Publications (45)
Joint Link Scheduling and Brightness Control for Greening VLC-based Indoor Access Networks
Sihua Shao, Abdallah Khreishah, Issa Khalil
Demands for broadband wireless access services is expected to outstrip the spectrum capacity in the near-term - "spectrum crunch". Deploying additional femotocells to address this…
FairDP: Certified Fairness with Differential Privacy
Khang Tran, Ferdinando Fioretto, Issa Khalil +2
This paper introduces FairDP, a novel training mechanism designed to provide group fairness certification for the trained model's decisions, along with a differential privacy (DP)…
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…
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-…
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…
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…
Asymptotically-Optimal Incentive-Based En-Route Caching Scheme
Ammar Gharaibeh, Abdallah Khreishah, Issa Khalil +1
Content caching at intermediate nodes is a very effective way to optimize the operations of Computer networks, so that future requests can be served without going back to the origi…
Demo: SGCode: A Flexible Prompt-Optimizing System for Secure Generation of Code
Khiem Ton, Nhi Nguyen, Mahmoud Nazzal +6
This paper introduces SGCode, a flexible prompt-optimizing system to generate secure code with large language models (LLMs). SGCode integrates recent prompt-optimization approaches…
StructTransform: A Scalable Attack Surface for Safety-Aligned Large Language Models
Shehel Yoosuf, Temoor Ali, Ahmed Lekssays +2
In this work, we present a series of structure transformation attacks on LLM alignment, where we encode natural language intent using diverse syntax spaces, ranging from simple str…
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…
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…
Poison with Style: A Practical Poisoning Attack on Code Large Language Models
Khang Tran, Yazan Boshmaf, Issa Khalil +3
Code Large Language Models (CLLMs) serve as the core of modern code agents, enabling developers to automate complex software development tasks. In this paper, we present Poison-wit…
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…
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…
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…
NOIR: Privacy-Preserving Generation of Code with Open-Source LLMs
Khoa Nguyen, Khiem Ton, NhatHai Phan +6
Although boosting software development performance, large language model (LLM)-powered code generation introduces intellectual property and data security risks rooted in the fact t…
Gradient Transformer: Learning to Generate Updates for LLMs
Binh-Nguyen Nguyen, Khang Tran, NhatHai Phan +1
Many organizations lack computational resources to fine-tune large language models (LLMs) on private (unshareable) data for better utility, while fine-tuning tiny language models (…
Unmasking Synthetic Realities in Generative AI: A Comprehensive Review of Adversarially Robust Deepfake Detection Systems
Naseem Khan, Tuan Nguyen, Amine Bermak +1
The rapid advancement of Generative Artificial Intelligence has fueled deepfake proliferation-synthetic media encompassing fully generated content and subtly edited authentic mater…
MANTIS: Detection of Zero-Day Malicious Domains Leveraging Low Reputed Hosting Infrastructure
Fatih Deniz, Mohamed Nabeel, Ting Yu +1
Internet miscreants increasingly utilize short-lived disposable domains to launch various attacks. Existing detection mechanisms are either too late to catch such malicious domains…
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…
LLMxCPG: Context-Aware Vulnerability Detection Through Code Property Graph-Guided Large Language Models
Ahmed Lekssays, Hamza Mouhcine, Khang Tran +2
Software vulnerabilities present a persistent security challenge, with over 25,000 new vulnerabilities reported in the Common Vulnerabilities and Exposures (CVE) database in 2024 a…
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…
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…
aiXamine: Simplified LLM Safety and Security
Fatih Deniz, Dorde Popovic, Yazan Boshmaf +4
Evaluating Large Language Models (LLMs) for safety and security remains a complex task, often requiring users to navigate a fragmented landscape of ad hoc benchmarks, datasets, met…
CAMME: Adaptive Deepfake Image Detection with Multi-Modal Cross-Attention
Naseem Khan, Tuan Nguyen, Amine Bermak +1
The proliferation of sophisticated AI-generated deepfakes poses critical challenges for digital media authentication and societal security. While existing detection methods perform…
DeBackdoor: A Deductive Framework for Detecting Backdoor Attacks on Deep Models with Limited Data
Dorde Popovic, Amin Sadeghi, Ting Yu +2
Backdoor attacks are among the most effective, practical, and stealthy attacks in deep learning. In this paper, we consider a practical scenario where a developer obtains a deep mo…
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…
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…
PRPO: Paragraph-level Policy Optimization for Vision-Language Deepfake Detection
Tuan Nguyen, Naseem Khan, Khang Tran +2
The rapid rise of synthetic media has made deepfake detection a critical challenge for online safety and trust. Progress remains constrained by the scarcity of large, high-quality…
ViGText: Deepfake Image Detection with Vision-Language Model Explanations and Graph Neural Networks
Ahmad ALBarqawi, Mahmoud Nazzal, Issa Khalil +2
The rapid rise of deepfake technology, which produces realistic but fraudulent digital content, threatens the authenticity of media. Traditional deepfake detection approaches often…
Ten Years after ImageNet: A 360° Perspective on AI
Sanjay Chawla, Preslav Nakov, Ahmed Ali +7
It is ten years since neural networks made their spectacular comeback. Prompted by this anniversary, we take a holistic perspective on Artificial Intelligence (AI). Supervised Lear…
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…
SGFusion: Stochastic Geographic Gradient Fusion in Federated Learning
Khoa Nguyen, Khang Tran, NhatHai Phan +3
This paper proposes Stochastic Geographic Gradient Fusion (SGFusion), a novel training algorithm to leverage the geographic information of mobile users in Federated Learning (FL).…
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…
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…
Explainable AI-based Intrusion Detection System for Industry 5.0: An Overview of the Literature, associated Challenges, the existing Solutions, and Potential Research Directions
Naseem Khan, Kashif Ahmad, Aref Al Tamimi +3
Industry 5.0, which focuses on human and Artificial Intelligence (AI) collaboration for performing different tasks in manufacturing, involves a higher number of robots, Internet of…
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…
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.…
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,…
PromSec: Prompt Optimization for Secure Generation of Functional Source Code with Large Language Models (LLMs)
Mahmoud Nazzal, Issa Khalil, Abdallah Khreishah +1
The capability of generating high-quality source code using large language models (LLMs) reduces software development time and costs. However, they often introduce security vulnera…
CapsFake: A Multimodal Capsule Network for Detecting Instruction-Guided Deepfakes
Tuan Nguyen, Naseem Khan, Issa Khalil
The rapid evolution of deepfake technology, particularly in instruction-guided image editing, threatens the integrity of digital images by enabling subtle, context-aware manipulati…
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…
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…
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…