Erten, Yusuf Murat

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14365/6667
Name Variants
Erten, Yusuf
Erten, Y. Murat
Erten, YM
Erten, Y. M.
Erten, Yusuf Murat.
Y. M. Erten
Erten, Yusuf M.
Job Title
Email Address
yusuf.erten@ieu.edu.tr
Main Affiliation
05.05. Computer Engineering
Status
Current Staff
Website
ORCID ID
0000-0001-9537-7414
Scopus Author ID
55665216700
Turkish CoHE Profile ID
AC6D00E31A5E7AF9
Google Scholar ID
XY_kpWgAAAAJ
WoS Researcher ID
ABE-9688-2020
Files
Yusuf_Murat_Erten.jpg (11.61 KB)

Sustainable Development Goals

Documents

34

Citations

184

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6

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Documents

22

Citations

73

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Scholarly Output

7

Articles

2

Views / Downloads

38/1141

Supervised MSc Theses

1

Supervised PhD Theses

0

WoS Citation Count

2

Scopus Citation Count

5

WoS h-index

1

Scopus h-index

1

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0

Projects

0

WoS Citations per Publication

0.29

Scopus Citations per Publication

0.71

Open Access Source

3

Supervised Theses

1

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Now showing 1 - 7 of 7
  • Thumbnail Image
    Conference Object
    Comparison of Different Weather Data Acquisition Methods
    (Institute of Electrical and Electronics Engineers Inc., 2024) Evcin, E.; Erten, Y.M.
    The Internet of Things is widely used in various aspects of our lives, including weather data collection which is usually performed using commercially available sensors such as DHT11 and microcontrollers such as Arduino. This data, however, is also available through various websites. In this study, we have developed a system using an ESP32 microcontroller to locally obtain temperature and humidity data using a DHT11 sensor and compared it with data retrieved from two different weather websites. We have compared the values downloaded with each other, as well as the sensor data obtained locally. Our results show that the temperature data obtained from the two websites are in 92% agreement with each other and the sensor data is, on average, in 87% agreement with the data from the websites. These figures are 72% and 75% respectively for humidity measurements. © 2024 IEEE.
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    Conference Object
    Citation - Scopus: 4
    Helpchain: a Blockchain Based Disaster Management System
    (Institute of Electrical and Electronics Engineers Inc., 2023) Parildar, B.; Sayin,; Turkzeybek, F.Z.; Kucukoz, O.; Erten, Yusuf Murat; Sayin, Doruk
    The motivation of this study is to design a blockchain-based, decentralized, and trustworthy disaster management system. The proposed system provides an inventory of residents in the disaster areas such as earthquake zones. This information may be used by the relief agencies in case of natural disasters to track the people living in the area and initiate a rescue operation if needed. The system involves a mobile application for individual users to register and indicate their status, blockchain network to keep the data, and a desktop application to be used by disaster relief agencies to manage the whereabouts of the possible victims and organize their operations. We have built and tested a working system with Sepolia Blockchain (Ethereum Test Network) with test users, but a specific blockchain network designed for this purpose should be implemented for the project to be more feasible. © 2023 IEEE.
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    Article
    Performance Analysis and Feature Selection for Network-Based Intrusion Detection with Deep Learning
    (Turkiye Klinikleri, 2022) Caner, Serhat; Erdoğmuş, Nesli; Erten, Y. Murat
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    Article
    Citation - Scopus: 1
    Performance Analysis and Feature Selection for Network-Based Intrusion Detection With Deep Learning
    (Scientific Technical Research Council Turkey-Tubitak, 2022) Caner, Serhat; Erdogmus, Nesli; Erten, Y. Murat
    An intrusion detection system is an automated monitoring tool that analyzes network traffic and detects malicious activities by looking out either for known patterns of attacks or for an anomaly. In this study, intrusion detection and classification performances of different deep learning based systems are examined. For this purpose, 24 deep neural networks with four different architectures are trained and evaluated on CICIDS2017 dataset. Furthermore, the best performing model is utilized to inspect raw network traffic features and rank them with respect to their contributions to success rates. By selecting features with respect to their ranks, sets of varying size from 3 to 77 are assessed in terms of classification accuracy and time efficiency. The results show that recurrent neural networks with a certain level of complexity can achieve comparable success rates with state-of-the-art systems using a small feature set of size 9; while the average time required to classify a test sample is halved compared to the complete set.
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    Conference Object
    Citation - WoS: 2
    Secure Iot Update Using Blockchain
    (IEEE, 2021) Kaptan, Melike; Tomur, Emrah; Ayav, Tolga; Erten, Yusuf Murat
    In this study a platform is devised to send automatic remote updates for embedded devices. In this scenario there are Original Equipment Manufacturers (OEMs), Software suppliers, blockchain nodes, Gateways and embedded devices. OEMs and software suppliers are there to keep their software on Inter Planetary File System (IPFS) and send the meta-data and hashes of their software to the blockchain nodes in order to keep this information distributed and ready to be requested and used. There are also gateways which are the members of the blockchain and the IPFS network. Gateways are responsible for asking for a specific update for specific devices from IPFS database using the meta-data kept on the blockchain, and they will send those hashed secure updates to the devices. In order to provide a traceable data keeping platform, gateway update operations are handled as transactions in a second blockchain network which is the clockchain of the gateways. The system was implemented as of the two separate blockchain networks and it has been shown that, despite the calculation overhead of the member devices, by separating the functions between the two blockchain networks a more reliable and secure platform can be achieved.
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    Conference Object
    Inferring Location Information From Cell Data: The Viterbi Algorithm As A Case Study
    (Institute of Electrical and Electronics Engineers Inc., 2025) Yaman, Okan; Rasmussen, Kasper; Ayav, Tolga; Erten, Yusuf Murat
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    Master Thesis
    Effects of radio duty cycle to energy consumption in wireless sensor network
    (İzmir Ekonomi Üniversitesi, 2024) Çetinbaş, Oğuzhan; Erten, Yusuf Murat
    Kablosuz Sensör Ağları, kablolara ihtiyaç duymadan veri alışverişi yapılması açısından çok yararlı olmakla birlikte pil kapasitesi sınırlı olduğundan, güç tüketimi problem olarak karşımıza çıkmaktadır. Radyo görev döngüsü protokolleri, veri iletimini ve güç tüketimini verimli bir şekilde kullanmak için uyanma aralığını (WUI) programlayan mekanizmalardır. Bu tez çalışmasında, farklı uyanma aralıklarına (WUI) sahip iki farklı görev döngüsü olan X-MAC ve ContikiMAC protokolleri arasında bir karşılaştırma yapılmıştır. Bu iki protokol Cooja simülatöründe Sky motes kullanılarak test edilmiş ve farklı kablosuz sensör ağları oluşturularak deneysel bir çalışma gerçekleştirilmiştir. Ağlar farklı uyanma aralıkları için analiz edilip sonuçlar varsayılan özelliklerde elde edilen bulgularla karşılaştırılmıştır. Burada amaç radyoyu daha kısa süre açık tutarak sensörlerin güç tüketimini azaltmak, dolayısıyla ağın ömrünü uzatmak ve bu yaklaşımdan kaynaklanan paket kaybı ve gecikmelerini gözlemlemektir. Sonuçlar, uyanma aralığı parametresi kontrol edildiğinde paket kaybında önemli bir değişiklik olmadan enerji tüketiminin belirli aralıklarla azaltılabileceğini göstermektedir.