Samet Yılmaz Temel

My Interests

I have been interested in the field of cyber security, software,ai technologies, machine learning and computer technologies for approximately 10 years. I have been involved in various studies and projects in these areas.

Competitions

I have participated in competitions within TUBITAK and TEKNOFEST. Additionally, I have competed in hackathon competitions within TEKNOFEST twice in the past years.

Practices

I regularly practice in lab environments and on platforms such as Hack The Box and TryHackMe. I am proud to be in the top 1% of the world ranking on TryHackMe.com.

School Projects

I actively participate in projects at my school to improve my skills. I serve as the president of the Forensic Informatics Community within my school, where I lead projects and trainings.

R&D Coordination

I manage our R&D coordination efforts and prepare project teams for competitions.

Education

In addition to my other activities, I am pursuing a distance education program in Computer Science at Harvard University.

Projects

Detection of Deepfake Content With The Artificial Intelligence | Project Manager | Team Leader |

The phrase "System that detects deficiencies with artificial intelligence algorithms on the anomalies of deepfake content published on the internet" describes a system that helps detect deepfake content published on the internet using artificial intelligence algorithms. This system is specifically designed to detect manipulated content using deepfake techniques. Equipped with artificial intelligence algorithms, such as deep learning and machine learning, it analyzes this content to identify signs or anomalies of deepfake manipulation. For instance, it can detect signs of deepfake manipulation such as facial synthesis, voice synthesis, perspective changes, and lighting variations. The system automatically scans content published on the internet and identifies content with indications of deepfake manipulation. Thus, it helps prevent the spread of manipulated media content and informs the public about fake content. Such a system can be used by media companies, social media platforms, news organizations, and other internet content providers to enhance the reliability of the internet and reduce the risk of information manipulation.

Cyber Attack/Defense, Intelligence/Counterintelligence and Forensic Investigations on UAV/UAV Vehicles | Project Manager | Team Leader |

This statement outlines a systematic approach to managing cybersecurity threats in the context of unmanned aerial vehicles (UAVs). The process begins with the formulation of offensive and defensive strategies tailored specifically to UAVs, addressing vulnerabilities and implementing safeguards against potential cyberattacks. Following this, it involves the execution of cyber assaults and corresponding defensive actions, reflecting the dynamic nature of cybersecurity operations. Subsequently, the focus shifts to intelligence gathering and counterintelligence activities, emphasizing the importance of understanding and mitigating emerging threats. Finally, the process concludes with forensic informatics investigations, which involve detailed analysis and attribution of security incidents to inform future defensive strategies. Overall, this approach underscores the comprehensive and proactive nature of cybersecurity measures designed to safeguard UAVs against evolving cyber threats.

System that Scrapes Biometric Data from Open Data on the Internet with the Help of Artificial Intelligence Algorithms | Project Manager | Team Leader |

Due to the extensive utilization of social media and the general populace's lack of vigilance, individuals frequently disclose substantial amounts of their biometric data unknowingly across various social media platforms throughout the day. Consequently, to safeguard the integrity and confidentiality of this sensitive information, innovative data scraping techniques are employed to identify and extract such data. Subsequently, once the accuracy and relevance of the collected data are verified, pertinent feedback is furnished to the respective users, facilitating their awareness and enabling them to take appropriate measures to protect their privacy and security. At this stage, artificial intelligence (AI) and machine learning (ML) techniques play an important role in securing biometric data. First, AI and ML algorithms can be used to collect and analyze data. These algorithms process large amounts of data quickly, enabling biometric data to be detected and verified. AI and ML can also be used in techniques such as data encryption and anonymization to protect the privacy of biometric data. These techniques protect against unauthorized access by ensuring that data is stored and transmitted securely. Furthermore, artificial intelligence and machine learning can be used to detect anomalies in biometric data and identify potential threats. In this way, automated alert systems can be developed to determine whether users' data is at risk of unauthorized use or malicious activity. Finally, by analyzing users' interactions with their biometric data, artificial intelligence and machine learning techniques can predict future usage behavior and provide personalized security recommendations. In this way, users can make safer and more informed decisions.

Cyberattack Detection and Prevention Automation with Machine Learning/LLM Model for MAIN | Project Manager | Team Leader |

Cyberattack identification and defense automation is a crucial aspect of cybersecurity, particularly in the context of rapidly evolving threats and sophisticated attack techniques. This process involves the use of advanced algorithms and techniques to identify patterns and anomalies in network traffic and system behavior that may indicate a cyberattack. One approach to achieving this is through the analysis of attack and defense vectors, which are essentially the methods and strategies used by attackers and defenders, respectively. By analyzing historical attack data and known defense strategies, machine learning algorithms can be trained to recognize patterns associated with specific types of attacks and corresponding defense measures. Once these patterns are identified and matched in the dataset, automated defense mechanisms can be triggered to respond to potential threats in real-time. This proactive approach to cybersecurity not only helps in detecting and mitigating cyberattacks more effectively but also enables organizations to better adapt to emerging threats and protect their systems and data from unauthorized access and exploitation.

Large language model developed for educational technologies that can prepare multiple choice questions on custom topics | Project Manager | Team Leader |

A large language model developed for educational technologies is designed to facilitate the creation of multiple-choice questions tailored to specific topics. This model leverages advanced natural language processing techniques to generate a wide range of questions based on the provided subject matter. By inputting custom topics, educators and content creators can utilize this tool to efficiently generate quizzes, assessments, or study materials. The model's ability to comprehend and analyze text enables it to produce questions that accurately assess students' understanding of the given topics. Additionally, its adaptability allows for the creation of diverse question types, ensuring comprehensive coverage of the subject matter. Overall, this model serves as a valuable resource for educators seeking to enhance the learning experience through personalized and effective assessment tools.

Samet Yılmaz Temel

My Interests

Competitions

Practices

School Projects

R&D Coordination

Education

Attended Events

Education Events

Skills

Programing Languages & Technologies

Languages

Business

Volunteering

Education

Projects

Connections