Malmö University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
On the Analysis of Semantic Denial-of-Service Attacks Affecting Smart Living Devices
Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0003-0546-072X
Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-8512-2976
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).ORCID iD: 0000-0003-0326-0556
2020 (English)In: Intelligent Computing: Proceedings of the 2020 Computing Conference / [ed] Kohei Arai, Supriya Kapoor, Rahul Bhatia, Springer, 2020, Vol. 2Conference paper, Published paper (Refereed)
Abstract [en]

With the interconnectedness of heterogeneous IoT devices being deployed in smart living spaces, it is imperative to assure that connected devices are resilient against Denial-of-Service (DoS) attacks. DoS attacks may cause economic damage but may also jeopardize the life of individuals, e.g., in a smart home healthcare environment since there might be situations (e.g., heart attacks), when urgent and timely actions are crucial. To achieve a better understanding of the DoS attack scenario in the ever so private home environment, we conduct a vulnerability assessment of five commercial-off-the-shelf IoT devices: a gaming console, media player, lighting system, connected TV, and IP camera, that are typically found in a smart living space. This study was conducted using an automated vulnerability scanner – Open Vulnerability Assessment System (OpenVAS) – and focuses on semantic DoS attacks. The results of the conducted experiment indicate that the majority of the tested devices are prone to DoS attacks, in particular those caused by a failure to manage exceptional conditions, leading to a total compromise of their availability. To understand the root causes for successful attacks, we analyze the payload code, identify the weaknesses exploited, and propose some mitigations that can be adopted by smart living developers and consumers.

Place, publisher, year, edition, pages
Springer, 2020. Vol. 2
Series
Advances in Intelligent Systems and Computing book series (AISC), ISSN 2194-5357, E-ISSN 2194-5365 ; 1229
Keywords [en]
DoS, IoT, OpenVAS, Smart home, Security, vulnerabilities, risks
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:mau:diva-17692DOI: 10.1007/978-3-030-52246-9_32Scopus ID: 2-s2.0-85088500921ISBN: 978-3-030-52246-9 (electronic)ISBN: 978-3-030-52245-2 (print)OAI: oai:DiVA.org:mau-17692DiVA, id: diva2:1452877
Conference
Computing Conference 2020
Available from: 2020-07-08 Created: 2020-07-08 Last updated: 2024-02-05Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Bugeja, JosephJacobsson, AndreasSpalazzese, Romina

Search in DiVA

By author/editor
Bugeja, JosephJacobsson, AndreasSpalazzese, Romina
By organisation
Internet of Things and People (IOTAP)Department of Computer Science and Media Technology (DVMT)
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 137 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf