AISecHub

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AISecHub

@AISecHub

12 Jul 2025

Evaluating Language Models For Threat Detection in IoT Security Logs - arxiv.org/pdf/2507.02390 Log analysis is a relevant research field in cybersecurity as they can provide a source of information for the detection of threats to networks and systems. This paper presents a pipeline to use fine-tuned Large Language Models (LLMs) for anomaly detection and mitigation recommendation using IoT security logs. Utilizing classical machine learning classifiers as a baseline, three open-source LLMs are compared for binary and multiclass anomaly detection, with three strategies: zero-shot, few-shot prompting and fine-tuning using an IoT dataset. LLMs give better results on multi-class attack classification than the corresponding baseline models. By mapping detected threats to MITRE CAPEC, defining a set of IoT-specific mitigation actions, and fine-tuning the models with those actions, the models are able to provide a combined detection and recommendation guidance. #IoTSecurity #ThreatDetection #LLMSecurity #LogAnalysis #AIforCybersecurity #AnomalyDetection #MITRECAPEC #LLMfineTuning #FewShotLearning #ZeroShotLearning #CyberThreats #IoTLogs #AIThreatDetection #CyberDefense #LLMvsML #MulticlassClassification #SecurityAutomation #AIMitigation #AI4IoT #OpenSourceLLM

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Muhammed Musaddique

Muhammed Musaddique @zmusaddique_

6 Jun 2023

As I continue this machine learning expedition, I'm thrilled to unravel more insights and skills. ⚙️ #MachineLearning #MulticlassClassification #PerformanceMetrics #ConfusionMatrix #LearningInProgress #DeveloperJourneys

Data-Driven Science

Data-Driven Science @DrivenScience

31 Mar 2023

🌟 Dive into the fascinating world of #MulticlassClassification algorithms! 🧩 Explore popular techniques like Multinomial Naïve Bayes, Decision Trees & K-Nearest Neighbors to tackle diverse #MachineLearning challenges. Unleash the power of #DataScience! 🔥💡🚀 #AI #ML