2.4k citations · 2.8k across the 25 of their papers we have counts for
26 papers
CallShield: Secure Caller Authentication over Real-Time Audio Channels
Mouna Rabh, Yazan Boshmaf, Mashael Alsabah +3
We present CallShield, the first caller identity authentication system that operates entirely at the audio layer, without relying on speech transcription, internet connectivity, or…
A Client-level Assessment of Collaborative Backdoor Poisoning in Non-IID Federated Learning
Phung Lai, Guanxiong Liu, NhatHai Phan +3
Federated learning (FL) enables collaborative model training using decentralized private data from multiple clients. While FL has shown robustness against poisoning attacks with ba…
Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection
Mahmoud Nazzal, Issa Khalil, Abdallah Khreishah +2
Malicious domain detection (MDD) is an open security challenge that aims to detect if an Internet domain is associated with cyber-attacks. Among many approaches to this problem, gr…
Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks
Khang Tran, Phung Lai, NhatHai Phan +5
Graph neural networks (GNNs) are susceptible to privacy inference attacks (PIAs), given their ability to learn joint representation from features and edges among nodes in graph dat…
An Adaptive Black-box Defense against Trojan Attacks (TrojDef)
Guanxiong Liu, Abdallah Khreishah, Fatima Sharadgah +1
Trojan backdoor is a poisoning attack against Neural Network (NN) classifiers in which adversaries try to exploit the (highly desirable) model reuse property to implant Trojans int…
Exploration of Enterprise Server Data to Assess Ease of Modeling System Behavior
Enes Altinisik, Husrev Taha Sencar, Mohamed Nabeel +2
Enterprise networks are one of the major targets for cyber attacks due to the vast amount of sensitive and valuable data they contain. A common approach to detecting attacks in the…
A Large Scale Study and Classification of VirusTotal Reports on Phishing and Malware URLs
Euijin Choo, Mohamed Nabeel, Ravindu De Silva +2
VirusTotal (VT) provides aggregated threat intelligence on various entities including URLs, IP addresses, and binaries. It is widely used by researchers and practitioners to collec…
How to Backdoor HyperNetwork in Personalized Federated Learning?
Phung Lai, NhatHai Phan, Issa Khalil +2
This paper explores previously unknown backdoor risks in HyperNet-based personalized federated learning (HyperNetFL) through poisoning attacks. Based upon that, we propose a novel…
A Synergetic Attack against Neural Network Classifiers combining Backdoor and Adversarial Examples
Guanxiong Liu, Issa Khalil, Abdallah Khreishah +1
In this work, we show how to jointly exploit adversarial perturbation and model poisoning vulnerabilities to practically launch a new stealthy attack, dubbed AdvTrojan. AdvTrojan i…
Time-Window Group-Correlation Support vs. Individual Features: A Detection of Abnormal Users
Lun-Pin Yuan, Euijin Choo, Ting Yu +2
Autoencoder-based anomaly detection methods have been used in identifying anomalous users from large-scale enterprise logs with the assumption that adversarial activities do not fo…
Morshed: Guiding Behavioral Decision-Makers towards Better Security Investment in Interdependent Systems
Mustafa Abdallah, Daniel Woods, Parinaz Naghizadeh +4
We model the behavioral biases of human decision-making in securing interdependent systems and show that such behavioral decision-making leads to a suboptimal pattern of resource a…
ManiGen: A Manifold Aided Black-box Generator of Adversarial Examples
Guanxiong Liu, Issa Khalil, Abdallah Khreishah +5
Machine learning models, especially neural network (NN) classifiers, have acceptable performance and accuracy that leads to their wide adoption in different aspects of our daily li…
BASCPS: How does behavioral decision making impact the security of cyber-physical systems?
Mustafa Abdallah, Daniel Woods, Parinaz Naghizadeh +4
We study the security of large-scale cyber-physical systems (CPS) consisting of multiple interdependent subsystems, each managed by a different defender. Defenders invest their sec…
Using Single-Step Adversarial Training to Defend Iterative Adversarial Examples
Guanxiong Liu, Issa Khalil, Abdallah Khreishah
Adversarial examples have become one of the largest challenges that machine learning models, especially neural network classifiers, face. These adversarial examples break the assum…
DeviceWatch: Identifying Compromised Mobile Devices through Network Traffic Analysis and Graph Inference
Euijin Choo, Mohamed Nabeel, Mashael Alsabah +3
In this paper, we propose to identify compromised mobile devices from a network administrator's point of view. Intuitively, inadvertent users (and thus their devices) who download…
Using Intuition from Empirical Properties to Simplify Adversarial Training Defense
Guanxiong Liu, Issa Khalil, Abdallah Khreishah
Due to the surprisingly good representation power of complex distributions, neural network (NN) classifiers are widely used in many tasks which include natural language processing,…
ZK-GanDef: A GAN based Zero Knowledge Adversarial Training Defense for Neural Networks
Guanxiong Liu, Issa Khalil, Abdallah Khreishah
Neural Network classifiers have been used successfully in a wide range of applications. However, their underlying assumption of attack free environment has been defied by adversari…
GanDef: A GAN based Adversarial Training Defense for Neural Network Classifier
Guanxiong Liu, Issa Khalil, Abdallah Khreishah
Machine learning models, especially neural network (NN) classifiers, are widely used in many applications including natural language processing, computer vision and cybersecurity.…
A Survey on Malicious Domains Detection through DNS Data Analysis
Yury Zhauniarovich, Issa Khalil, Ting Yu +1
Malicious domains are one of the major resources required for adversaries to run attacks over the Internet. Due to the important role of the Domain Name System (DNS), extensive res…
Unmanned Aerial Vehicles: A Survey on Civil Applications and Key Research Challenges
Hazim Shakhatreh, Ahmad Sawalmeh, Ala Al-Fuqaha +6
The use of unmanned aerial vehicles (UAVs) is growing rapidly across many civil application domains including real-time monitoring, providing wireless coverage, remote sensing, sea…
Killing Two Birds with One Stone: Malicious Domain Detection with High Accuracy and Coverage
Issa Khalil, Bei Guan, Mohamed Nabeel +1
Inference based techniques are one of the major approaches to analyze DNS data and detecting malicious domains. The key idea of inference techniques is to first define associations…
The Indoor Mobile Coverage Problem Using UAVs
Hazim Shakhatreh, Abdallah Khreishah, Issa Khalil
Unmanned aerial vehicles (UAVs) can be used as aerial wireless base stations when cellular networks are not operational due to natural disasters. They can also be used to supplemen…
Efficient 3D Placement of a UAV Using Particle Swarm Optimization
Hazim Shakhatreh, Abdallah Khreishah, Ayoub Alsarhan +3
Unmanned aerial vehicles (UAVs) can be used as aerial wireless base stations when cellular networks go down. Prior studies on UAV-based wireless coverage typically consider an Air-…
On The Continuous Coverage Problem for a Swarm of UAVs
Hazim Shakhatreh, Abdallah Khreishah, Jacob Chakareski +2
Unmanned aerial vehicles (UAVs) can be used to provide wireless network and remote surveillance coverage for disaster-affected areas. During such a situation, the UAVs need to retu…