# Collective Attestation for Manageable IoT Environments
## 2 Related Work  
Attestation for IoT/WSN devices.Attestation has been researched in a number of studies. The research work on attestation can be categorized into three approaches. First, software-based attestation [9; 10; 11; 12] targets constrained devices especially for the WSN/IoT environment. Under the assumption that forging a result incurs additional computation overhead inevitably, the software-based attestation optimizes the checksum code and then uses the time-based checksum results. This approach is suitable for low-end devices since they require no hardware additions. However, the remote attestation through wireless communications may suffer from various network delay or network failures. Thus, the use of software attestation is limited to the one-hop attestation, which restricts the practical use of attestations [13]. Second, the co-processor based attestation [3; 4; 5; 6; 7; 8] lets devices prove their integrity by using the secure result from the security co-processors, i.e., Trusted Platform Module (TPM) [33]. The security co-processor can guarantee the secure execution of attestation code and generate the machine-unique digital signature on the attestation results. Although the hardware-backed attestation provides the trustworthy results, the cost for the security co-processor is still high for a large-scale WSN/IoT devices. Third, the hybrid approaches [14; 15; 16; 17] employ the low-cost, simple hardware supports (e.g., ROM and MPU), to reinforce the process of attestation. The read-only attestation code and secure key provide the basic trust base on the attestation, but it obstructs the efficient update process (e.g., OTA software update), and increases the maintenance cost in operation. These approaches apply individual identification to recognize compromised nodes. Thus, when attesting to a large number of devices, the runtime for attestation increases linearly with the number of compromised devices. However, the proposed scheme takes the approach of the collective attestation and coalesced measurement report for scalability. **Collective Attestation. ** In order to apply attestation to multiple provers, the collective attestation approaches have been proposed in [18; 19; 20; 21; 22; 23]. SMATT [18] is the first attempt for attesting multiple provers, and it is proposed for the attestation on smart meters. SMATT assumes that all the devices are identical. It compares the measurement results from randomly sampled devices and then identifies compromised devices that give different results from others. It has been evolved into collective (or swarm) attestation approaches to target a larger number of devices for attestation. Among them, SEDA [19] and SANA [21] are closely related to our work. SEDA performs the in-network verification to improve the scalability of attestation. A newly arrived device registers itself to a neighbor with its certificate to prove the software configuration. Like other collective attestation methods, SEDA assumes the minimal trust anchor, such as SMART [15] and TrustLite [16], of the hybrid attestation. Upon the attestation request, SEDA builds a spanning tree and reports the result of the integrity checks reversely along the spanning tree. SANA extends the swarm attestation by using Optimistic Aggregate Signature (OAS), which supports aggregation and multi-signatures. SANA uses the spanning tree as the aggregation tree. At the confluence point, the OAS signed reports from provers are aggregated. If a compromised device is found during the process, the aggregator appends the signature of the compromised device to the message. SEDA and SANA provide the mechanism to identify compromised devices at collective attestation, but the individual identification is not scalable to contagious malware infections, of which a large number of infected devices may overwhelm the normal attestation process. In addition, although OAS is much more efficient than the traditional public key cryptography, it still requires a high amount of computation for IoT/WSN devices.