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20122024
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134 citations · 419 across the 67 of their papers we have counts for

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Showing 2019Show all

9 papers · 1 filter

cs.CR2019

Covert Channel-Based Transmitter Authentication in Controller Area Networks

Xuhang Ying, Giuseppe Bernieri, Mauro Conti +2

In recent years, the security of automotive Cyber-Physical Systems (CPSs) is facing urgent threats due to the widespread use of legacy in-vehicle communication systems. As a repres…

eess.SY2019

Linear Temporal Logic Satisfaction in Adversarial Environments using Secure Control Barrier Certificates

Bhaskar Ramasubramanian, Luyao Niu, Andrew Clark +2

This paper studies the satisfaction of a class of temporal properties for cyber-physical systems (CPSs) over a finite-time horizon in the presence of an adversary, in an environmen…

cs.LG2019★ 13 cited

Are Odds Really Odd? Bypassing Statistical Detection of Adversarial Examples

Hossein Hosseini, Sreeram Kannan, Radha Poovendran

Deep learning classifiers are known to be vulnerable to adversarial examples. A recent paper presented at ICML 2019 proposed a statistical test detection method based on the observ…

cs.CR2019★ 2 cited

Mitigating Vulnerabilities of Voltage-based Intrusion Detection Systems in Controller Area Networks

Sang Uk Sagong, Radha Poovendran, Linda Bushnell

Data for controlling a vehicle is exchanged among Electronic Control Units (ECUs) via in-vehicle network protocols such as the Controller Area Network (CAN) protocol. Since these p…

cs.LG2019★ 1 cited

Potential-Based Advice for Stochastic Policy Learning

Baicen Xiao, Bhaskar Ramasubramanian, Andrew Clark +3

This paper augments the reward received by a reinforcement learning agent with potential functions in order to help the agent learn (possibly stochastic) optimal policies. We show…

cs.LG2019

Dropping Pixels for Adversarial Robustness

Hossein Hosseini, Sreeram Kannan, Radha Poovendran

Deep neural networks are vulnerable against adversarial examples. In this paper, we propose to train and test the networks with randomly subsampled images with high drop rates. We…

cs.CR2019★ 13 cited

Detecting ADS-B Spoofing Attacks using Deep Neural Networks

Xuhang Ying, Joanna Mazer, Giuseppe Bernieri +3

The Automatic Dependent Surveillance-Broadcast (ADS-B) system is a key component of the Next Generation Air Transportation System (NextGen) that manages the increasingly congested…

eess.SY2019

Secure Control under Partial Observability with Temporal Logic Constraints

Bhaskar Ramasubramanian, Andrew Clark, Linda Bushnell +1

This paper studies the synthesis of control policies for an agent that has to satisfy a temporal logic specification in a partially observable environment, in the presence of an ad…

cs.CR2019★ 8 cited

TACAN: Transmitter Authentication through Covert Channels in Controller Area Networks

Xuhang Ying, Giuseppe Bernieri, Mauro Conti +1

Nowadays, the interconnection of automotive systems with modern digital devices offers advanced user experiences to drivers. Electronic Control Units (ECUs) carry out a multitude o…