataset from a smart grid testbed for machine learning based CPS security research'. Together they form a unique fingerprint.

Cite this