Statistical machine learning techniques have recently garnered increased popularity as a means to improve network design and security. For intrusion detection, such methods build ...
Benjamin I. P. Rubinstein, Blaine Nelson, Ling Hua...
Re-identification is a major privacy threat to public datasets containing individual records. Many privacy protection algorithms rely on generalization and suppression of "qu...
Abstract. In the bounded-storage model (BSM) for information-theoretically secure encryption and key-agreement one uses a random string R whose length t is greater than the assumed...
In this paper we introduce a framework for privacypreserving distributed computation that is practical for many real-world applications. The framework is called Peers for Privacy ...
Yitao Duan, NetEase Youdao, John Canny, Justin Z. ...
The strongest standard security notion for digital signature schemes is unforgeability under chosen message attacks. In practice, however, this notion can be insufficient due to â€...
Sebastian Faust, Eike Kiltz, Krzysztof Pietrzak, G...