Trust-based Detection Strategy against Replication Attacks in
IoT

D 2021

Trust-based Detection Strategy against Replication Attacks in IoT

MBAREK, Bacem, Mouzhi GE a Tomáš PITNER

Základní údaje

Originální název

Trust-based Detection Strategy against Replication Attacks in IoT

Autoři

MBAREK, Bacem (788 Tunisko, domácí), Mouzhi GE (156 Čína) a Tomáš PITNER (203 Česká republika, domácí)

Vydání

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

Nakladatel

Springer

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10200 1.2 Computer and information sciences

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Odkazy

Springer Link

Kód RIV

RIV/00216224:14330/21:00121148

Organizační jednotka

Fakulta informatiky

ISBN

978-3-030-75074-9

ISSN

DOI

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

Klíčová slova anglicky

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

Štítky

core_B, firank_B

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 23. 5. 2022 14:25, RNDr. Pavel Šmerk, Ph.D.

Anotace

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.

Návaznosti

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

Název: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur (Akronym: C4e)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur, PO 1 Posilování kapacit pro kvalitní výzkum

EF16_019/0000822, projekt VaV

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

Citovat

MBAREK, Bacem, Mouzhi GE a 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, s. 646-656. ISBN 978-3-030-75074-9. Dostupné z: 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 a 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, s.~646-656. ISBN~978-3-030-75074-9. Dostupné z: https://dx.doi.org/10.1007/978-3-030-75075-6\_{}53.

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