Nazife Baykal

E-mail

baykal@metu.edu.tr

Department

Graduate School of Informatics

ORCID

0000-0003-0432-8057

Web of Science Researcher ID

A-4883-2016

landusemix: A Python package for calculating land use mix Akyol, Mehmet Ali; Duzgun, Sebnem; Baykal, Nazife (2024-09-01) Integrating different land uses within a geographic area is essential to urban planning and development. Accurate and fast land use mix (LUM) measurement is necessary for evaluating urban diversity and sustainability. In t...
Identification of Land Use Mix Using Point-Based Geospatial Data in Urban Areas Akyol, Mehmet Ali; Taşkaya Temizel, Tuğba; Duzgun, Sebnem; Baykal, Nazife (2024-08-01) Identifying land use mix (LUM) in urban areas is challenging, often requiring extensive human intervention and fieldwork. Accurate classification of LUM is crucial for various disciplines, including urban planning, urban e...
Online DDoS attack detection using Mahalanobis distance and Kernel-based learning algorithm Cakmakci, Salva Daneshgadeh; Kemmerich, Thomas; Ahmed, Tarem; Baykal, Nazife (Elsevier BV, 2020-10-01) Distributed denial-of-service (DDoS) attacks are constantly evolving as the computer and networking technologies and attackers' motivations are changing. In recent years, several supervised DDoS detection algorithms have b...
Detection of DDoS Attacks and Flash Events Using Shannon Entropy, KOAD and Mahalanobis Distance Daneshgadeh, Salva; Ahmed, Tarem; Kemmerich, Thomas; Baykal, Nazife (2019-01-01) The growing number of internet based services and applications along with increasing adoption rate of connected wired and wireless devices presents opportunities as well as technical challenges and threads. Distributed Den...
A simulation environment for cybersecurity attack analysis based on network traffic logs Daneshgadeh, Salva; Oney, Mehmet Ugur; Kemmerich, Thomas; Baykal, Nazife (2019-01-01) The continued and rapid progress of network technology has revolutionized all modern critical infrastructures and business models. Technologies today are firmly relying on network and communication facilities which in turn...
An Empirical Investigation of DDoS and Flash Event Detection Using Shannon Entropy, KOAD and SVM Combined Daneshgadeh, Salva; Kemmerich, Thomas; Ahmed, Tarem; Baykal, Nazife (2019-01-01) In the world of internet and communication technologies where our personal and business lives are inextricably tied to internet enabled services and applications, Distributed Denial of Service (DDoS) attacks continue to ad...
I see EK: A lightweight technique to reveal exploit kit family by overall URL patterns of infection chains Suren, Emre; Angın, Pelin; Baykal, Nazife (2019-01-01) The prevalence and nonstop evolving technical sophistication of exploit kits (EKs) is one of the most challenging shifts in the modern cybercrime landscape. Over the last few years, malware infections via drive-by download...
A Hybrid Approach to Detect DDoS Attacks Using KOAD and the Mahalanobis Distance Daneshgadeh, Salva; Kemmerich, Thomas; Ahmed, Tarem; Baykal, Nazife (2018-11) Distributed Denial of Service (DDoS) attacks continue to adversely affect internet-based services and applications. Various approaches have been proposed to detect different types of DDoS attacks. The computational and mem...
DDoS Attack Modeling and Detection Using SMO Daneshgadeh, Salva; Baykal, Nazife; Ertekin Bolelli, Şeyda (2017-12-21) Over the last decade, Distributed Denial of Service (DDoS) attacks have been employed to cause huge financial and prestige loss to different kinds of e-business. Attackers also target governmental websites using DDoS attac...
Binary Classification Performance Measures/Metrics: A Comprehensive Visualized Roadmap to Gain New Insights Canbek, Gurol; SAĞIROĞLU, Şeref; Taşkaya Temizel, Tuğba; Baykal, Nazife (2017-10-08) Binary classification is one of the most frequent studies in applied machine learning problems in various domains, from medicine to biology to meteorology to malware analysis. Many researchers use some performance metrics ...

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