  Cloud platforms are widely adopted by many systems, such as time series
processing systems, to store and process massive amounts of sensitive time
series data. Unfortunately, several incidents have shown that cloud platforms
are vulnerable to internal and external attacks that lead to critical data
breaches. Adopting cryptographic protocols such as homomorphic encryption and
secure multi-party computation adds high computational and network overhead to
query operations.
  We present TimeClave, a fully oblivious in-enclave time series processing
system: TimeClave leverages Intel SGX to support aggregate statistics on time
series with minimal memory consumption inside the enclave. To hide the access
pattern inside the enclave, we introduce a non-blocking read-optimised ORAM
named RoORAM. TimeClave integrates RoORAM to obliviously and securely handle
client queries with high performance. With an aggregation time interval of
$10s$, $2^{14}$ summarised data blocks and 8 aggregate functions, TimeClave run
point query in $0.03ms$ and a range query of 50 intervals in $0.46ms$. Compared
to the ORAM baseline, TimeClave achieves lower query latency by up to
$2.5\times$ and up to $2\times$ throughput, with up to 22K queries per second.
