activity
20222026
most citedSecure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for Metaverses

84 citations · 140 across the 19 of their papers we have counts for

collaborators

20 papers

cs.CL2026

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…

cs.AI2025

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…

cs.CR2025

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…

cs.CV2025

TEMSET-24K: Densely Annotated Dataset for Indexing Multipart Endoscopic Videos using Surgical Timeline Segmentation

Muhammad Bilal, Mahmood Alam, Deepa Bapu +16

Indexing endoscopic surgical videos is vital in surgical data science, forming the basis for systematic retrospective analysis and clinical performance evaluation. Despite its sign…

cs.CR2025★ 32 cited

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…

cs.CL2025★ 3 cited

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…

cs.CV2025

Surgical Scene Understanding in the Era of Foundation AI Models: A Comprehensive Review

Ufaq Khan, Umair Nawaz, Adnan Qayyum +5

Recent advancements in machine learning (ML) and deep learning (DL), particularly through the introduction of Foundation Models (FMs), have significantly enhanced surgical scene un…

cs.LG2024★ 2 cited

R-CONV: An Analytical Approach for Efficient Data Reconstruction via Convolutional Gradients

Tamer Ahmed Eltaras, Qutaibah Malluhi, Alessandro Savino +3

In the effort to learn from extensive collections of distributed data, federated learning has emerged as a promising approach for preserving privacy by using a gradient-sharing mec…

cs.LG2023

MedISure: Towards Assuring Machine Learning-based Medical Image Classifiers using Mixup Boundary Analysis

Adam Byfield, William Poulett, Ben Wallace +6

Machine learning (ML) models are becoming integral in healthcare technologies, presenting a critical need for formal assurance to validate their safety, fairness, robustness, and t…

eess.IV2023★ 3 cited

Multivessel Coronary Artery Segmentation and Stenosis Localisation using Ensemble Learning

Muhammad Bilal, Dinis Martinho, Reiner Sim +8

Coronary angiography analysis is a common clinical task performed by cardiologists to diagnose coronary artery disease (CAD) through an assessment of atherosclerotic plaque's accum…

cs.CR2023★ 1 cited

Privacy Preserving Large Language Models: ChatGPT Case Study Based Vision and Framework

Imdad Ullah, Najm Hassan, Sukhpal Singh Gill +5

The generative Artificial Intelligence (AI) tools based on Large Language Models (LLMs) use billions of parameters to extensively analyse large datasets and extract critical privat…

cs.LG2023

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…

cs.CR2023★ 5 cited

Privacy Preservation in Artificial Intelligence and Extended Reality (AI-XR) Metaverses: A Survey

Mahdi Alkaeed, Adnan Qayyum, Junaid Qadir

The metaverse is a nascent concept that envisions a virtual universe, a collaborative space where individuals can interact, create, and participate in a wide range of activities. P…

cs.CV2023

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…

cs.LG2023★ 3 cited

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.…

eess.IV2023

Robust Surgical Tools Detection in Endoscopic Videos with Noisy Data

Adnan Qayyum, Hassan Ali, Massimo Caputo +7

Over the past few years, surgical data science has attracted substantial interest from the machine learning (ML) community. Various studies have demonstrated the efficacy of emergi…

cs.SD2023★ 1 cited

Lightweight Toxicity Detection in Spoken Language: A Transformer-based Approach for Edge Devices

Ahlam Husni Abu Nada, Siddique Latif, Junaid Qadir

Toxicity is a prevalent social behavior that involves the use of hate speech, offensive language, bullying, and abusive speech. While text-based approaches for toxicity detection a…

cs.AI2023★ 3 cited

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…

cs.LG2023★ 3 cited

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…

cs.AI2022★ 84 cited

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…