Many network solutions and overlay networks utilize probabilistic techniques to reduce
information processing and networking costs. This survey article presents a number of …

The Bloom filter provides fast approximate set membership while using little memory.
Engineers often use these filters to avoid slow operations such as disk or network accesses …

Encrypted multi-map (EMM), as a special case of structured encryption, has attracted
extensive attention recently. However, most of EMM constructions reveal the real volumes of …

Searchable symmetric encryption (SSE) enables a client to store a database on an untrusted
server while supporting keyword search in a secure manner. Despite the rapidly increasing …

A hash function h, ie, a function from the set U of all keys to the range range [m]={0,..., m− 1}
is called a perfect hash function (PHF) for a subset S⊆ U of size n≤ m if h is 1-1 on S. The …

We settle the question of tight thresholds for offline cuckoo hashing. The problem can be
stated as follows: we have n keys to be hashed into m buckets each capable of holding a …

The performance of a dynamic dictionary is measured mainly by its update time, lookup time,
and space consumption. In terms of update time and lookup time there are known …

Filter data structures over-approximate a set of hashable keys, ie set membership queries
may incorrectly come out positive. A filter with false positive rate $ f\in (0, 1] $ is known to …

Bloom and cuckoo filters provide fast approximate set membership while using little memory.
Engineers use them to avoid expensive disk and network accesses. The recently introduced …

Probabilistic data structures use space-efficient representations of data in order to
(approximately) respond to queries about the data. Traditionally, these structures are …