Machine learning models that use deep neural networks (DNNs) are vulnera...
Autonomous cyber and cyber-physical systems need to perform decision-mak...
Electric Vehicles (EVs) share common technologies with classical
fossil-...
The data used to train deep neural network (DNN) models in applications ...
Dynamic wireless power transfer provides means for charging Electric Veh...
Machine learning models in the wild have been shown to be vulnerable to
...
Recent advancements in wireless charging technology, as well as the
poss...
Binary analysis of software is a critical step in cyber forensics
applic...
Machine learning (ML) models that use deep neural networks are vulnerabl...
Cyber and cyber-physical systems equipped with machine learning algorith...
To support the increasing spread of Electric Vehicles (EVs), Charging
St...
Reinforcement learning involves agents interacting with an environment t...
This paper considers multi-agent reinforcement learning (MARL) tasks whe...
The inputs and preferences of human users are important considerations i...
Multi-agent reinforcement learning involves multiple agents interacting ...
Multi-agent Markov Decision Processes (MMDPs) arise in a variety of
appl...
We study a two-player Stackelberg game with incomplete information such ...
This paper studies the control of safety-critical dynamical systems in t...
A cyber-physical system (CPS) is expected to be resilient to more than o...
Advanced persistent threats (APTs) are organized prolonged cyberattacks ...
This paper studies the synthesis of control policies for an agent that h...
Advanced Persistent Threats (APTs) are stealthy attacks that threaten th...
Advanced Persistent Threats (APTs) are stealthy customized attacks by
in...
Reinforcement learning has been successful in training autonomous agents...
In recent years, the security of automotive Cyber-Physical Systems (CPSs...
This paper studies the satisfaction of a class of temporal properties fo...
Deep learning classifiers are known to be vulnerable to adversarial exam...
Data for controlling a vehicle is exchanged among Electronic Control Uni...
This paper augments the reward received by a reinforcement learning agen...
Deep neural networks are vulnerable against adversarial examples. In thi...
The Automatic Dependent Surveillance-Broadcast (ADS-B) system is a key
c...
This paper studies the synthesis of control policies for an agent that h...
Nowadays, the interconnection of automotive systems with modern digital
...
Advanced Persistent Threats (APTs) infiltrate cyber systems and compromi...
This paper presents a new masquerade attack called the cloaking attack a...
It is known that humans display "shape bias" when classifying new items,...
Deep neural networks are known to be vulnerable to adversarial examples,...
Due to the growth of video data on Internet, automatic video analysis ha...
Despite the rapid progress of the techniques for image classification, v...
Convolutional Neural Networks (CNNs) have achieved state-of-the-art
perf...
We consider the setting where a collection of time series, modeled as ra...
This paper presents a novel approach for automatic recognition of group
...
This paper presents a novel approach for automatic recognition of human
...