108 citations · 132 across the 11 of their papers we have counts for
11 papers
There Are No Silly Questions: Evaluation of Offline LLM Capabilities from a Turkish Perspective
Edibe Yilmaz, Kahraman Kostas
The integration of large language models (LLMs) into educational processes introduces significant constraints regarding data privacy and reliability, particularly in pedagogically…
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…
Graph-Based Floor Separation Using Node Embeddings and Clustering of WiFi Trajectories
Rabia Yasa Kostas, Kahraman Kostas
Indoor positioning systems (IPSs) are increasingly vital for location-based services in complex multi-storey environments. This study proposes a novel graph-based approach for floo…
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…
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…
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…
Externally validating the IoTDevID device identification methodology using the CIC IoT 2022 Dataset
Kahraman Kostas, Mike Just, Michael A. Lones
In the era of rapid IoT device proliferation, recognizing, diagnosing, and securing these devices are crucial tasks. The IoTDevID method (IEEE Internet of Things 2022) proposes a m…
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…
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…
WiFi Based Distance Estimation Using Supervised Machine Learning
Kahraman Kostas, Rabia Yasa Kostas, Francisco Zampella +1
In recent years WiFi became the primary source of information to locate a person or device indoor. Collecting RSSI values as reference measurements with known positions, known as W…
IoTDevID: A Behavior-Based Device Identification Method for the IoT
Kahraman Kostas, Mike Just, Michael A. Lones
Device identification is one way to secure a network of IoT devices, whereby devices identified as suspicious can subsequently be isolated from a network. In this study, we present…