3 citations · 8 across the 14 of their papers we have counts for
15 papers
Beyond Model Scaling: Rethinking Sequence Construction for Transformer-based Network Intrusion Detection
Zeeshan Zulkifl Shah, Muhammad Ikram, Dali Kaafar +1
Transformer-based network intrusion detection systems (NIDS) have shown strong potential for detecting multi-stage cyberattacks, yet most methods construct input sequences using fi…
Johnny Still Receives Spam SMS: Assessing the Robustness of SMS Spam Detection
Muhammad Salman, Muhammad Islam, Muhammad Ikram +1
SMS spam detection systems often achieve high accuracy in controlled environments but struggle against adversarial attacks and increasingly sophisticated spam tactics in real-world…
Scalable AI-Driven Analytics for User Engagement and Stance Detection on Social Media
Thammitage Piyumi Wathsala Seneviratne, Muhammad Ikram, Dinusha Vatsalan +2
Social media platforms have become a major vector for the large-scale dissemination of misinformation and conspiracy content, posing significant risks to public trust, health, and…
Pro-ZD: A Transferable Graph Neural Network Approach for Proactive Zero-Day Threats Mitigation
Nardine Basta, Firas Ben Hmida, Houssem Jmal +3
In today's enterprise network landscape, the combination of perimeter and distributed firewall rules governs connectivity. To address challenges arising from increased traffic and…
LTV-YOLO: A Lightweight Thermal Object Detector for Young Pedestrians in Adverse Conditions
Abdullah Jirjees, Ryan Myers, Muhammad Haris Ikram +1
Detecting vulnerable road users (VRUs), particularly children and adolescents, in low light and adverse weather conditions remains a critical challenge in computer vision, surveill…
Prompting the Priorities: A First Look at Evaluating LLMs for Vulnerability Triage and Prioritization
Osama Al Haddad, Muhammad Ikram, Ejaz Ahmed +1
Security analysts face increasing pressure to triage large and complex vulnerability backlogs. Large Language Models (LLMs) offer a potential aid by automating parts of the interpr…
RINSER: Accurate API Prediction Using Masked Language Models
Muhammad Ejaz Ahmed, Christopher Cody, Muhammad Ikram +5
Malware authors commonly use obfuscation to hide API identities in binary files, making analysis difficult and time-consuming for a human expert to understand the behavior and inte…
A Large-Scale Empirical Analysis of Custom GPTs' Vulnerabilities in the OpenAI Ecosystem
Sunday Oyinlola Ogundoyin, Muhammad Ikram, Hassan Jameel Asghar +2
Millions of users leverage generative pretrained transformer (GPT)-based language models developed by leading model providers for a wide range of tasks. To support enhanced user in…
Enhancing Malware Fingerprinting through Analysis of Evasive Techniques
Alsharif Abuadbba, Sean Lamont, Ejaz Ahmed +6
As malware detection evolves, attackers adopt sophisticated evasion tactics. Traditional file-level fingerprinting, such as cryptographic and fuzzy hashes, is often overlooked as a…
SpaLLM-Guard: Pairing SMS Spam Detection Using Open-source and Commercial LLMs
Muhammad Salman, Muhammad Ikram, Nardine Basta +1
The increasing threat of SMS spam, driven by evolving adversarial techniques and concept drift, calls for more robust and adaptive detection methods. In this paper, we evaluate the…
On the Robustness of Malware Detectors to Adversarial Samples
Muhammad Salman, Benjamin Zi Hao Zhao, Hassan Jameel Asghar +3
Adversarial examples add imperceptible alterations to inputs with the objective to induce misclassification in machine learning models. They have been demonstrated to pose signific…
SenTopX: Benchmark for User Sentiment on Various Topics
Hina Qayyum, Muhammad Ikram, Benjamin Zhao +3
Toxic sentiment analysis on Twitter (X) often focuses on specific topics and events such as politics and elections. Datasets of toxic users in such research are typically gathered…
GPTs Window Shopping: An analysis of the Landscape of Custom ChatGPT Models
Benjamin Zi Hao Zhao, Muhammad Ikram, Mohamed Ali Kaafar
OpenAI's ChatGPT initiated a wave of technical iterations in the space of Large Language Models (LLMs) by demonstrating the capability and disruptive power of LLMs. OpenAI has prom…
On mission Twitter Profiles: A Study of Selective Toxic Behavior
Hina Qayyum, Muhammad Ikram, Benjamin Zi Hao Zhao +3
The argument for persistent social media influence campaigns, often funded by malicious entities, is gaining traction. These entities utilize instrumented profiles to disseminate d…
Exploring the Distinctive Tweeting Patterns of Toxic Twitter Users
Hina Qayyum, Muhammad Ikram, Benjamin Zi Hao Zhao +3
In the pursuit of bolstering user safety, social media platforms deploy active moderation strategies, including content removal and user suspension. These measures target users eng…