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08/22/2023
Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection
Malicious domain detection (MDD) is an open security challenge that aims...
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11/10/2022
Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks
Graph neural networks (GNNs) are susceptible to privacy inference attack...
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09/05/2022
An Adaptive Black-box Defense against Trojan Attacks (TrojDef)
Trojan backdoor is a poisoning attack against Neural Network (NN) classi...
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06/12/2022
Exploration of Enterprise Server Data to Assess Ease of Modeling System Behavior
Enterprise networks are one of the major targets for cyber attacks due t...
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05/26/2022
A Large Scale Study and Classification of VirusTotal Reports on Phishing and Malware URLs
VirusTotal (VT) provides aggregated threat intelligence on various entit...
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01/18/2022
Model Transferring Attacks to Backdoor HyperNetwork in Personalized Federated Learning
This paper explores previously unknown backdoor risks in HyperNet-based ...
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09/03/2021
A Synergetic Attack against Neural Network Classifiers combining Backdoor and Adversarial Examples
In this work, we show how to jointly exploit adversarial perturbation an...
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12/27/2020
Time-Window Group-Correlation Support vs. Individual Features: A Detection of Abnormal Users
Autoencoder-based anomaly detection methods have been used in identifyin...
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11/12/2020
Morshed: Guiding Behavioral Decision-Makers towards Better Security Investment in Interdependent Systems
We model the behavioral biases of human decision-making in securing inte...
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07/11/2020
ManiGen: A Manifold Aided Black-box Generator of Adversarial Examples
Machine learning models, especially neural network (NN) classifiers, hav...
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04/04/2020
BASCPS: How does behavioral decision making impact the security of cyber-physical systems?
We study the security of large-scale cyber-physical systems (CPS) consis...
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02/22/2020
Using Single-Step Adversarial Training to Defend Iterative Adversarial Examples
Adversarial examples have become one of the largest challenges that mach...
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11/27/2019
DeviceWatch: Identifying Compromised Mobile Devices through Network Traffic Analysis and Graph Inference
In this paper, we propose to identify compromised mobile devices from a ...
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06/27/2019
Using Intuition from Empirical Properties to Simplify Adversarial Training Defense
Due to the surprisingly good representation power of complex distributio...
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04/17/2019
ZK-GanDef: A GAN based Zero Knowledge Adversarial Training Defense for Neural Networks
Neural Network classifiers have been used successfully in a wide range o...
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03/06/2019
GanDef: A GAN based Adversarial Training Defense for Neural Network Classifier
Machine learning models, especially neural network (NN) classifiers, are...
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05/22/2018
A Survey on Malicious Domains Detection through DNS Data Analysis
Malicious domains are one of the major resources required for adversarie...
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04/19/2018
Unmanned Aerial Vehicles: A Survey on Civil Applications and Key Research Challenges
The use of unmanned aerial vehicles (UAVs) is growing rapidly across man...
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11/01/2017