Trust-based Detection Strategy against Replication Attacks in
IoT

D 2021

Trust-based Detection Strategy against Replication Attacks in IoT

MBAREK, Bacem, Mouzhi GE and Tomáš PITNER

Basic information

Original name

Trust-based Detection Strategy against Replication Attacks in IoT

Authors

MBAREK, Bacem (788 Tunisia, belonging to the institution), Mouzhi GE (156 China) and Tomáš PITNER (203 Czech Republic, belonging to the institution)

Edition

Springer International Publi. Toronto, Canada, The 35th International Conference on Advanced Information Networking and Applications (AINA-2021), p. 646-656, 11 pp. 2021

Publisher

Springer

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10200 1.2 Computer and information sciences

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

Springer Link

RIV identification code

RIV/00216224:14330/21:00121148

Organization unit

Faculty of Informatics

ISBN

978-3-030-75074-9

ISSN

DOI

http://dx.doi.org/10.1007/978-3-030-75075-6_53

Keywords in English

6LoWPAN; Detection strategy; Internet of Things; Replication attack; Trust in IoT

Abstract

V originále

The integration of 6LoWPAN standard in the Internet of Things (IoT) has been emerging and applied in many domains such as smart transportation and healthcare. However, given the resource constrained nature of nodes in the IoT, 6LoWPAN is vulnerable to a variety of attacks, among others, replication attack can be launched to consume the node’s resources and degrade the network’s performance. This paper therefore proposes a trust-based detection strategy against replication attacks in IoT, where a number of replica nodes are intentionally inserted into the network to test the reliability and response of witness nodes. We further assess the feasibility of the proposed detection strategy and compare with other two strategies of brute-force and first visited with a thorough simulation, taking into account the detection probability for compromised attacks and the execution time of transactions. The simulation results show that the proposed trust-based strategy can significantly increase the detection probability to 90% on average against replication attacks, while within the number of nodes up to 1000 the detection runtime on average keeps around 60 s.

Links

CZ.02.1.01/0.0/0.0/16_019/0000822, interní kód MU
(CEP code: EF16_019/0000822)

Name: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur (Acronym: C4e)

Investor: Ministry of Education, Youth and Sports of the CR, CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence, Priority axis 1: Strengthening capacities for high-quality research

EF16_019/0000822, research and development project

Name: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur

Citovat

MBAREK, Bacem, Mouzhi GE and Tomáš PITNER. Trust-based Detection Strategy against Replication Attacks in IoT. Online. In Makoto Takizawa, Leonard Barolli, Donald Elmazi. The 35th International Conference on Advanced Information Networking and Applications (AINA-2021). Springer International Publi. Toronto, Canada: Springer, 2021, p. 646-656. ISBN 978-3-030-75074-9. Available from: https://dx.doi.org/10.1007/978-3-030-75075-6_53.

@inproceedings{1743539,
   author = {Mbarek, Bacem and Ge, Mouzhi and Pitner, Tomáš},
   address = {Toronto, Canada},
   booktitle = {The 35th International Conference on Advanced Information Networking and Applications (AINA-2021)},
   doi = {http://dx.doi.org/10.1007/978-3-030-75075-6_53},
   edition = {Springer International Publi},
   editor = {Makoto Takizawa, Leonard Barolli, Donald Elmazi},
   keywords = {6LoWPAN; Detection strategy; Internet of Things; Replication attack; Trust in IoT},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Toronto, Canada},
   isbn = {978-3-030-75074-9},
   pages = {646-656},
   publisher = {Springer},
   title = {Trust-based Detection Strategy against Replication Attacks in IoT},
   url = {https://link.springer.com/chapter/10.1007/978-3-030-75075-6_53},
   year = {2021}
}

TY  - JOUR
ID  - 1743539
AU  - Mbarek, Bacem - Ge, Mouzhi - Pitner, Tomáš
PY  - 2021
TI  - Trust-based Detection Strategy against Replication Attacks in IoT
PB  - Springer
CY  - Toronto, Canada
SN  - 9783030750749
KW  - 6LoWPAN
KW  - Detection strategy
KW  - Internet of Things
KW  - Replication attack
KW  - Trust in IoT
UR  - https://link.springer.com/chapter/10.1007/978-3-030-75075-6_53
N2  - The integration of 6LoWPAN standard in the Internet of Things (IoT) has been emerging and applied in many domains such as smart transportation and healthcare. However, given the resource constrained nature of nodes in the IoT, 6LoWPAN is vulnerable to a variety of attacks, among others, replication attack can be launched to consume the node’s resources and degrade the network’s performance. This paper therefore proposes a trust-based detection strategy against replication attacks in IoT, where a number of replica nodes are intentionally inserted into the network to test the reliability and response of witness nodes. We further assess the feasibility of the proposed detection strategy and compare with other two strategies of brute-force and first visited with a thorough simulation, taking into account the detection probability for compromised attacks and the execution time of transactions. The simulation results show that the proposed trust-based strategy can significantly increase the detection probability to 90% on average against replication attacks, while within the number of nodes up to 1000 the detection runtime on average keeps around 60 s.
ER  -

MBAREK, Bacem, Mouzhi GE and Tomáš PITNER. Trust-based Detection Strategy against Replication Attacks in IoT. Online. In Makoto Takizawa, Leonard Barolli, Donald Elmazi. \textit{The 35th International Conference on Advanced Information Networking and Applications (AINA-2021)}. Springer International Publi. Toronto, Canada: Springer, 2021, p.~646-656. ISBN~978-3-030-75074-9. Available from: https://dx.doi.org/10.1007/978-3-030-75075-6\_{}53.

Detailed Information on Publication Record