Today's Internet services rely heavily on text-based passwords for user authentication. The
pervasiveness of these services coupled with the difficulty of remembering large numbers of …

As eye tracking becomes pervasive with screen-based devices and head-mounted displays,
privacy concerns regarding eye-tracking data have escalated. While state-of-the-art …

When processing data in the encrypted domain, homomorphic encryption can be used to
enable linear operations on encrypted data. Integer division of encrypted data however …

Alice possesses a sample of private data from which she wishes to obtain some probabilistic
inference. Bob possesses Hidden Markov Models (HMMs) for this purpose, but he wants the …

Text mining is the process to automatically infer relevant information from semantically
related text documents. This technique, which has applications from business intelligence to …

The edit distance is a metric widely used in genomics to measure the similarity of two DNA
chains. Motivated by privacy concerns, we propose a 2PC protocol to compute the edit …

A method for verifying a similarity between a first signal and a second signal is described.
The first and the second signals are encrypted homomorphically using a key. First, we …

With the ever-growing data and the need for developing powerful machine learning models,
data owners increasingly depend on various untrusted platforms (eg, public clouds, edges …

As web attackers hide themselves by using multi-step springboard (eg, VPN, encrypted
proxy) or anonymous network (ie Tor network), it raises a big obstacle for traceability and …

Web attacks have proliferated across the whole Internet in recent years. To protect websites,
security vendors and researchers collect attack information using web honeypots. However …