During the last decade, there has been a significant advancement in imaging of urologic
diseases. Transrectal ultrasound (TRUS), computerized tomography (CT), magnetic resonance …

Deep learning (DL) systems are increasingly deployed in safety- and security-critical domains
including self-driving cars and malware detection, where the correctness and predictability …

Adversarial examples that fool machine learning models, particularly deep neural networks,
have been a topic of intense research interest, with attacks and defenses being developed …

SSL (Secure Sockets Layer) is the de facto standard for secure Internet communications.
Security of SSL connections against an active network attacker depends on correctly validating …

We evaluate the effectiveness of secret key extraction, for private communication between
two wireless devices, from the received signal strength (RSS) variations on the wireless …

Due to the increasing deployment of Deep Neural Networks (DNNs) in real-world security-critical
domains including autonomous vehicles and collision avoidance systems, formally …

We initiate the study of fair classifiers that are robust to perturbations in the training distribution.
Despite recent progress, the literature on fairness has largely ignored the design of fair …

Many recent works have proposed methods to train classifiers with local robustness properties,
which can provably eliminate classes of evasion attacks for most inputs, but not all inputs. …

Recent advances in Deep Neural Networks (DNNs) have led to the development of DNN-driven
autonomous cars that, using sensors like camera, LiDAR, etc., can drive without any …

Secret keys can be generated and shared between two wireless nodes by measuring and
encoding radio channel characteristics without ever revealing the secret key to an …