5 citations · 24 across the 27 of their papers we have counts for
27 papers
MulRobBench: A Decision-Level Benchmark for Safe and Security-Policy-Compliant Multimodal UAV Agents
Belal S. Alsinglawi, Weizheng Wang, Junyi Wu +4
In IoT-enabled smart-city settings, Uncrewed Aerial Vehicles (UAVs) are evolving from passive sensing platforms into cyber-physical decision makers that must respect operational ru…
HPC-LLM: Practical Domain Adaptation and Retrieval-Augmented Generation for HPC Support
Nourin Shahin, Izzat Alsmadi
Modern scientific research increasingly depends on High-Performance Computing (HPC) infrastructures, yet many researchers face significant operational barriers when interacting wit…
A Unified Compliance Aggregator Framework for Automated Multi-Tool Security Assessment of Linux Systems
Sheldon Paul, Izzat Alsmadi
Assessing the security posture of modern computing systems typically requires the use of multiple specialized tools. These tools focus on different aspects such as configuration co…
TAMUSA-Chat: A Domain-Adapted Large Language Model Conversational System for Research and Responsible Deployment
Izzat Alsmadi, Anas Alsobeh
This paper presents TAMUSA-Chat, a research-oriented framework for building domain-adapted large language model conversational systems. The work addresses critical challenges in ad…
Benchmarking LLAMA Model Security Against OWASP Top 10 For LLM Applications
Nourin Shahin, Izzat Alsmadi
As large language models (LLMs) move from research prototypes to enterprise systems, their security vulnerabilities pose serious risks to data privacy and system integrity. This st…
Security Hardening Using FABRIC: Implementing a Unified Compliance Aggregator for Linux Servers
Sheldon Paul, Izzat Alsmadi
This paper presents a unified framework for evaluating Linux security hardening on the FABRIC testbed through aggregation of heterogeneous security auditing tools. We deploy three…
An empirical analysis of zero-day vulnerabilities disclosed by the zero day initiative
Apurva Shet, Izzat Alsmadi
Zero-day vulnerabilities represent some of the most critical threats in cybersecurity, as they correspond to previously unknown flaws in software or hardware that are actively expl…
Intrusion Detection in Internet of Vehicles Using Machine Learning
Hop Le, Izzat Alsmadi
The Internet of Vehicles (IoV) has evolved modern transportation through enhanced connectivity and intelligent systems. However, this increased connectivity introduces critical vul…
HeSRN: Representation Learning On Heterogeneous Graphs via Slot-Aware Retentive Network
Yifan Lu, Ziyun Zou, Belal Alsinglawi +6
Graph Transformers have recently achieved remarkable progress in graph representation learning by capturing long-range dependencies through self-attention. However, their quadratic…
Exploring the Potential of Large Language Models in Public Transportation: San Antonio Case Study
Ramya Jonnala, Gongbo Liang, Jeong Yang +1
The integration of large language models (LLMs) into public transit systems presents a transformative opportunity to enhance urban mobility. This study explores the potential of LL…
Using Large Language Models in Public Transit Systems, San Antonio as a case study
Ramya Jonnala, Gongbo Liang, Jeong Yang +1
The integration of large language models into public transit systems represents a significant advancement in urban transportation management and passenger experience. This study ex…
Navigating the Shadows: Unveiling Effective Disturbances for Modern AI Content Detectors
Ying Zhou, Ben He, Le Sun
With the launch of ChatGPT, large language models (LLMs) have attracted global attention. In the realm of article writing, LLMs have witnessed extensive utilization, giving rise to…
Transforming Computer Security and Public Trust Through the Exploration of Fine-Tuning Large Language Models
Garrett Crumrine, Izzat Alsmadi, Jesus Guerrero +1
Large language models (LLMs) have revolutionized how we interact with machines. However, this technological advancement has been paralleled by the emergence of "Mallas," malicious…
Predicting Question Quality on StackOverflow with Neural Networks
Mohammad Al-Ramahi, Izzat Alsmadi, Abdullah Wahbeh
The wealth of information available through the Internet and social media is unprecedented. Within computing fields, websites such as Stack Overflow are considered important source…
A Review on Searchable Encryption Functionality and the Evaluation of Homomorphic Encryption
Brian Kishiyama, Izzat Alsmadi
Cloud Service Providers, such as Google Cloud Platform, Microsoft Azure, or Amazon Web Services, offer continuously evolving cloud services. It is a growing industry. Businesses, s…
Mutation-Based Adversarial Attacks on Neural Text Detectors
Gongbo Liang, Jesus Guerrero, Izzat Alsmadi
Neural text detectors aim to decide the characteristics that distinguish neural (machine-generated) from human texts. To challenge such detectors, adversarial attacks can alter the…
A Mutation-based Text Generation for Adversarial Machine Learning Applications
Jesus Guerrero, Gongbo Liang, Izzat Alsmadi
Many natural language related applications involve text generation, created by humans or machines. While in many of those applications machines support humans, yet in few others, (…
Balanced Datasets for IoT IDS
Alaa Alhowaide, Izzat Alsmadi, Jian Tang
As the Internet of Things (IoT) continues to grow, cyberattacks are becoming increasingly common. The security of IoT networks relies heavily on intrusion detection systems (IDSs).…
Synthetic Text Detection: Systemic Literature Review
Jesus Guerrero, Izzat Alsmadi
Within the text analysis and processing fields, generated text attacks have been made easier to create than ever before. To combat these attacks open sourcing models and datasets h…
Benchmark Assessment for DeepSpeed Optimization Library
Gongbo Liang, Izzat Alsmadi
Deep Learning (DL) models are widely used in machine learning due to their performance and ability to deal with large datasets while producing high accuracy and performance metrics…
Adversarial Attacks and Defenses for Social Network Text Processing Applications: Techniques, Challenges and Future Research Directions
Izzat Alsmadi, Kashif Ahmad, Mahmoud Nazzal +4
The growing use of social media has led to the development of several Machine Learning (ML) and Natural Language Processing(NLP) tools to process the unprecedented amount of social…
Event Detection in Twitter: A Content and Time-Based Analysis
Izzat Alsmadi, Michael O'Brien
The detection of events from online social networks is a recent, evolving field that attracts researchers from across a spectrum of disciplines and domains. Here we report a time-s…
An ontological analysis of misinformation in online social networks
Izzat Alsmadi, Iyad Alazzam, Mohammad A. AlRamahi
The internet, Online Social Networks (OSNs) and smart phones enable users to create tremendous amount of information. Users who search for general or specific knowledge may not hav…
Adversarial Machine Learning in Text Analysis and Generation
Izzat Alsmadi
The research field of adversarial machine learning witnessed a significant interest in the last few years. A machine learner or model is secure if it can deliver main objectives wi…