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20242026
most citedGPTs Window Shopping: An analysis of the Landscape of Custom ChatGPT Models

3 citations · 8 across the 14 of their papers we have counts for

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7 papers · 1 filter

cs.CR2026

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…

cs.CR2026

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…

cs.CR2025

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…

cs.CR20251 cited

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…

cs.CR2025

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…

cs.CR2025

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…