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Adaptive Learning in Two-Player Stackelberg Games with Application to Network Security
We study a two-player Stackelberg game with incomplete information such ...
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Safety-Critical Online Control with Adversarial Disturbances
This paper studies the control of safety-critical dynamical systems in t...
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Privacy-Preserving Resilience of Cyber-Physical Systems to Adversaries
A cyber-physical system (CPS) is expected to be resilient to more than o...
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Stochastic Dynamic Information Flow Tracking Game using Supervised Learning for Detecting Advanced Persistent Threats
Advanced persistent threats (APTs) are organized prolonged cyberattacks ...
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Secure Control in Partially Observable Environments to Satisfy LTL Specifications
This paper studies the synthesis of control policies for an agent that h...
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A Multi-Agent Reinforcement Learning Approach for Dynamic Information Flow Tracking Games for Advanced Persistent Threats
Advanced Persistent Threats (APTs) are stealthy attacks that threaten th...
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Dynamic Information Flow Tracking for Detection of Advanced Persistent Threats: A Stochastic Game Approach
Advanced Persistent Threats (APTs) are stealthy customized attacks by in...
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FRESH: Interactive Reward Shaping in High-Dimensional State Spaces using Human Feedback
Reinforcement learning has been successful in training autonomous agents...
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Covert Channel-Based Transmitter Authentication in Controller Area Networks
In recent years, the security of automotive Cyber-Physical Systems (CPSs...
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Linear Temporal Logic Satisfaction in Adversarial Environments using Secure Control Barrier Certificates
This paper studies the satisfaction of a class of temporal properties fo...
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Are Odds Really Odd? Bypassing Statistical Detection of Adversarial Examples
Deep learning classifiers are known to be vulnerable to adversarial exam...
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Mitigating Vulnerabilities of Voltage-based Intrusion Detection Systems in Controller Area Networks
Data for controlling a vehicle is exchanged among Electronic Control Uni...
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Potential-Based Advice for Stochastic Policy Learning
This paper augments the reward received by a reinforcement learning agen...
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Dropping Pixels for Adversarial Robustness
Deep neural networks are vulnerable against adversarial examples. In thi...
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Detecting ADS-B Spoofing Attacks using Deep Neural Networks
The Automatic Dependent Surveillance-Broadcast (ADS-B) system is a key c...
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Secure Control under Partial Observability with Temporal Logic Constraints
This paper studies the synthesis of control policies for an agent that h...
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TACAN: Transmitter Authentication through Covert Channels in Controller Area Networks
Nowadays, the interconnection of automotive systems with modern digital ...
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A Game Theoretic Approach for Dynamic Information Flow Tracking to Detect Multi-Stage Advanced Persistent Threats
Advanced Persistent Threats (APTs) infiltrate cyber systems and compromi...
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Shape of the Cloak: Formal Analysis of Clock Skew-Based Intrusion Detection System in Controller Area Networks
This paper presents a new masquerade attack called the cloaking attack a...
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Assessing Shape Bias Property of Convolutional Neural Networks
It is known that humans display "shape bias" when classifying new items,...
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Semantic Adversarial Examples
Deep neural networks are known to be vulnerable to adversarial examples,...
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Attacking Automatic Video Analysis Algorithms: A Case Study of Google Cloud Video Intelligence API
Due to the growth of video data on Internet, automatic video analysis ha...
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Deceiving Google's Cloud Video Intelligence API Built for Summarizing Videos
Despite the rapid progress of the techniques for image classification, v...
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On the Limitation of Convolutional Neural Networks in Recognizing Negative Images
Convolutional Neural Networks (CNNs) have achieved state-of-the-art perf...
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Learning Temporal Dependence from Time-Series Data with Latent Variables
We consider the setting where a collection of time series, modeled as ra...
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Group Event Detection with a Varying Number of Group Members for Video Surveillance
This paper presents a novel approach for automatic recognition of group ...
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Activity Recognition Using A Combination of Category Components And Local Models for Video Surveillance
This paper presents a novel approach for automatic recognition of human ...
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