# Trusted Energy-Aware Hierarchical Routing (TEAHR) for Wireless Sensor Networks
## 3 Proposed Studies
### Research Contribution
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Feature/** & **Probability** & **Weighted** & **Fuzzy Logic** & **Game** & **Directed** & **Undirected** & **TEAHR** \\
**Aspect** & **Trust Model** & **Trust Model** & **Trust Model** & **Trust Model** & **Trust Models** & **Trust Models** & **Trust Models** \\ \hline
**Inputs** & Previous trust values, successful interactions, and total & Metrics like packet forwarding ratio, data trustworthiness, energy levels, energy levels & Message success rate, success rate, elapsed time, correctness, fairness & The payoff, node actions, utility functions & Weights of edges in the directed graph & Weights of edges in the undirected graph & Energy, Consistency, Behavioral \\
**Handling of Uncertainty** & Incorporates & Handles & Fuzzy logic & & & & \\  & prior & uncertainty by adjusting & uncertainty by & under & & & \\  & probabilities to & adjusting & handling & uncertainty and & & & \\  & handle & weights & imprecise & evolves & trust relationships & & \\  & uncertainty & dynamically & input values & strategies over & & & \\  & & & levels & & & & \\  & & Best for & Ideal for & Effective in & Useful in & Applicable in & Dynamic \\
**Applicability** & Seenarios with & networks with & networks with & dynamic and & networks & & \\  & historical & where multiple & complex, & adversarial & where Trust is & & \\  & behavior data & trust metrics & multifaceted & environments & not reciprocal & Trust is & \\  & & are relevant & trust metrics & where strategies & or equal & required & \\  & & are relevant & trust metrics & evolve & & between nodes & \\
**Strengths** & Adjusts well to & Flexible and & Handles & Cooperative & Effective for & Provides a & High security, \\  & new data, & adaptable with & vague data & behavior, handles & directed trust & mutual Trust in & energy \\  & incorporates & various trust & inputs & & adversarial & relationships & networks & \\  & past behaviors & & effectively & nodes well & & & \\  & & Requires & & & & & It may not \\
**Weaknesses** & It can be computationally intensive, & careful & Complexity in & Requires & May not & & & \\  & selection of & defining fuzzy & sophisticated & handle & represent & & \\  & intensive, & weights; might & rules and & modeling; might & symmetric & & \\  & requires a lot of & be sensitive to & membership & be complex to & relationships & & \\  & historical data & metric & functions & implement & well & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._forwarded packets, packet loss rates, and transmission delays. Nodes that demonstrate consistency and trustworthiness in forwarding behavior are assigned higher trust scores, which make them more favorable for inclusion in routing paths. * Consistency Trust: The level of consistency in a node's behavior over time, particularly in relation to packet forwarding, is evaluated by consistency trust. This metric helps detect deviations that may signal potential malignancy or hardware failure. Inconsistencies in a node's behavior, such as sudden drops in forwarding success rates or erratic energy consumption, can indicate that the Node has been compromised or is experiencing technical issues. TEAHR can identify nodes that may pose a risk to the network and adjust routing decisions accordingly to maintain overall network stability. * Behavioral Trust: Behavioral Trust examines a node's adherence to network protocols and its past activity patterns to detect anomalies or potential security breaches. This metric is critical for identifying nodes that may be engaging in malicious activities, such as data tampering, unauthorized access, or collusion with other compromised nodes. Behavioral Trust is assessed by analyzing a node's interaction with other nodes, its response to protocol commands, and any deviations from expected behavior. Nodes that exhibit suspicious or non-compliant behavior are assigned lower trust scores and may be excluded from critical network functions.