Citation: Al-Otaiby, N.; Alhindi, A.;
Kurdi, H. AntTrust: An Ant-Inspired
Trust Management System for
Peer-to-Peer Networks. Sensors 2022,
22, 533. https://doi.org/10.3390/
s22020533
Academic Editors: Alvaro
Araujo Pinto and Hacene Fouchal
Received: 23 November 2021
Accepted: 3 January 2022
Published: 11 January 2022
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Article
AntTrust: An Ant-Inspired Trust Management System for
Peer-to-Peer Networks
Nehal Al-Otaiby
1
, Afnan Alhindi
1
and Heba Kurdi
1,2,
*
1
Department of Computer Science, College of Computer and Information Sciences, King Saud University,
Riyadh 11451, Saudi Arabia; nfalotaiby@iau.edu.sa (N.A.-O.); aalhindi@ksu.edu.sa (A.A.)
2
Mechanical Engineering Department, Massachusetts Institute of Technology (MIT),
Cambridge, MA 02139, USA
* Correspondence: hkurdi@ksu.edu.sa
Abstract:
In P2P networks, self-organizing anonymous peers share different resources without a
central entity controlling their interactions. Peers can join and leave the network at any time, which
opens the door to malicious attacks that can damage the network. Therefore, trust management
systems that can ensure trustworthy interactions between peers are gaining prominence. This
paper proposes AntTrust, a trust management system inspired by the ant colony. Unlike other
ant-inspired algorithms, which usually adopt a problem-independent approach, AntTrust follows a
problem-dependent
(problem-specific) heuristic to find a trustworthy peer in a reasonable time. It
locates a trustworthy file provider based on four consecutive trust factors: current trust, recommen-
dation, feedback, and collective trust. Three rival trust management paradigms, namely, EigenTrust,
Trust Network Analysis with Subjective Logic (TNA-SL), and Trust Ant Colony System (TACS),
were tested to benchmark the performance of AntTrust. The experimental results demonstrate
that AntTrust is capable of providing a higher and more stable success rate at a low running time
regardless of the percentage of malicious peers in the network.
Keywords: peer-to-peer networks; trust management; wireless sensor networks; privacy
1. Introduction
Computer networks, especially newly emerging forms such as wireless sensor net-
works (WSNs) and Internet of Things (IoT), are susceptible to failure [
1
–
3
]. Network
failures can be attributed to a range of issues, of which security breaches are among the
most common and dangerous. This is because, in these networks, a central component
(e.g., gateway/router) is usually essential to the connection to the cloud or to the nearest
network, which makes them more vulnerable, as a compromised central component can re-
sult in cascading failures. Therefore, many new application domains adopt the peer-to-peer
(P2P) structure [
4
] or device-to-device cooperative (D2D) scheme [
5
], in which network
nodes interact directly with each other, eliminating the need for the central component.
A P2P network is an open and dynamic distributed system, where nodes can directly
communicate with each other without the need for a centralized server. In these networks,
services are provided by peers; however, peers are characterized by their anonymity and
freedom, so trust is essential to establishing communication among them [
6
]. Therefore,
it is important to build a trust management system to encourage resource sharing among
peers in such networks [7].
Many emerging studies have focused on trust management systems in P2P net-
works [
8
–
12
]. On the other hand, only a few studies have considered bioinspired ap-
proaches [
13
], although they might be of great benefit in such a context. Furthermore, to
the best of our knowledge, all of the proposed bioinspired trust management algorithms
are based on metaheuristics, also known as problem-independent heuristics, such as ant
colony optimization (ACO) and artificial bee colony (ABC), rather than problem-specific
Sensors 2022, 22, 533. https://doi.org/10.3390/s22020533 https://www.mdpi.com/journal/sensors
