Redis (Remote Dictionary Server) is a general purpose, in-memory database that supports a rich array of functionality, including various Probabilistic Data Structures (PDS), such as Bloom filters, Cuckoo filters, as well as cardinality and frequency estimators. These PDS typically perform well in the average case. However, given that Redis is intended to be used across a diverse array of applications, it is crucial to evaluate how these PDS perform under worst-case scenarios, i.e., when...

We present Waffle, a datastore that protects an application’s data access patterns from a passive persistent adversary. Waffle achieves this without prior knowledge of the input data access distribution, making it the first of its kind to adaptively handle input sequences under a passive persistent adversary. Waffle maintains a constant bandwidth and client-side storage overhead, which can be adjusted to suit the application owner’s preferences. This flexibility allows the owner to fine-tune...

Computing the count of distinct elements in large data sets is a common task but naive approaches are memory-expensive. The HyperLogLog (HLL) algorithm (Flajolet et al., 2007) estimates a data set’s cardinality while using significantly less memory than a naive approach, at the cost of some accuracy. This trade-off makes the HLL algorithm very attractive for a wide range of applications such as database management and network monitoring, where an exact count may not be needed. The HLL...

While businesses shift their databases to the cloud, they continue to depend on them to operate correctly. Alarmingly, cloud services constantly face threats from exploits in the privileged computing layers (e.g. OS, Hypervisor) and attacks from rogue datacenter administrators, which tamper with the database's storage and cause it to produce incorrect results. Although integrity verification of outsourced storage and file systems is a well-studied problem, prior techniques impose prohibitive...