Trust Computations and Trust Dynamics in Mobile Adhoc Networks: A Survey

Abstract

Trust is an important aspect of mobile adhoc networks (MANETs). It enables entities to cope with uncertainty and uncontrollability caused by the free will of others. Trust computations and management are highly challenging issues in MANETs due to computational complexity constraints, and the independent movement of component nodes. This prevents the direct application of techniques suited for other networks. In MANETs, an untrustworthy node can wreak considerable damage and adversely affect the quality and reliability of data. Therefore, analyzing the trust level of a node has a positive influence on the confidence with which an entity conducts transactions with that node. In this work we present a detailed survey on various trust computing approaches that are geared towards MANETs. We highlight the summary and comparisons of these approaches. In addition, we analyze various works on trust dynamics including trust propagation, prediction and aggregation algorithms, the influence of network dynamics on trust dynamics and the impact of trust on security services.

A Reliable Trustworthy Approach Based on Node Behavior Prediction for Secure Routing in MANET

“…Previous work on trust restoration, are discussed in [5,17,18,20,21], which suggested that node restoration cannot be an important measure for node trust recovery, where nodes are discarded based on low dependency trust because it mostly measures the past behavior for trust calculation. Negative behavior nodes are isolated due to low trust and new untrusted nodes cannot join the network, so no new behavior is observed and the scope of node recovery is limited [16,21].…”

“…It describes the malicious behavior of a node depends on the number of packets forwarded for on receiving from the neighboring nodes. The source node computes the trust value with the support of direct detection of any data packet modification made by the intermediate node in the route [18]. The indirect approach considering trust observation made based on the messages transmitted by neighboring or ranges nodes to update positive or negative behavior of the node.…”

DTM²: Adapting job market signaling for distributed trust management in vehicular ad hoc networks

“…There are many solutions proposed in literature dealing with trust models for mobile ad-hoc networks as presented in the survey [8]. These solutions cope either with malicious nodes or selfish ones, but rarely with both of them at the same time.…”

Secure Trust Metadata Management for Mobile Ad-Hoc Networks

“…Trust metadata created by a node could include several components, namely, the category of misbehavior (e.g., jamming, packet dropping, etc. ), the observation region (i.e., the region of the MANET in which misbehavior was observed), the interval (i.e., the time interval in which misbehavior was observed), the evaluated node identifier (i.e., the identifier of the misbehaving node), the creating node identifier (i.e., the identifier of the node that created the trust metadata), the trust score (e.g., a value between -1 and 1, where -1 denotes the least level of trust, 0 is neutral and 1 denotes the highest level of trust) [11,12], the evidence (i.e., data to support the trust score, that could include the identifiers of a set of other witness nodes) and a digital signature (computed by the creating node over all the other components for authenticity and integrity). The category, observation region, interval, evaluated node identifier and creating node identifier are the components of trust metadata based on which the TA constructs its queries.…”

“…A trust management framework could be subjected to other types of security attacks [2,15,12]. For example, bad mouthing attack, in which dishonest recommendations are provided by nodes, on-off attack, in which nodes behave well and badly alternatively, conflicting behavior attack, in which nodes behave differently with different peer nodes, sybil attack, in which several fake identifiers are created by a node and newcomer attack, in which a node registers itself as a new user.…”