## 2 Related Work  
Embedded devices that handle privacy-sensitive data or perform safety-critical functions are increasingly becoming prime targets for cybersecurity threats, such as denial-of-service (DoS) attacks, unauthorized network access, firmware tampering, and more [20]. These devices often run embedded firmware from multiple vendors, meaning that a single vulnerability in one vendor's software can potentially affect a large number of devices that depend on the same component [21]. Nowadays, there is an increasing focus on detecting compromised devices before they can affect the functionality of connected systems. Remote attestation is one method used to ensure device integrity. Depending on the system architecture and security goals, various attestation approaches can be employed. These include single attestation, which verifies the integrity of individual devices, and collective attestation protocols, where multiple devices work together to validate the security of the entire network [22]. Large-scale IoT networks require collective attestation methods to effectively ensure the security of the entire network. One such example is PASTA [23], a fully decentralized attestation mechanism based on Schnorr-based multisignatures. It supports multiple provers and verifiers that can attest their integrity using lightweight tokens, making it ideal for resource-constrained embedded devices with limited computational capabilities. Other collective attestation protocols, such as SEDA [16], use a spanning tree topology where each parent node aggregates the attestation results from its child nodes. The underlying protection mechanisms of the edge devices rely on SMART [24] or TrustLite [25] architectures. Both TEE architectures can provide remote attestation for low-end embedded systems by leveraging custom hardware memory protection units and carefully designed software. However, their disadvantage is that they require hardware modifications to be integrated into current CPU architectures, which poses a challenge for widespread adoption. Currently, collective attestation protocols lack the granularity to provide detailed information about individual devices, making them more suitable for homogeneous sensor networks where devices share similar configurations. In TinyML systems, devices may run different ML model versions, software stacks, and have varying requirements that need verification by a remote verifier. It is essential not only to confirm that a device is operational but also to assess its internal state and the state of its ML model. Methods such as single-device attestation are better suited to meet these specific needs. In [26], the authors present a single device attestation flow based on an off-the-shelf microcontroller (MCU) that leverages ARM TrustZone. The mechanism employs a paging-based process integrity measurement in a Linux-based IoT environment. It also relies on a ROM-based RoT to securely store and manage cryptographic keys, providing a tamper-resistant foundation for the attestation process. The attestation mechanism of the device relies on a simple hash value that is encrypted and sent to a remote server for verification. Relying solely on a hash value for attestation is inadequate, as it does not enable structured, interoperable communication of evidence. Different attestation models have been proposed for resource-constrained devices, where efficiency is crucial. Property-based attestation, utilizing structured claims such as those in PSA or EAT, enables more effective and scalable communication of trust, allowing relying parties to easily verify the security and integrity of devices or systems [27]. The Veraison project [28] seeks to establish standardization and interoperability across various remote attestation frameworks. It contains a set of software components that can be employed to construct attestation verification services that are common across different classes of devices, from IoT devices to large computing servers.