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Doktor Öğretim Üyesi Hakan AydınMühendislik Fakültesi/Bilgisayar Mühendisliği Bölümü/Bilgisayar Mühendisliği Pr. /
Erişime Açık

CYBER SECURITY IN INDUSTRIAL CONTROL SYSTEMS (ICS): A SURVEY OF ROWHAMMER VULNERABILITY

Hakan Aydın

Increasing dependence on Information and Communication Technologies (ICT) and especially on the Internet in Industrial Control Systems (ICS) has made these systems the primary target of cyber-attacks. As ICS are extensively used in Critical Infrastructures (CI), this makes CI more vulnerable to cyber-attacks and their protection becomes an important issue. On the other hand, cyberattacks can exploit not only software but also physics; that is, they can target the fundamental physical aspects of computation. The newly discovered RowHammer (RH) fault injection attack is a serious vulnerability t ...Daha fazlası

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A Brain MRI Segmentation Method Using Feature Weighting and a Combination of Efficient Visual Features

Taymaz Akan

Determining the area of brain tumors is an essential and fundamental step in automatic diagnosis and treatment systems. The authors present a method based on a combination of efficient visual features and fuzzy c-means clustering to detect brain tumors. For this purpose, first, the background area of the images is removed by the new thresholding method, then the useful and efficient features are extracted. The authors use this new feature space for clustering-based segmentation. The proposed clustering algorithm gives a different importance to the extracted features in the segmentation process ...Daha fazlası

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A long short-term memory (LSTM)-based distributed denial of service (DDoS) detection and defense system design in public cloud network environment

Hakan Aydın

The fact that cloud systems are under the increasing risks of cyber attacks has made the phenomenon of information security first a need and then a necessity for these systems. Distributed Denial of Service (DDoS) attacks can exploit, disrupt, change, prevent or damage cloud services. Accurate and timely detection and prevention of these attacks are very important in terms of ensuring information security. During the COVID-19 period, the increase in the use of information technologies and especially the internet has made cyber attacks a real concern. Deep learning (DL) has become widely used f ...Daha fazlası

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Comparison of Classification Success Rates of Different Machine Learning Algorithms in the Diagnosis of Breast Cancer

Hakan Aydın

Objective: To identify which Machine Learning (ML) algorithms are the most successful in predicting and diagnosing breast cancer according to accuracy rates. Methods: The “College of Wisconsin Breast Cancer Dataset”, which consists of 569 data and 30 features, was classified using Support Vector Machine (SVM), Naive Bayes (NB), Random Forest (RF), Decision Tree (DT), K-Nearest Neighbor (KNN), Logistic Regression (LR), Multilayer Perceptron (MLP), Linear Discriminant Analysis (LDA), XgBoost (XGB), Ada-Boost (ABC) and Gradient Boosting (GBC) ML algorithms. Before the classification process, the ...Daha fazlası

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Netflix Verileri Üzerinde TF-IDF Algoritması ve Kosinüs Benzerliği ile Bir İçerik Öneri Sistemi Uygulaması

Hakan Aydın

Dijital platform kullanıcıları, bu platformların sunduğu özelleştirilmiş hizmetlerden yararlanmak ve bunları zaman ve mekan bağımsız olarak tüketmek istemektedirler. İnternet üzerinden yayın yapan bu platformlar arasında dünya çapında en yaygın olanlardan biri de Netflix’tir. Bu çalışmanın amacı TF-IDF (term frequency–inverse document frequency) algoritması ve Kosinüs Benzerliği (Cosine Similarity) ile Doğal Dil İşleme (NLP) ile Netflix kullanıcı verileri üzerinde bir içerik öneri sistemi uygulaması geliştirmektir. Bu bağlamda çalışmamızda yapılan analizler ile benzerlik yöntemleri ve uygun eş ...Daha fazlası

Süresiz Ambargo

Internet of things security: A multi-agent-based defense system design

Hakan Aydın

The increasing Internet of Things (IoT) network complexity and sophisticated Distributed Denial of Service (DDoS) attacks at machine speeds make accurate and timely detection and mitigation of these attacks a challenging activity. This study presents a multi-agent-based system design (MAS-IoT) against DDoS attacks in the IoT network. The MAS-IoT consists of different types of agents which communicate using Advanced Encryption Standard (AES). In the context of the study, DDoS attacks were detected using a long-short-term memory (LSTM)-based model (LSTMIoT) developed based on the CIC-IoT-2022 da ...Daha fazlası

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