2 citations · 2 across the 5 of their papers we have counts for
6 papers
Small, Free, and Effective: Orchestrating Open-Weight Small Language Models to Outperform Single LLM for Malware Analysis
Adel ElZemity, Shujun Li, Budi Arief
Malware analysis demands rapid interpretation of complex detonation reports spanning filesystem, network, and process behaviours. While large language models (LLMs) demonstrate imp…
APIOT: Autonomous Vulnerability Management Across Bare-Metal Industrial OT Networks
Adel ElZemity, Budi Arief, Shujun Li +6
Operational technology (OT) devices run safety-critical physical processes, yet their security testing remains manual and expert-intensive. Autonomous security agents could ease th…
Agentic Knowledge Distillation: Autonomous Training of Small Language Models for SMS Threat Detection
Adel ElZemity, Joshua Sylvester, Budi Arief +1
SMS-based phishing (smishing) attacks have surged, yet training effective on-device detectors requires labelled threat data that quickly becomes outdated. To deal with this issue,…
Analysing Safety Risks in LLMs Fine-Tuned with Pseudo-Malicious Cyber Security Data
Adel ElZemity, Budi Arief, Shujun Li
Large language models (LLMs) have been used in many application domains, including cyber security. The application of LLMs in the cyber security domain presents significant opportu…
CyberLLMInstruct: A Pseudo-malicious Dataset Revealing Safety-performance Trade-offs in Cyber Security LLM Fine-tuning
Adel ElZemity, Budi Arief, Shujun Li
The integration of large language models (LLMs) into cyber security applications presents both opportunities and critical safety risks. We introduce CyberLLMInstruct, a dataset of…
Privacy Threats and Countermeasures in Federated Learning for Internet of Things: A Systematic Review
Adel ElZemity, Budi Arief
Federated Learning (FL) in the Internet of Things (IoT) environments can enhance machine learning by utilising decentralised data, but at the same time, it might introduce signific…