## 2 Theoretical Foundation and Sybil Attack Landscape
### Sybil Detection Algorithms  
In WSNs, [PERSON] et al. [37] formulated a Sybil detection algorithm: message authentication with a Random Password Generation (RPG) algorithm to identify and neutralize Sybil attacks. RPG generates routing tables for network nodes, comparing node details during message transmission to identify unauthorized nodes. The Compareand Match-Position Verification Method (CAM-PVM) detects Sybil attacks. Data are rerouted through verified nodes, omitting known Sybil nodes. However, due to the high computational demands, [PERSON] et al. (2017) advocate prevention prioritization over detection. CAM-PVM is selectively employed when data-sending nodes suspect a recipient, ensuring efficiency. Regarding Sybil attack detection in mobile ad hoc networks (MANETs), [PERSON] et al. (2018) introduced a detection scheme for versatile MANETs, widely applied across various fields. MANETs self-organize into versatile typologies driven by application needs with wireless nodes that connect/disconnect dynamically based on bandwidth. However, such wireless connectivity reduces capacities compared to those of wired connections. Security is challenging due to autonomy and the absence of centralized authority, rendering MANETs vulnerable to diverse cyber threats. All nodes in MANETs function as hosts/routers, enhancing their configurations while compromising their security. While wireless connectivity boosts data transfer rates, latency is introduced due to constrained resources like battery-powered small units. Despite these complexities, the unique properties of MANETs have led to their diverse applications. [PERSON] et al. (2018) examined security threats in sensor networks. Due to the cost-efficiency requirement for mass production, sensor nodes often lack advanced hardware, computational power, and storage space, limitations that hinder the use of robust cryptography algorithms, leaving networks vulnerable to threats like Sybil attacks. For instance, in a weather prediction ad hoc network, a Sybil node could manipulate forecasts to predict extreme conditions, or, in a military application's MANET, a Sybil node breaching the network might endanger lives. [PERSON] et al. (2018) proposed the received Signal Strength (RSS)-based localization algorithm as a solution for Sybil attacks. An algorithm was leveraged by [PERSON] et al. (2018) for the identification of Sybil attacks within sensor networks. [PERSON] et al. recognized its key role as a promising strategy for detecting Sybil attacks in MANETs. They benchmarked it as a measure of the signal's strength received from a specific node at a given location. The RSS value varies depending on the signal's source node location. According to [PERSON] et al. (2018), one way to distinguish between Sybil and legitimate nodes is by analyzing the nodes' entry and exit behaviors within the network. RSS is the measurement of signal strength received by a receptor, typically gauged at the receiver's antenna. Several factors influence RSS, e.g., transmitter-receiver distance, transmission medium, and receiver signal power. RSS applications are crucial in detecting and estimating the geographical location of a transmitter. [PERSON] et al. (2018) examined network nodes as they joined and exited a network assessing proximity and signal strength to distinguish legitimate from Sybil nodes. When a newly Sybil node enters a network, it is expected to exhibit a high RSS. Conversely, legitimate nodes tend to join a network upon receiving a signal, which results in a lower RSS value during network entry. Such discrepancy arises from the fact that Sybil nodes are spawned by nodes already in the network. In contrast, legitimate nodes, drawn by proximity, promptly join the network with weaker signals, leaning toward a lower RSS value. The detection mechanism involves storing communication histories between neighboring nodes in individual nodes such that each node maintains a table that encompasses the entire communication history.