P2PIoT: A Peer-To-Peer Communication Model for the Internet of Things

Mendonça, Fábio Lúcio Lópes de; Cunha, Dayanne F. da; Praciano, Bruno J. G.; Zanatta, Mateus da Rosa; Costa, João Paulo; Sousa, Rafael T. de

doi:10.1109/wcnps.2019.8896313

Cited by 1 publication

(1 citation statement)

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“…However, P2P architecture supports emerging IoT applications such as proximity sharing, where colocated devices can cooperate with each other in real time to complete a task or share a resource. However, in this case, devices (peers) need to discover each other, trust each other, and then make a connection [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Managing Trust and Detecting Malicious Groups in Peer-to-Peer IoT Networks

Alhussain

Kurdi

Altoaimy

2021

Sensors

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Peer-to-peer (P2P) networking is becoming prevalent in Internet of Thing (IoT) platforms due to its low-cost low-latency advantages over cloud-based solutions. However, P2P networking suffers from several critical security flaws that expose devices to remote attacks, eavesdropping and credential theft due to malicious peers who actively work to compromise networks. Therefore, trust and reputation management systems are emerging to address this problem. However, most systems struggle to identify new smart models of malicious peers, especially those who cooperate together to harm other peers. This paper proposes an intelligent trust management system, namely, Trutect, to tackle this issue. Trutect exploits the power of neural networks to provide recommendations on the trustworthiness of each peer. The system identifies the specific model of an individual peer, whether good or malicious. The system also detects malicious collectives and their suspicious group members. The experimental results show that compared to rival trust management systems, Trutect raises the success rates of good peers at a significantly lower running time. It is also capable of accurately identifying the peer model.

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Section: Introductionmentioning

confidence: 99%