A5060255810- Network Security and Intrusion Detection
- Attention Deficit Hyperactivity Disorder
- Neural and Behavioral Psychology Studies
- Internet Traffic Analysis and Secure E-voting
- Data Management and Algorithms
- Advanced Malware Detection Techniques
- Children's Physical and Motor Development
- Data Mining Algorithms and Applications
- Adversarial Robustness in Machine Learning
- Video Analysis and Summarization
- Anomaly Detection Techniques and Applications
- Web Application Security Vulnerabilities
Recep Tayyip Erdoğan University
2023-2024
Gazi University
2022
Web applications are often exposed to attacks because of the critical information and valuable assets they host. In this study, Bi-LSTM based web application security models were developed in order detect classify them into binary or multiple classes using HTTP requests. A novel data augmentation technique on self-adapting noise adding method (DA-SANA) was developed. The DA-SANA solves low sensitivity problem caused by imbalanced complex structure multi-class classification attack detection....
Data mining is an important technique used in many fields with the purpose of acquiring valuable information from big data.This study aims to reveal relations between attributes independent criminal records.The NIBRS database, which includes records USA that are recorded 2013, this study.The association rules created by Apriori algorithm have been extract relationships features experimental results show useful for analysis.This reveals different and allows authorities establish new old incidents.
: Attention-Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity. Traditional diagnostic methods, which depend on subjective assessments, often lack precision. This study evaluates the validity reliability of newly developed tool, Distractor-Embedded Auditory Continuous Performance Test (da-CPT), integrates auditory stimuli with distractors to enhance clinical utility ADHD diagnosis.
Detecting web attacks is a major challenge, and it observed that the use of simple models leads to low sensitivity or high false positive problems.In this study, we aim develop robust two-stage deep learning based stacked ensemble application firewall.Normal abnormal classification carried out in first stage proposed WAF model.The process types traffics postponed second using an integrated model.By way, clients' requests can be served without time delay, attack detected with sensitivity.In...