2.4k citations · 3.3k across the 39 of their papers we have counts for
43 papers
From Normative Frameworks to Alignment Data: Constructing and Evaluating SFT and Preference Data
Husrev Taha Sencar, Rezart Beka, Danish Naeem +6
Aligning language models with a specified normative framework requires translating abstract principles into concrete examples and preference signals from which models can learn. We…
Budget-Constrained Online Retrieval-Augmented Generation: The Chunk-as-a-Service Model
Shawqi Al-Maliki, Ammar Gharaibeh, Mohamed Rahouti +4
Large Language Models (LLMs) have revolutionized the field of natural language processing. However, they exhibit some limitations, including a lack of reliability and transparency:…
A Multi-Perspective Benchmark and Moderation Model for Evaluating Safety and Adversarial Robustness
Naseem Machlovi, Maryam Saleki, Ruhul Amin +5
As large language models (LLMs) become deeply embedded in daily life, the urgent need for safer moderation systems that distinguish between naive and harmful requests while upholdi…
Can LLMs Write Faithfully? An Agent-Based Evaluation of LLM-generated Islamic Content
Abdullah Mushtaq, Rafay Naeem, Ezieddin Elmahjub +5
Large language models are increasingly used for Islamic guidance, but risk misquoting texts, misapplying jurisprudence, or producing culturally inconsistent responses. We pilot an…
Large Language Model Enhanced Particle Swarm Optimization for Hyperparameter Tuning for Deep Learning Models
Saad Hameed, Basheer Qolomany, Samir Brahim Belhaouari +3
Determining the ideal architecture for deep learning models, such as the number of layers and neurons, is a difficult and resource-intensive process that frequently relies on human…
A Survey of Social Cybersecurity: Techniques for Attack Detection, Evaluations, Challenges, and Future Prospects
Aos Mulahuwaish, Basheer Qolomany, Kevin Gyorick +5
In today's digital era, the Internet, especially social media platforms, plays a significant role in shaping public opinions, attitudes, and beliefs. Unfortunately, the credibility…
Resource Constraint Estimation of In-Quantum Implementated Mini-AES
Syed Shahmir, Ghulam Murtaza, Ala-Al-Fuqaha +2
The advancement in quantum technology has brought the implementation of Grover's Search attack on cybersecurity algorithms much closer to reality. For such tasks, the Hilbert space…
Safeguarding connected autonomous vehicle communication: Protocols, intra- and inter-vehicular attacks and defenses
Mohammed Aledhari, Rehma Razzak, Mohamed Rahouti +6
The advancements in autonomous driving technology, coupled with the growing interest from automotive manufacturers and tech companies, suggest a rising adoption of Connected Autono…
Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription
Mahdi Alkaeed, Sofiat Abioye, Adnan Qayyum +7
In response to the success of proprietary Large Language Models (LLMs), there is a growing interest in developing open, non-proprietary LLMs and AI foundation models (AIFMs) for tr…
Layer-Wise Security Framework and Analysis for the Quantum Internet
Zebo Yang, Ali Ghubaish, Raj Jain +5
With its significant security potential, the quantum internet is poised to revolutionize technologies like cryptography and communications. Although it boasts enhanced security ove…
Efficient Data Labeling and Optimal Device Scheduling in HWNs Using Clustered Federated Semi-Supervised Learning
Moqbel Hamood, Abdullatif Albaseer, Mohamed Abdallah +1
Clustered Federated Multi-task Learning (CFL) has emerged as a promising technique to address statistical challenges, particularly with non-independent and identically distributed…
Optimized Federated Multitask Learning in Mobile Edge Networks: A Hybrid Client Selection and Model Aggregation Approach
Moqbel Hamood, Abdullatif Albaseer, Mohamed Abdallah +2
We propose clustered federated multitask learning to address statistical challenges in non-independent and identically distributed data across clients. Our approach tackles complex…
Charging Ahead: A Hierarchical Adversarial Framework for Counteracting Advanced Cyber Threats in EV Charging Stations
Mohammed Al-Mehdhar, Abdullatif Albaseer, Mohamed Abdallah +1
The increasing popularity of electric vehicles (EVs) necessitates robust defenses against sophisticated cyber threats. A significant challenge arises when EVs intentionally provide…
Meta Reinforcement Learning for Strategic IoT Deployments Coverage in Disaster-Response UAV Swarms
Marwan Dhuheir, Aiman Erbad, Ala Al-Fuqaha
In the past decade, Unmanned Aerial Vehicles (UAVs) have grabbed the attention of researchers in academia and industry for their potential use in critical emergency applications, s…
Empowering HWNs with Efficient Data Labeling: A Clustered Federated Semi-Supervised Learning Approach
Moqbel Hamood, Abdullatif Albaseer, Mohamed Abdallah +1
Clustered Federated Multitask Learning (CFL) has gained considerable attention as an effective strategy for overcoming statistical challenges, particularly when dealing with non in…
Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally
Shawqi Al-Maliki, Adnan Qayyum, Hassan Ali +5
Deep Neural Networks (DNNs) have been the driving force behind many of the recent advances in machine learning. However, research has shown that DNNs are vulnerable to adversarial…
R2S100K: Road-Region Segmentation Dataset For Semi-Supervised Autonomous Driving in the Wild
Muhammad Atif Butt, Hassan Ali, Adnan Qayyum +3
Semantic understanding of roadways is a key enabling factor for safe autonomous driving. However, existing autonomous driving datasets provide well-structured urban roads while ign…
Membership Inference Attacks on DNNs using Adversarial Perturbations
Hassan Ali, Adnan Qayyum, Ala Al-Fuqaha +1
Several membership inference (MI) attacks have been proposed to audit a target DNN. Given a set of subjects, MI attacks tell which subjects the target DNN has seen during training.…
Motion Comfort Optimization for Autonomous Vehicles: Concepts, Methods, and Techniques
Mohammed Aledhari, Mohamed Rahouti, Junaid Qadir +3
This article outlines the architecture of autonomous driving and related complementary frameworks from the perspective of human comfort. The technical elements for measuring Autono…
Can We Revitalize Interventional Healthcare with AI-XR Surgical Metaverses?
Adnan Qayyum, Muhammad Bilal, Muhammad Hadi +5
Recent advancements in technology, particularly in machine learning (ML), deep learning (DL), and the metaverse, offer great potential for revolutionizing surgical science. The com…
Consistent Valid Physically-Realizable Adversarial Attack against Crowd-flow Prediction Models
Hassan Ali, Muhammad Atif Butt, Fethi Filali +2
Recent works have shown that deep learning (DL) models can effectively learn city-wide crowd-flow patterns, which can be used for more effective urban planning and smart city manag…
Topic Modeling Based on Two-Step Flow Theory: Application to Tweets about Bitcoin
Aos Mulahuwaish, Matthew Loucks, Basheer Qolomany +1
Digital cryptocurrencies such as Bitcoin have exploded in recent years in both popularity and value. By their novelty, cryptocurrencies tend to be both volatile and highly speculat…
Addressing Data Distribution Shifts in Online Machine Learning Powered Smart City Applications Using Augmented Test-Time Adaptation
Shawqi Al-Maliki, Faissal El Bouanani, Mohamed Abdallah +2
Data distribution shift is a common problem in machine learning-powered smart city applications where the test data differs from the training data. Augmenting smart city applicatio…
Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for Metaverses
Adnan Qayyum, Muhammad Atif Butt, Hassan Ali +6
Metaverse is expected to emerge as a new paradigm for the next-generation Internet, providing fully immersive and personalised experiences to socialize, work, and play in self-sust…