# Towards Tamper-Proof Trust Evaluation of Internet of Things Nodes Leveraging IOTA Ledger
## 1 Introduction  
The Internet of Things (IoT) represents a transformative evolution in digital technology, characterized by the interconnection of a vast array of devices and systems, ranging from everyday household items to sophisticated industrial machinery [1]. This widespread integration has fueled major advances in sectors such as smart healthcare, intelligent transportation, energy optimization, and industrial automation [2]. These applications rely heavily on the seamless exchange of data and autonomous decision-making. However, as the number of connected devices continues to grow, ensuring that all participating nodes are reliable and secure becomes a foundational concern [3]. The presence of malicious and compromised nodes in the network can lead to security breaches, data corruption, and system malfunctions, which poses severe risks to individuals and organizations [4]. Therefore, robust mechanisms for trust evaluation within IoT networks are essential to maintaining the integrity, security, and reliability of these interconnected systems [5]. Evaluating the trustworthiness of network nodes in IoT is paramount to safeguarding the network's overall integrity and functionality [6]. Trust evaluation mechanisms help in identifying and isolating malicious or faulty nodes to prevent potential security risksincluding network failures, unauthorized access, and data breaches [7]. Recent literature has proposed various solutions to address these challenges. Traditional centralized trust management systems rely on a central authority to assess and validate trust, but these models are exposed to single points of failure and scalability issues [8]. Alternatively, distributed trust management approaches have gained traction, leveraging peer-to-peer interactions and reputation systems to evaluate trust. Some studies have explored the use of machine learning algorithms to dynamically assess node behavior and predict trustworthiness [9]. However, these methods often face challenges related to computational overhead and the requirement for real-time data processing [10]. More recent advancements include the adoption of blockchain and distributed ledger technologies to create immutable and transparent trust evaluation frameworks to enhance security and resilience against tampering and fraud [6; 11]. Despite these innovations, there remains a need for more efficient, scalable, and secure trust evaluation mechanisms that can seamlessly integrate with the diverse and dynamic nature of IoT networks. Trust refers to the confidence that one node places in another node within the network to behave predictably and reliably based on its past behavior and interactions [12]. We define trust as a dynamic, context-dependent concept that evolves over time, driven by the node's historical performance and interactions. A node's trustworthiness is determined by its reliability in providing services (such as data transmission, validation of transactions, etc. ), its responsiveness to requests, and its adherence to expected behaviors [13; 14]. The need for a decentralized trustworthiness evaluation mechanism in IoT networks has become increasingly evident as the limitations of centralized systems are more clearly understood. Traditional trust paradigms typically rely on centralized cluster heads to evaluate and disseminate trust information, which creates a single point of failure [15; 16] that can be exploited by malicious actors to disrupt or manipulate network operations. Such centralized architectures also raise significant privacy concerns, as sensitive trust data must be aggregated and processed by a central authority, increasing the risk of unauthorized access or misuse [17]. Furthermore, these models often lack standardized and quantitative trust metrics, which leads to subjective assessments that hinder consistent and reliable decision-making across heterogeneous networks [18].