Supervised machine learning is a branch of artificial intelligence concerned with learning computer programs to automatically improve with experience through knowledge extraction from examples. It builds predictive models from labeled data. Such learning approaches are useful for many interesting real-world applications, but are particularly useful for tasks involving the automatic categorizati...

We show how to add key recovery to existing security protocols such as SSL/TLS and SSH without changing the protocol. Our key recovery designs possess the following novel features: (1) The Key recovery channels are “unfilterable” — the key recovery channels cannot be removed without also breaking correct operation of the protocol. (2) Protocol implementations containing our key recovery designs...

Most tools to recognize the application associated with network connections use well-known signatures as basis for their classification. This approach is very effective in enterprise and campus networks to pinpoint forbidden applications (peer to peer, for instance) or security threats. However, it is easy to use encryption to evade these mechanisms. In particular, Secure Sockets Layer (SSL) li...

Most secure web sites use the SSL/TLS protocol for server authentication. SSL/TLS supports mutual authentication, i.e. both server and client authentication. However, this optional feature of SSL/TLS is not used by most web sites because not every client has a certified public key. Instead user authentication is typically achieved by sending a password to the server after the establishment of a...

I-MINDS is a computer-supported collaborative learning environment which allows an instructor to establish a virtual online classroom where the students can login an collaborate with each other. This collaboration allows the students to learn from both the instructor and the other students. During this classroom session, I-MINDS works as a communication platform for the students and the instruc...

We present an algorithmic approach for speeding up SSL’s performance on a web server. Our approach improves the performance of SSL’s handshake protocol by up to a factor of 2.5 for 1024-bit RSA keys. It is designed for heavily-loaded web servers handling many concurrent SSL sessions. We improve the server’s performance by batching the SSL handshake protocol. That is, we show that b SSL handshak...

Purpose. To evaluate intraobserver and interobserver agreement in locating the scleral spur landmark (SSL) and anterior chamber angle measurements obtained using Fourier Domain Anterior Segment Optical Coherence Tomography (ASOCT) images. Methods. Two independent, masked observers (SR and AZC) identified SSLs on ASOCT images from 31 eyes with open and nonopen angles. A third independent reader,...

From a machine learning perspective, the human ability localize sounds can be modeled as a non-parametric and non-linear regression problem between binaural spectral features of sound received at the ears (input) and their sound-source directions (output). The input features can be summarized in terms of the individual’s head-related transfer functions (HRTFs) which measure the spectral respons...

Semi-Supervised Learning (SSL) techniques have become very relevant since they require a small set of labeled data. In this scenario, graph-based SSL algorithms provide a powerful framework for modeling manifold structures in high-dimensional spaces and are effective for the propagation of the few initial labels present in training data through the graph. An important step in graph-based SSL me...