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09/05/2023
The Adversarial Implications of Variable-Time Inference
Machine learning (ML) models are known to be vulnerable to a number of a...
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03/02/2023
D-Score: An Expert-Based Method for Assessing the Detectability of IoT-Related Cyber-Attacks
IoT devices are known to be vulnerable to various cyber-attacks, such as...
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11/27/2022
Latent SHAP: Toward Practical Human-Interpretable Explanations
Model agnostic feature attribution algorithms (such as SHAP and LIME) ar...
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11/16/2022
Attacking Object Detector Using A Universal Targeted Label-Switch Patch
Adversarial attacks against deep learning-based object detectors (ODs) h...
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11/16/2022
Improving Interpretability via Regularization of Neural Activation Sensitivity
State-of-the-art deep neural networks (DNNs) are highly effective at tac...
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09/08/2022
Evaluating the Security of Aircraft Systems
The sophistication and complexity of cyber attacks and the variety of ta...
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01/16/2022
Adversarial Machine Learning Threat Analysis in Open Radio Access Networks
The Open Radio Access Network (O-RAN) is a new, open, adaptive, and inte...
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01/16/2022
Evaluating the Security of Open Radio Access Networks
The Open Radio Access Network (O-RAN) is a promising RAN architecture, a...
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09/23/2021
On The Vulnerability of Anti-Malware Solutions to DNS Attacks
Anti-malware agents typically communicate with their remote services to ...
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07/05/2021
A Framework for Evaluating the Cybersecurity Risk of Real World, Machine Learning Production Systems
Although cyberattacks on machine learning (ML) production systems can be...
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09/23/2020
Adversarial robustness via stochastic regularization of neural activation sensitivity
Recent works have shown that the input domain of any machine learning cl...
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08/10/2020
An Automated, End-to-End Framework for Modeling Attacks From Vulnerability Descriptions
Attack graphs are one of the main techniques used to automate the risk a...
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06/30/2020
Autosploit: A Fully Automated Framework for Evaluating the Exploitability of Security Vulnerabilities
The existence of a security vulnerability in a system does not necessari...
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02/06/2020
Neural Network Representation Control: Gaussian Isolation Machines and CVC Regularization
In many cases, neural network classifiers are likely to be exposed to in...
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09/08/2019
When Explainability Meets Adversarial Learning: Detecting Adversarial Examples using SHAP Signatures
State-of-the-art deep neural networks (DNNs) are highly effective in sol...
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06/26/2019
Heuristic Approach Towards Countermeasure Selection using Attack Graphs
Selecting the optimal set of countermeasures is a challenging task that ...
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06/24/2019
Evaluating the Information Security Awareness of Smartphone Users
Information security awareness (ISA) is a practice focused on the set of...
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06/24/2019
Extending Attack Graphs to Represent Cyber-Attacks in Communication Protocols and Modern IT Networks
An attack graph is a method used to enumerate the possible paths that an...
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12/12/2018
Analysis of Location Data Leakage in the Internet Traffic of Android-based Mobile Devices
In recent years we have witnessed a shift towards personalized, context-...
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05/11/2018