Device logs are essential for forensic investigations, enterprise monitoring, and fraud detection; however, they often leak personally identifiable information (PII) when exported for third-party analysis. Existing approaches either fail to minimize PII exposure across all stages of log collection and analysis or sacrifice data fidelity, resulting in less effective analysis. We present Proteus, a privacy-preserving device logging framework that enables forensic analysis without disclosing plaintext PII or compromising fidelity, even when facing adversaries with access to multiple snapshots of the log files. To achieve this, Proteus proposes a two-layer scheme that employs keyed-hash pseudonymization of PII fields and time-rotating encryption with ratcheted ephemeral keys to prevent multi-snapshot correlation. For controlled sharing, clients export ratchet states that grant time-bounded access, permitting decryption of pseudonymized tokens that enable linkage and timeline reconstruction without exposing the underlying PII. Subsequent ratchet rotations ensure forward secrecy, while DICE-based attestation authenticates device provenance. We implement Proteus as a transparent extension to Android’s logcat and evaluate it across three generations of hardware. Our results demonstrate a median latency of 0.2 ms per message and an average per-PII-field size overhead of only 97.1 bytes.

The long-awaited smart home revolution has arrived, and with it comes the challenge of managing dozens of potentially vulnerable network devices by average users. While research has developed techniques to fingerprint these devices, and even provide for sophisticated network access control models, such techniques are too complex for end users to manage, require sophisticated systems or unavailable public device descriptions, and proposed network policies have not been tested against real device behaviors. As a result, none of these solutions are available to users today.