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20212026
most citedIndividual Packet Features are a Risk to Model Generalisation in ML-Based Intrusion Detection

14 citations · 24 across the 10 of their papers we have counts for

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7 papers · 1 filter

cs.CR2026

IoT Device Identification with Machine Learning: Common Pitfalls and Best Practices

Kahraman Kostas, Rabia Yasa Kostas

This paper critically examines the device identification process using machine learning, addressing common pitfalls in existing literature. We analyze the trade-offs between identi…

cs.CR2024★ 1 cited

GeMID: Generalizable Models for IoT Device Identification

Kahraman Kostas, Rabia Yasa Kostas, Mike Just +1

With the proliferation of devices on the Internet of Things (IoT), ensuring their security has become paramount. Device identification (DI), which distinguishes IoT devices based o…

cs.CR2024★ 14 cited

Individual Packet Features are a Risk to Model Generalisation in ML-Based Intrusion Detection

Kahraman Kostas, Mike Just, Michael A. Lones

Machine learning is increasingly used for intrusion detection in IoT networks. This paper explores the effectiveness of using individual packet features (IPF), which are attributes…

cs.CR2024★ 3 cited

IoTGeM: Generalizable Models for Behaviour-Based IoT Attack Detection

Kahraman Kostas, Mike Just, Michael A. Lones

Previous research on behavior-based attack detection for networks of IoT devices has resulted in machine learning models whose ability to adapt to unseen data is limited and often…

cs.CR2023

LSTM based IoT Device Identification

Kahraman Kostas

While the use of the Internet of Things is becoming more and more popular, many security vulnerabilities are emerging with the large number of devices being introduced to the marke…

cs.CR2023

CNN-based IoT Device Identification: A Comparative Study on Payload vs. Fingerprint

Kahraman Kostas

The proliferation of the Internet of Things (IoT) has introduced a massive influx of devices into the market, bringing with them significant security vulnerabilities. In this diver…